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{ unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst variants=['BASE','COMMIT_COW2','COMMIT_SHEEP2','COMMIT_MIX11','WAIT3'];const seeds=[9403,9419,9431,9461,9491];const opp='RITA_BASE';\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();const zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);for(const [n,p] of Object.entries({DYN:{animal_target:{COW:0,SHEEP:0}},RITA_BASE:{}})){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name): _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction owned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:any){const x:any={COW:owned(obs,'COW'),SHEEP:owned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1],q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction initialGoal(v:string){if(v==='COMMIT_COW2')return{COW:2,SHEEP:0};if(v==='COMMIT_SHEEP2')return{COW:0,SHEEP:2};if(v==='COMMIT_MIX11')return{COW:1,SHEEP:1};return null;}\nasync function play(v:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0;const goal=initialGoal(v);let commitmentDone=!goal;const diary:any[]=[];while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const own={COW:owned(obs,'COW'),SHEEP:owned(obs,'SHEEP')};targets={...own};if(goal&&!commitmentDone){commitmentDone=own.COW>=goal.COW&&own.SHEEP>=goal.SHEEP;if(!commitmentDone){targets={COW:Math.max(own.COW,goal.COW),SHEEP:Math.max(own.SHEEP,goal.SHEEP)};setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(goal.SHEEP>0?['SHEEP','COW']:['COW','SHEEP']));}}\nif(commitmentDone){if(v==='WAIT3'&&+obs.day<3){setHerd('DYN',own.COW,own.SHEEP,JSON.stringify(['COW','SHEEP']));targets={...own};}else{const total=own.COW+own.SHEEP,c=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:0});if(total<16&&c.choice)targets[c.choice]+=Math.min(2,16-total);setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP')));}}\nif([0,1,2,3,6,9,12,18].includes(+obs.day))diary.push({day:+obs.day,cash:obs.farms[pid].money,own:{...own},targets:{...targets},commitmentDone,shops:[...(obs.town?.unlocked_shops??[])]});}\ntry{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors,diary};}\nconst games:any[]=[];for(const v of variants)for(const seed of seeds){games.push(await play(v,seed,0));games.push(await play(v,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,bySeed:Object.fromEntries(seeds.map(seed=>{const x=rs.filter(r=>r.seed===seed);return[seed,{wins:x.filter(r=>r.win).length,avgMargin:x.reduce((a,r)=>a+r.margin,0)/x.length,avgBank:x.reduce((a,r)=>a+r.ours,0)/x.length}]}))};}const b=games.filter(g=>g.v==='BASE');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgMarginDelta:r.reduce((s,g,i)=>s+(g.margin-b[i].margin),0)/r.length,better:r.filter((g,i)=>g.margin>b[i].margin).length,worse:r.filter((g,i)=>g.marging.seed===9491&&g.seat===0).map(g=>({v:g.v,diary:g.diary}))},null,2));","import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst variants=['BASE','WAIT3'];const seeds=[12007,12113,12227,12347,12457,12569,12671,12781,12893,13001,13109,13217,13327,13441,13553,13669,13781,13883,13997,14107];const opp='RITA_BASE';\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();const zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);for(const [n,p] of Object.entries({DYN:{animal_target:{COW:0,SHEEP:0}},RITA_BASE:{}})){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name): _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction owned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:any){const x:any={COW:owned(obs,'COW'),SHEEP:owned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1],q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction initialGoal(v:string){if(v==='COMMIT_COW2')return{COW:2,SHEEP:0};if(v==='COMMIT_SHEEP2')return{COW:0,SHEEP:2};if(v==='COMMIT_MIX11')return{COW:1,SHEEP:1};return null;}\nasync function play(v:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0;const goal=initialGoal(v);let commitmentDone=!goal;const diary:any[]=[];while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const own={COW:owned(obs,'COW'),SHEEP:owned(obs,'SHEEP')};targets={...own};if(goal&&!commitmentDone){commitmentDone=own.COW>=goal.COW&&own.SHEEP>=goal.SHEEP;if(!commitmentDone){targets={COW:Math.max(own.COW,goal.COW),SHEEP:Math.max(own.SHEEP,goal.SHEEP)};setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(goal.SHEEP>0?['SHEEP','COW']:['COW','SHEEP']));}}\nif(commitmentDone){if(v==='WAIT3'&&+obs.day<3){setHerd('DYN',own.COW,own.SHEEP,JSON.stringify(['COW','SHEEP']));targets={...own};}else{const total=own.COW+own.SHEEP,c=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:0});if(total<16&&c.choice)targets[c.choice]+=Math.min(2,16-total);setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP')));}}\nif([0,1,2,3,6,9,12,18].includes(+obs.day))diary.push({day:+obs.day,cash:obs.farms[pid].money,own:{...own},targets:{...targets},commitmentDone,shops:[...(obs.town?.unlocked_shops??[])]});}\ntry{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors,diary};}\nconst games:any[]=[];for(const v of variants)for(const seed of seeds){games.push(await play(v,seed,0));games.push(await play(v,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,bySeed:Object.fromEntries(seeds.map(seed=>{const x=rs.filter(r=>r.seed===seed);return[seed,{wins:x.filter(r=>r.win).length,avgMargin:x.reduce((a,r)=>a+r.margin,0)/x.length,avgBank:x.reduce((a,r)=>a+r.ours,0)/x.length}]}))};}const b=games.filter(g=>g.v==='BASE');const paired=variants.slice(1).map(v=>{const 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variant_id TEXT NOT NULL,\n opponent_variant_id TEXT,\n environment TEXT NOT NULL,\n seed_set TEXT,\n seat_mode TEXT,\n episodes INTEGER NOT NULL DEFAULT 0,\n wins INTEGER NOT NULL DEFAULT 0,\n losses INTEGER NOT NULL DEFAULT 0,\n ties INTEGER NOT NULL DEFAULT 0,\n mean_terminal_bank REAL,\n median_terminal_bank REAL,\n movement_rate REAL,\n pass_rate REAL,\n runtime_errors INTEGER NOT NULL DEFAULT 0,\n evidence_state TEXT NOT NULL,\n evidence_json TEXT,\n created_at TEXT NOT NULL,\n FOREIGN KEY(variant_id) REFERENCES strategy_variants(variant_id)\n )` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_strategy_variants_agent ON strategy_variants(agent_id,generation,status)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_variant_evals_variant ON variant_evaluations(variant_id,created_at)` },\n { sql: `INSERT INTO schema_meta(key,value,updated_at) VALUES('strategy_variant_schema_version','0.6.1-candidate',?)\n ON CONFLICT(key) DO UPDATE SET value=excluded.value,updated_at=excluded.updated_at`, args:[now] },\n]);\n\nconst variants = [\n ['K0','A4-KAGGRICULTURE',null,0,'Deterministic Control','A compact deterministic executor provides a stable regression oracle and baseline','baseline_control','DESIGNED','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n ['K1','A4-KAGGRICULTURE','K0',1,'Labor/Route Optimizer','Reducing walking/thrashing produces larger gains than more complex crop valuation','route_executor','DESIGNED','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n ['K2','A4-KAGGRICULTURE','K1',2,'Livestock/Fertilizer Flywheel','Jointly valuing animal product plus fertilizer stream improves asset ROI','livestock_fertilizer','DESIGNED','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n ['K3','A4-KAGGRICULTURE','K1',2,'Opponent-Aware Anti-Glut','Visible opponent production can predict shared-market glut early enough to alter profitable production/sale timing','opponent_forecast','DESIGNED','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n ['K4','A4-KAGGRICULTURE','K1',2,'Demand/Horizon Portfolio','Explicit remaining-horizon NPV and observed town demand improve allocation and liquidation','horizon_npv','DESIGNED','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n ['K5','A4-KAGGRICULTURE','K1',3,'Hybrid Champion Candidate','Only mechanisms that independently survive ablation should be fused into a challenger','evidence_gated_fusion','BLOCKED_BY_EVIDENCE','UNVERIFIED','artifacts/kaggriculture_neuron_protocol_v1.md'],\n] as const;\n\nfor (const [id,agent,parent,generation,name,hypothesis,mutation,status,evidence,artifact] of variants) {\n await sqlite.execute({\n sql:`INSERT INTO strategy_variants(variant_id,agent_id,parent_variant_id,generation,name,hypothesis,mutation,status,evidence_state,artifact_pointer,created_at,updated_at)\n VALUES(?,?,?,?,?,?,?,?,?,?,?,?)\n ON CONFLICT(variant_id) DO UPDATE SET name=excluded.name,hypothesis=excluded.hypothesis,mutation=excluded.mutation,status=excluded.status,evidence_state=excluded.evidence_state,artifact_pointer=excluded.artifact_pointer,updated_at=excluded.updated_at`,\n args:[id,agent,parent,generation,name,hypothesis,mutation,status,evidence,artifact,now,now]\n });\n}\n\nconst rows = await sqlite.execute(`SELECT variant_id,parent_variant_id,generation,name,status,evidence_state FROM strategy_variants WHERE agent_id='A4-KAGGRICULTURE' ORDER BY generation,variant_id`);\nconsole.log(JSON.stringify({status:'PASS',version:'0.6.1-candidate',variants:rows.rows},null,2));\n",[219],"d17e92c8-0409-47b8-9ab8-94a9e01ee097","status.ts","01a077bc-2b99-740d-9881-6727e0b68381",["D",1788715215771],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { providerState } from \"./providers/router.ts\";\nimport { getProviderHealth } from \"./lib/provider_health.ts\";\nimport { POLICY } from \"./lib/policy.ts\";\nimport { COST_NOTES } from \"./lib/cost.ts\";\n\nconst schema = await sqlite.execute(\"SELECT key,value,updated_at FROM schema_meta ORDER BY key\");\nconst counts = await sqlite.execute(\"SELECT status, COUNT(*) AS count FROM browser_tasks GROUP BY status ORDER BY status\");\nconst census = await sqlite.execute(\"SELECT provider, priority, state, recurring_free, notes, updated_at FROM provider_census ORDER BY priority\");\nconst recent = await sqlite.execute(\"SELECT run_id,status,provider,attempt_count,error,updated_at FROM browser_tasks ORDER BY id DESC LIMIT 10\");\nconst attemptMetrics = await sqlite.execute(`\n SELECT provider,status,COUNT(*) AS attempts,\n CAST(AVG(duration_ms) AS INTEGER) AS avg_duration_ms,\n COALESCE(SUM(estimated_units),0) AS estimated_units\n FROM browser_attempts\n GROUP BY provider,status\n ORDER BY provider,status\n`);\n\nconst result = {\n service: \"chat-native-maestro\",\n version: POLICY.version,\n status: \"ready\",\n authenticatedDiagnostic: true,\n schema: schema.rows,\n providers: providerState(),\n providerHealth: await getProviderHealth(),\n taskCounts: counts.rows,\n providerCensus: census.rows,\n attemptMetrics: attemptMetrics.rows,\n recentReceipts: recent.rows,\n policy: POLICY,\n costNotes: COST_NOTES,\n environmentRequirements: {\n kernel: \"KERNEL_API_KEY\",\n browserless: \"BROWSERLESS_TOKEN\",\n },\n networkPreflight: {\n dnsOverHttps: \"cloudflare-dns.com\",\n failClosed: true,\n blocksPrivateAndReservedIpRanges: true,\n blocksUrlUserinfo: true,\n blocksNonstandardPorts: true,\n },\n automaticSchedule: \"disabled\",\n timestamp: new Date().toISOString(),\n};\n\nconsole.log(JSON.stringify(result, null, 2));\n",[226],"abd98a94-ae35-4165-976e-a3c5acbfba2b","stateful_selftest.ts","01a077bc-2b99-740d-9881-604153bba708",["D",1788715215771],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { decideDisposition, withTimeout } from \"./lib/policy.ts\";\nimport { providerAvailable, recordProviderOutcome } from \"./lib/provider_health.ts\";\nimport type { BrowserReceipt } from \"./lib/types.ts\";\n\nconst now = new Date().toISOString();\nconst syntheticFail = (n: number): BrowserReceipt => ({\n runId: `circuit-selftest-${n}`,\n provider: \"kernel\",\n status: \"FAIL\",\n error: `synthetic failure ${n}`,\n durationMs: 1,\n});\n\nlet timeoutBlocked = false;\ntry {\n await withTimeout(new Promise((resolve) => setTimeout(resolve, 50)), 5, \"synthetic timeout\");\n} catch (error) {\n timeoutBlocked = String(error).includes(\"timed out\");\n}\n\nconst dispositions = {\n readOnlyFirstFail: decideDisposition(\"read_only\", \"FAIL\", 1),\n readOnlyBudgetExhausted: decideDisposition(\"read_only\", \"FAIL\", 2),\n writeFail: decideDisposition(\"consequential\", \"FAIL\", 1),\n};\n\nlet circuitAfterThree: unknown;\nlet availableAfterThree: unknown;\ntry {\n await sqlite.execute({\n sql: `UPDATE provider_health SET circuit_state='CLOSED', consecutive_failures=0, open_until=NULL,\n last_success_at=NULL,last_failure_at=NULL,last_error=NULL,updated_at=? WHERE provider='kernel'`,\n args: [now],\n });\n await recordProviderOutcome(\"kernel\", syntheticFail(1));\n await recordProviderOutcome(\"kernel\", syntheticFail(2));\n await recordProviderOutcome(\"kernel\", syntheticFail(3));\n circuitAfterThree = (await sqlite.execute(\"SELECT provider,circuit_state,consecutive_failures,open_until FROM provider_health WHERE provider='kernel'\")).rows[0];\n availableAfterThree = await providerAvailable(\"kernel\");\n} finally {\n await sqlite.execute({\n sql: `UPDATE provider_health SET circuit_state='CLOSED', consecutive_failures=0, open_until=NULL,\n last_success_at=NULL,last_failure_at=NULL,last_error=NULL,updated_at=? WHERE provider='kernel'`,\n args: [new Date().toISOString()],\n });\n}\n\nconsole.log(JSON.stringify({\n version: \"0.5.0\",\n timeoutBlocked,\n dispositions,\n circuitAfterThree,\n availableAfterThree,\n restoredKernelHealth: (await sqlite.execute(\"SELECT provider,circuit_state,consecutive_failures,open_until FROM provider_health WHERE provider='kernel'\")).rows[0],\n}, null, 2));\n",[232],"73e9e358-f044-43f3-8b0c-ee8e3f20e4f8","snapshot_export.ts","01a077bc-2b99-740d-9881-5e611370bab8",["D",1788715215771],"import JSZip from \"npm:jszip\";\nimport { blob } from \"https://esm.town/v/std/blob/main.ts\";\n\nconst release = \"65-main\";\nconst paths = [\n \"main.ts\",\n \"status.ts\",\n \"runner.ts\",\n \"selftest.ts\",\n \"stateful_selftest.ts\",\n \"url_selftest.ts\",\n \"README.md\",\n \"lib/types.ts\",\n \"lib/dsl.ts\",\n \"lib/policy.ts\",\n \"lib/provider_health.ts\",\n \"lib/cost.ts\",\n \"lib/url_security.ts\",\n \"providers/router.ts\",\n \"providers/kernel.ts\",\n \"providers/browserless.ts\",\n \"docs/CURRENT_STATE.md\",\n \"docs/PROVIDER_CENSUS.md\",\n \"docs/ACTIVATION_RUNBOOK.md\",\n \"docs/TASK_SCHEMA.md\",\n \"docs/SMOKE_TASK.json\",\n \"docs/SECURITY_MODEL.md\",\n];\n\nconst zip = new JSZip();\nconst manifest: Array<{ path: string; bytes: number; sha256: string; sourceUrl: string }> = [];\nconst enc = new TextEncoder();\nconst hex = (bytes: ArrayBuffer) => [...new Uint8Array(bytes)].map((x) => x.toString(16).padStart(2, \"0\")).join(\"\");\n\nfor (const path of paths) {\n const sourceUrl = `https://esm.town/v/cleitoncosta/chat-native-maestro@${release}/${path}`;\n const response = await fetch(sourceUrl, { signal: AbortSignal.timeout(10_000) });\n if (!response.ok) throw new Error(`${path}: HTTP ${response.status}`);\n let text = await response.text();\n if (path.endsWith(\".ts\") || path.endsWith(\".tsx\")) {\n text = text.replace(/^\\/\\* Open in Val Town: [^\\n]+ \\*\\/\\n/, \"\");\n }\n const bytes = enc.encode(text);\n const sha256 = hex(await crypto.subtle.digest(\"SHA-256\", bytes));\n manifest.push({ path, bytes: bytes.byteLength, sha256, sourceUrl });\n zip.file(path, text);\n}\n\nconst metadata = {\n name: \"CHATGPT_CHAT_NATIVE_MAESTRO_V0_5_0_CLOUD_SNAPSHOT\",\n sourceVal: \"cleitoncosta/chat-native-maestro\",\n sourceBranchRelease: release,\n appVersion: \"0.5.0\",\n exportedAt: new Date().toISOString(),\n fileCount: paths.length,\n credentialsIncluded: false,\n databaseContentsIncluded: false,\n note: \"Source files fetched from immutable esm.town release URLs; esm.town TypeScript display header removed before packaging.\",\n};\nzip.file(\"LIVE_EXPORT_METADATA.json\", JSON.stringify(metadata, null, 2));\nzip.file(\"SOURCE_MANIFEST.json\", JSON.stringify(manifest, null, 2));\nconst base64 = await zip.generateAsync({ type: \"base64\", compression: \"DEFLATE\", compressionOptions: { level: 9 } });\nconst blobKey = \"release:v0.5.0:source.zip.b64\";\nawait blob.set(blobKey, base64);\nconst base64Sha256 = hex(await crypto.subtle.digest(\"SHA-256\", enc.encode(base64)));\nconsole.log(JSON.stringify({ metadata, manifest, blobKey, base64Length: base64.length, base64Sha256 }));\n",[238],"53ccefb1-9a83-4be5-a76f-668e29910d84","selftest.ts","01a077bc-2b99-740d-9881-5a19ff4d14c8",["D",1788715215771],"import { validateTask } from \"./lib/dsl.ts\";\nimport { providerState } from \"./providers/router.ts\";\nimport { POLICY } from \"./lib/policy.ts\";\nimport { getProviderHealth } from \"./lib/provider_health.ts\";\n\nconst validRead = {\n runId: \"selftest-read-v05\",\n targetUrl: \"https://example.com\",\n risk: \"read_only\" as const,\n purpose: \"Validate V0.5 DSL without opening a browser\",\n evidenceRetention: \"minimal\" as const,\n steps: [{ action: \"expect_text\" as const, text: \"Example Domain\" }],\n};\n\nconst blockedWrite = {\n runId: \"selftest-write-v05\",\n targetUrl: \"https://example.com\",\n risk: \"consequential\" as const,\n approved: false,\n purpose: \"Negative control for approval gate\",\n steps: [{ action: \"click\" as const, selector: \"button\" }],\n};\n\nconst blockedSecret = {\n runId: \"selftest-secret-v05\",\n targetUrl: \"https://example.com\",\n risk: \"read_only\" as const,\n approved: false,\n purpose: \"Negative control for secret resolution gate\",\n steps: [{ action: \"fill_secret\" as const, selector: \"#password\", envVar: \"EXAMPLE_PASSWORD\" }],\n};\n\nconst invalidProvider = {\n ...validRead,\n runId: \"selftest-provider-v05\",\n preferredProvider: \"imaginary-provider\" as any,\n};\n\nconst blockedValueExtraction = {\n ...validRead,\n runId: \"selftest-value-v05\",\n steps: [{ action: \"extract_attribute\" as const, selector: \"#password\", attribute: \"value\", key: \"password\" }],\n};\n\nconst result = {\n version: POLICY.version,\n validReadErrors: validateTask(validRead),\n blockedWriteErrors: validateTask(blockedWrite),\n blockedSecretErrors: validateTask(blockedSecret),\n invalidProviderErrors: validateTask(invalidProvider),\n blockedValueExtractionErrors: validateTask(blockedValueExtraction),\n providers: providerState(),\n providerHealth: await getProviderHealth(),\n policy: POLICY,\n expected: {\n validReadErrors: [],\n blockedWriteContains: \"NEEDS_APPROVAL\",\n blockedSecretContains: \"NEEDS_SECRET_APPROVAL\",\n invalidProviderContains: \"invalid preferredProvider\",\n valueExtractionBlocked: true,\n providersConfigured: false,\n },\n};\n\nconsole.log(JSON.stringify(result, null, 2));\n",[244],"4c29f586-3db0-4d31-84e4-90a8a3bc8396","selection_engine.ts","ef689386-aa18-11f1-8b71-1607ee4eb77e",11,["D",1788715949727],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { rankGeneration, offspringPlan, type SelectionCandidate, type SelectionResult } from \"./lib/neuron_evolution.ts\";\n\nconst now = new Date().toISOString();\n\nconst agents = await sqlite.execute(`\n SELECT a.agent_id,a.generation,\n COALESCE(SUM(t.gross_revenue),0) AS gross,\n COALESCE(SUM(t.browser_cost+t.llm_cost+t.api_cost+t.hosting_cost+t.platform_fee+t.transaction_cost),0) AS cost,\n COALESCE(SUM(t.net_revenue),0) AS net,\n COALESCE(SUM(CASE WHEN t.operationally_eligible=1 AND t.terminal=1 THEN 1 ELSE 0 END),0) AS terminal_trials,\n COALESCE(SUM(CASE WHEN t.operationally_eligible=1 AND t.terminal=1 AND t.net_revenue>0 THEN 1 ELSE 0 END),0) AS successful_trials,\n COALESCE(SUM(CASE WHEN t.operationally_eligible=1 AND t.terminal=1 AND t.net_revenue<=0 THEN 1 ELSE 0 END),0) AS failed_trials,\n COALESCE(SUM(CASE WHEN t.operationally_eligible=1 AND t.terminal=0 THEN 1 ELSE 0 END),0) AS active_eligible_trials\n FROM economic_agents a\n LEFT JOIN economic_trials t ON t.agent_id=a.agent_id\n GROUP BY a.agent_id,a.generation\n ORDER BY a.generation,a.agent_id\n`);\n\ntype Row = Record;\ntype Derived = { row: Row; candidate: SelectionCandidate };\nconst derived: Derived[] = agents.rows.map((row: Row) => {\n const terminalTrials = Number(row.terminal_trials ?? 0);\n const activeEligibleTrials = Number(row.active_eligible_trials ?? 0);\n return {\n row,\n candidate: {\n agentId: String(row.agent_id),\n netRevenue: Number(row.net ?? 0),\n operationallyEligible: terminalTrials > 0,\n terminal: terminalTrials > 0 && activeEligibleTrials === 0,\n },\n };\n});\n\nconst results = new Map();\nconst generations = [...new Set(derived.map((x) => Number(x.row.generation)))].sort((a,b)=>a-b);\nfor (const generation of generations) {\n const group = derived.filter((x) => Number(x.row.generation) === generation);\n for (const result of rankGeneration(group.map((x) => x.candidate))) results.set(result.agentId, result);\n}\n\nconst statements: Array<{sql:string;args:Array}> = [];\nconst plans: Array> = [];\nfor (const item of derived) {\n const result = results.get(item.candidate.agentId)!;\n const gross = Number(item.row.gross ?? 0);\n const cost = Number(item.row.cost ?? 0);\n const terminalTrials = Number(item.row.terminal_trials ?? 0);\n const successfulTrials = Number(item.row.successful_trials ?? 0);\n const failedTrials = Number(item.row.failed_trials ?? 0);\n statements.push({\n sql: `INSERT INTO agent_fitness(agent_id,selection_state,lifetime_gross,lifetime_cost,lifetime_net,benchmark_net,terminal_trials,successful_trials,failed_trials,rank,offspring_count,updated_at)\n VALUES(?,?,?,?,?,?,?,?,?,?,?,?)\n ON CONFLICT(agent_id) DO UPDATE SET\n selection_state=excluded.selection_state,\n lifetime_gross=excluded.lifetime_gross,\n lifetime_cost=excluded.lifetime_cost,\n lifetime_net=excluded.lifetime_net,\n benchmark_net=CASE WHEN excluded.lifetime_net>agent_fitness.benchmark_net THEN excluded.lifetime_net ELSE agent_fitness.benchmark_net END,\n terminal_trials=excluded.terminal_trials,\n successful_trials=excluded.successful_trials,\n failed_trials=excluded.failed_trials,\n rank=excluded.rank,\n offspring_count=excluded.offspring_count,\n updated_at=excluded.updated_at`,\n args: [result.agentId,result.state,gross,cost,result.netRevenue,Math.max(0,result.benchmark),terminalTrials,successfulTrials,failedTrials,result.rank ?? null,result.offspringCount,now],\n });\n if (result.state === \"DEAD\" || result.state === \"SURVIVOR\") {\n statements.push({\n sql: `UPDATE economic_agents SET status=?,updated_at=? WHERE agent_id=?`,\n args: [result.state,now,result.agentId],\n });\n }\n for (const plan of offspringPlan(result)) plans.push({ generation: Number(item.row.generation), ...plan });\n}\n\nif (statements.length) await sqlite.batch(statements);\nconst fitness = await sqlite.execute(`SELECT agent_id,selection_state,lifetime_gross,lifetime_cost,lifetime_net,benchmark_net,terminal_trials,successful_trials,failed_trials,rank,offspring_count FROM agent_fitness ORDER BY agent_id`);\n\nconsole.log(JSON.stringify({ status: \"PASS\", evaluated: derived.length, fitness: fitness.rows, offspringPlans: plans, timestamp: now }, null, 2));\n",[250],"78c1b1fd-24a3-47f8-83ee-334894178982","runner.ts","01a077bc-2b99-740d-9881-57dc4656df82",["D",1788715215771],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport type { BrowserReceipt, BrowserTask } from \"./lib/types.ts\";\nimport { validateTask } from \"./lib/dsl.ts\";\nimport { executeRouted } from \"./providers/router.ts\";\nimport { decideDisposition, POLICY } from \"./lib/policy.ts\";\nimport { estimateProviderUnits } from \"./lib/cost.ts\";\nimport { preflightTaskNetwork } from \"./lib/url_security.ts\";\n\nasync function recoverStaleLeases() {\n const staleBefore = new Date(Date.now() - POLICY.runningLeaseMs).toISOString();\n const now = new Date().toISOString();\n await sqlite.batch([\n {\n sql: `UPDATE browser_tasks SET status='FAIL', claimed_at=NULL, next_attempt_at=NULL,\n error='stale running lease; retry budget exhausted', updated_at=?\n WHERE status='RUNNING' AND claimed_at IS NOT NULL AND claimed_at=?`,\n args: [now, staleBefore, POLICY.maxAttemptsPerTask],\n },\n {\n sql: `UPDATE browser_tasks SET status='PENDING', claimed_at=NULL, next_attempt_at=?,\n error='stale running lease recovered', updated_at=?\n WHERE status='RUNNING' AND claimed_at IS NOT NULL AND claimed_at | undefined;\n}\n\nfunction storageReceipt(receipt: BrowserReceipt, task: BrowserTask) {\n if (task.evidenceRetention === \"full\") return receipt;\n const meta = receipt.providerMeta ?? {};\n return {\n runId: receipt.runId,\n provider: receipt.provider,\n status: receipt.status,\n finalUrl: receipt.finalUrl,\n checks: receipt.checks ?? [],\n error: receipt.error,\n durationMs: receipt.durationMs,\n providerMeta: {\n fallbackFrom: meta.fallbackFrom,\n priorStatus: meta.priorStatus,\n priorError: meta.priorError,\n priorDurationMs: meta.priorDurationMs,\n networkPreflight: meta.networkPreflight,\n },\n outputsPersisted: false,\n };\n}\n\nasync function recordAttempts(taskId: number, attemptNo: number, startedAt: string, receipt: BrowserReceipt, storedReceipt: unknown) {\n const finishedAt = new Date().toISOString();\n const meta = receipt.providerMeta ?? {};\n const statements: Array<{ sql: string; args: Array }> = [];\n\n if (typeof meta.fallbackFrom === \"string\") {\n statements.push({\n sql: `INSERT INTO browser_attempts(task_id,run_id,attempt_no,provider,started_at,finished_at,status,duration_ms,error,receipt_json,estimated_units)\n VALUES(?,?,?,?,?,?,?,?,?,?,?)`,\n args: [taskId, receipt.runId, attemptNo, meta.fallbackFrom, startedAt, finishedAt,\n String(meta.priorStatus ?? \"FAIL\"), Number(meta.priorDurationMs ?? 0),\n meta.priorError == null ? null : String(meta.priorError), null, null],\n });\n }\n\n statements.push({\n sql: `INSERT INTO browser_attempts(task_id,run_id,attempt_no,provider,started_at,finished_at,status,duration_ms,error,receipt_json,estimated_units)\n VALUES(?,?,?,?,?,?,?,?,?,?,?)`,\n args: [taskId, receipt.runId, attemptNo, receipt.provider, startedAt, finishedAt,\n receipt.status, receipt.durationMs ?? null, receipt.error ?? null, JSON.stringify(storedReceipt), estimateProviderUnits(receipt)],\n });\n await sqlite.batch(statements);\n}\n\nasync function finishTask(row: Record, task: BrowserTask, receipt: BrowserReceipt, storedReceipt: unknown) {\n const id = Number(row.id);\n const attemptCount = Number(row.attempt_count);\n const now = new Date().toISOString();\n const disposition = decideDisposition(task.risk, receipt.status, attemptCount);\n const next = disposition.retryable ? new Date(Date.now() + disposition.retryDelayMs).toISOString() : null;\n await sqlite.execute({\n sql: `UPDATE browser_tasks SET status=?, provider=?, receipt_json=?, error=?, updated_at=?, claimed_at=NULL, next_attempt_at=? WHERE id=?`,\n args: [disposition.taskStatus, receipt.provider, JSON.stringify(storedReceipt), receipt.error ?? null, now, next, id],\n });\n}\n\nasync function blockTask(row: Record, task: BrowserTask | undefined, errors: string[]) {\n const id = Number(row.id);\n const receipt = { runId: task?.runId ?? String(row.run_id), status: \"BLOCKED\", errors };\n const now = new Date().toISOString();\n await sqlite.batch([\n {\n sql: `UPDATE browser_tasks SET status='BLOCKED', provider=?, receipt_json=?, error=?, updated_at=?, claimed_at=NULL, next_attempt_at=NULL WHERE id=?`,\n args: [task?.preferredProvider ?? \"validation\", JSON.stringify(receipt), errors.join(\"; \"), now, id],\n },\n {\n sql: `INSERT INTO browser_attempts(task_id,run_id,attempt_no,provider,started_at,finished_at,status,error,receipt_json,estimated_units)\n VALUES(?,?,?,?,?,?,?,?,?,?)`,\n args: [id, String(row.run_id), Number(row.attempt_count), task?.preferredProvider ?? \"validation\",\n String(row.claimed_at ?? now), now, \"BLOCKED\", errors.join(\"; \"), JSON.stringify(receipt), null],\n },\n ]);\n console.log(JSON.stringify(receipt, null, 2));\n return receipt;\n}\n\nasync function main() {\n await recoverStaleLeases();\n const row = await claimNext();\n if (!row) {\n const result = { status: \"NO_PENDING_TASK\" };\n console.log(JSON.stringify(result));\n return result;\n }\n\n let task: BrowserTask;\n try {\n task = JSON.parse(String(row.task_json)) as BrowserTask;\n } catch (error) {\n return blockTask(row, undefined, [`invalid task_json: ${error instanceof Error ? error.message : String(error)}`]);\n }\n\n const errors = validateTask(task);\n if (errors.length) return blockTask(row, task, errors);\n\n let networkPreflight: Array<{ host: string; ips: string[] }>;\n try {\n networkPreflight = await preflightTaskNetwork(task);\n } catch (error) {\n return blockTask(row, task, [`NETWORK_PREFLIGHT_BLOCKED: ${error instanceof Error ? error.message : String(error)}`]);\n }\n\n const receipt = await executeRouted(task);\n receipt.providerMeta = { ...(receipt.providerMeta ?? {}), networkPreflight };\n const storedReceipt = storageReceipt(receipt, task);\n await recordAttempts(Number(row.id), Number(row.attempt_count), String(row.claimed_at), receipt, storedReceipt);\n await finishTask(row, task, receipt, storedReceipt);\n\n console.log(JSON.stringify(receipt, null, 2));\n return receipt;\n}\n\nawait main();\n",[257],"783bd826-874b-4a95-bcdc-c472e8ab076c","python_runtime_probe.ts","d0f3b032-aa38-11f1-bbfa-1607ee4eb77e",32,["D",1788729642559],"const cmds=['python3','python'];const out=[];for(const c of cmds){try{const p=new Deno.Command(c,{args:['--version'],stdout:'piped',stderr:'piped'});const r=await p.output();out.push({cmd:c,code:r.code,stdout:new TextDecoder().decode(r.stdout),stderr:new TextDecoder().decode(r.stderr)});}catch(e){out.push({cmd:c,error:String(e)});}}console.log(JSON.stringify({status:out.some((x:any)=>x.code===0)?'PASS':'BLOCKED',out},null,2));",[263],"07672df5-5413-4182-b0d5-2b32beaa0081","pyodide_probe.ts","3a9f848e-aa39-11f1-8b0c-1607ee4eb77e",40,["D",1788729833259],"try {\n const mod = await import(\"npm:pyodide\");\n const py = await mod.loadPyodide();\n const result = py.runPython(\"sum(i*i for i in range(10))\");\n console.log(JSON.stringify({status:\"PASS\",version:mod.version,result},null,2));\n} catch (e) {\n console.log(JSON.stringify({status:\"BLOCKED\",error:String(e)},null,2));\n}",[270],"d3478695-ab23-4ced-ba33-45fb9cac7566","neuron_selftest.ts","b37a05da-aa18-11f1-a8c4-1607ee4eb77e",9,["D",1788715849210],"import { classifyCandidate, rankGeneration, offspringPlan, MUTATION_ARCHETYPES } from \"./lib/neuron_evolution.ts\";\n\nconst incubation = classifyCandidate({ agentId: \"INC\", netRevenue: 0, operationallyEligible: false, terminal: false });\nconst running = classifyCandidate({ agentId: \"RUN\", netRevenue: 100, operationallyEligible: true, terminal: false });\nconst zero = classifyCandidate({ agentId: \"ZERO\", netRevenue: 0, operationallyEligible: true, terminal: true });\nconst loss = classifyCandidate({ agentId: \"LOSS\", netRevenue: -0.01, operationallyEligible: true, terminal: true });\nconst win = classifyCandidate({ agentId: \"WIN\", netRevenue: 12.5, operationallyEligible: true, terminal: true });\n\nconst ranked = rankGeneration([\n { agentId: \"A\", netRevenue: 100, operationallyEligible: true, terminal: true },\n { agentId: \"B\", netRevenue: 80, operationallyEligible: true, terminal: true },\n { agentId: \"C\", netRevenue: 50, operationallyEligible: true, terminal: true },\n { agentId: \"D\", netRevenue: 10, operationallyEligible: true, terminal: true },\n { agentId: \"E\", netRevenue: 1, operationallyEligible: true, terminal: true },\n { agentId: \"Z\", netRevenue: 0, operationallyEligible: true, terminal: true },\n]);\n\nconst byId = new Map(ranked.map((x) => [x.agentId, x]));\nconst topPlan = offspringPlan(byId.get(\"A\")!);\nconst deadPlan = offspringPlan(byId.get(\"Z\")!);\n\nconst checks = [\n { name: \"incubation is not killed\", pass: incubation.state === \"INCUBATION\" && incubation.offspringCount === 0 },\n { name: \"nonterminal profit is still incubation\", pass: running.state === \"INCUBATION\" && running.offspringCount === 0 },\n { name: \"terminal zero dies\", pass: zero.state === \"DEAD\" && zero.offspringCount === 0 },\n { name: \"terminal loss dies\", pass: loss.state === \"DEAD\" && loss.offspringCount === 0 },\n { name: \"positive terminal survives\", pass: win.state === \"SURVIVOR\" && win.benchmark === 12.5 },\n { name: \"highest net ranks first\", pass: byId.get(\"A\")?.rank === 1 },\n { name: \"top survivor gets more offspring than tail survivor\", pass: (byId.get(\"A\")?.offspringCount ?? 0) > (byId.get(\"E\")?.offspringCount ?? 0) },\n { name: \"dead candidate never spawns\", pass: deadPlan.length === 0 },\n { name: \"top offspring plan contains faithful replica\", pass: topPlan.some((x) => x.mutation === \"faithful_replica\") },\n { name: \"top offspring plan contains opposite hypothesis\", pass: topPlan.some((x) => x.mutation === \"opposite_hypothesis\") },\n { name: \"top offspring plan contains causal ablation\", pass: topPlan.some((x) => x.mutation === \"causal_ablation\") },\n { name: \"offspring inherit parent revenue benchmark\", pass: topPlan.every((x) => x.targetNetRevenue === 100) },\n { name: \"mutation archetypes remain unique\", pass: new Set(MUTATION_ARCHETYPES).size === MUTATION_ARCHETYPES.length },\n];\n\nconst failed = checks.filter((x) => !x.pass);\nconsole.log(JSON.stringify({\n status: failed.length ? \"FAIL\" : \"PASS\",\n checks,\n failed,\n samples: { incubation, running, zero, loss, win },\n ranked,\n topPlan,\n deadPlan,\n}, null, 2));\n\nif (failed.length) throw new Error(`neuron_selftest failed: ${failed.map((x) => x.name).join(\", \")}`);\n",[277],"0b8a62cc-6643-43ee-836c-80ffdb940f3c","main.ts","01a077bc-2b99-740d-9881-5062f5c9e3f1",["D",1788715215771],"http","export default async function (req: Request): Promise {\n if (req.method !== \"GET\") {\n return Response.json({ error: \"method_not_allowed\" }, { status: 405 });\n }\n\n return Response.json({\n service: \"chat-native-maestro\",\n version: \"0.5.0\",\n status: \"alive\",\n executionSurface: \"authenticated_val_town_plugin_only\",\n automaticExecution: \"disabled\",\n security: {\n publicEndpointWriteMethods: \"disabled\",\n detailedRuntimeState: \"not_exposed_publicly\",\n arbitraryCodeInput: \"disabled\",\n },\n });\n}\n",[284],"faee7910-7236-4be9-a865-f28cdd5603f0","kaggriculture_shop_world_census_v1.ts","7f4d5b02-aa38-11f1-82cf-1607ee4eb77e",31,["D",1788729505529],"import { loadOfficialKaggricultureEngine } from \"./lib/kaggriculture_engine_loader.ts\";\nconst E=await loadOfficialKaggricultureEngine();\nconst N=500;\nconst PASS={farmer:[\"PASS\"],hands:[],market:[]};\nconst products=[\"CARROT\",\"TOMATO\",\"EGG\"];\nconst rows:any[]=[];\nfor(let seed=1;seed<=N;seed++){\n const cfg=E.state.resolveConfig({seed}); let s=E.state.initGameState(2,cfg,seed);\n while(!s.done)s=E.interpreter.step(s,[PASS,PASS],cfg);\n const counts:any={};for(const sh of s.town.unlocked_shops)counts[sh]=(counts[sh]??0)+1;\n const rec:any={seed,shops:[...s.town.unlocked_shops],counts};\n for(const p of products){rec[p]={consumed:10000-s.market.inventory[p],inventory:s.market.inventory[p],price:s.market.prices[p]};}\n rows.push(rec);\n}\nconst quant=(xs:number[],q:number)=>{const a=[...xs].sort((x,y)=>x-y);const i=(a.length-1)*q,lo=Math.floor(i),hi=Math.ceil(i);return lo===hi?a[lo]:a[lo]+(a[hi]-a[lo])*(i-lo);};\nconst summary:any={};\nfor(const p of products){const cons=rows.map(r=>r[p].consumed),price=rows.map(r=>r[p].price);summary[p]={consumed:{min:Math.min(...cons),p10:quant(cons,.1),p25:quant(cons,.25),median:quant(cons,.5),p75:quant(cons,.75),p90:quant(cons,.9),p95:quant(cons,.95),max:Math.max(...cons)},price:{min:Math.min(...price),p50:quant(price,.5),p75:quant(price,.75),p90:quant(price,.9),p95:quant(price,.95),max:Math.max(...price)},gt100:price.filter(x=>x>100).length/N,gt200:price.filter(x=>x>200).length/N,gt500:price.filter(x=>x>500).length/N};}\nconst petHist:any={},fmHist:any={},pizzaHist:any={},eggShopHist:any={};\nfor(const r of rows){const pet=r.counts.PET_CAFE??0,fm=r.counts.FARMERS_MARKET??0,pizza=r.counts.PIZZA_SHOP??0,egg=(r.counts.BAKERY??0)+(r.counts.BRUNCH_SPOT??0);petHist[pet]=(petHist[pet]??0)+1;fmHist[fm]=(fmHist[fm]??0)+1;pizzaHist[pizza]=(pizzaHist[pizza]??0)+1;eggShopHist[egg]=(eggShopHist[egg]??0)+1;}\nconst extremes=(p:string)=>[...rows].sort((a,b)=>b[p].price-a[p].price).slice(0,10).map(r=>({seed:r.seed,price:r[p].price,consumed:r[p].consumed,counts:r.counts,shops:r.shops}));\nconsole.log(JSON.stringify({status:\"PASS\",evidenceState:\"OFFICIAL_TS_PORT_STATISTICAL_SHOP_CENSUS\",N,summary,histograms:{PET_CAFE:petHist,FARMERS_MARKET:fmHist,PIZZA_SHOP:pizzaHist,EGG_DEMAND_SHOPS:eggShopHist},extremes:{CARROT:extremes(\"CARROT\"),TOMATO:extremes(\"TOMATO\"),EGG:extremes(\"EGG\")},caveat:\"TS port RNG is not bit-identical to CPython; this census is for distributional mechanism discovery, not exact seed replay parity.\"},null,2));",[291],"413c051e-d17e-4504-9004-92671c8dc075","kaggriculture_seed9403_econ_diagnostic.ts","35ed3a24-aa40-11f1-9086-1607ee4eb77e",55,["D",1788732818434],"import { loadOfficialKaggricultureEngine } from './lib/kaggriculture_engine_loader.ts';\nconst E=await loadOfficialKaggricultureEngine();\nconst seed=9403; const cfg=E.state.resolveConfig({seed}); let s=E.state.initGameState(2,cfg,seed);\nconst PASS={farmer:['PASS'],hands:[],market:[]};\nconst history:any[]=[]; let prev=[] as string[];\nwhile(!s.done){\n const shops=[...s.town.unlocked_shops];\n if(JSON.stringify(shops)!==JSON.stringify(prev)){\n history.push({day:s.day,hour:s.hour,shops:[...shops],prices:{MILK:s.market.prices.MILK,WOOL:s.market.prices.WOOL,WHEAT:s.market.prices.WHEAT},inventory:{MILK:s.market.inventory.MILK,WOOL:s.market.inventory.WOOL,WHEAT:s.market.inventory.WHEAT}});\n prev=shops;\n }\n s=E.interpreter.step(s,[PASS,PASS],cfg);\n}\nconst items=['MILK','WOOL','WHEAT','CARROT','TOMATO']; const final:any={};\nfor(const p of items) final[p]={consumed:10000-s.market.inventory[p],inventory:s.market.inventory[p],price:s.market.prices[p]};\nconst counts:any={}; for(const sh of s.town.unlocked_shops)counts[sh]=(counts[sh]??0)+1;\nconsole.log(JSON.stringify({status:'PASS',seed,counts,history,final},null,2));\n",[298],"83965c46-3128-4450-a50f-b64de2454e02","kaggriculture_route_sweep_v1.ts","c0b9a6d2-aa37-11f1-a849-1607ee4eb77e",24,["D",1788729185837],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, K0, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst E = await loadOfficialKaggricultureEngine();\nconst cfgBase = E.state.resolveConfig();\nconst seeds = [11, 23, 37];\n\nconst variants: Record = {\n K0,\n R1_H1_T5: buildAgent({ crop:\"CARROT\", targetHands:1, maxTiles:5, persistent:true, seedBuffer:8 }),\n R2_H2_T6: buildAgent({ crop:\"CARROT\", targetHands:2, maxTiles:6, persistent:true, seedBuffer:10 }),\n R3_H3_T8: buildAgent({ crop:\"CARROT\", targetHands:3, maxTiles:8, persistent:true, seedBuffer:12 }),\n R4_H4_T10: buildAgent({ crop:\"CARROT\", targetHands:4, maxTiles:10, persistent:true, seedBuffer:15 }),\n R5_H6_T12: buildAgent({ crop:\"CARROT\", targetHands:6, maxTiles:12, persistent:true, seedBuffer:18 }),\n R6_H8_T16: buildAgent({ crop:\"CARROT\", targetHands:8, maxTiles:16, persistent:true, seedBuffer:22 }),\n R7_H10_T25: buildAgent({ crop:\"CARROT\", targetHands:10, maxTiles:25, persistent:true, seedBuffer:30 }),\n R4NP_H4_T10: buildAgent({ crop:\"CARROT\", targetHands:4, maxTiles:10, persistent:false, seedBuffer:15 }),\n};\n\nfunction stat(){return {unit:0,move:0,pass:0,work:0};}\nfunction count(s:any,a:any){for(const u of [a?.farmer??[\"PASS\"],...(a?.hands??[])]){s.unit++;const op=String(u?.[0]??\"PASS\");if([\"NORTH\",\"SOUTH\",\"EAST\",\"WEST\"].includes(op))s.move++;else if(op===\"PASS\")s.pass++;else s.work++;}}\n\nasync function play(a:AgentFn,b:AgentFn,seed:number){\n const cfg={...cfgBase,seed}; let state=E.state.initGameState(2,cfg,seed); const ss=[stat(),stat()];\n while(!state.done){const aa=a(observationFor(state,0)),bb=b(observationFor(state,1));count(ss[0],aa);count(ss[1],bb);state=E.interpreter.step(state,[aa,bb],cfg);}\n return {banks:state.farms.map((f:any)=>Number(f.money)),stats:ss};\n}\n\nconst results:any[]=[];\nfor(const [name,agent] of Object.entries(variants)){\n if(name===\"K0\") continue;\n for(const opponentName of [\"K0\",\"STARTER\"]){\n const opp=opponentName===\"K0\"?K0:STARTER;\n for(const seed of seeds){\n let g=await play(agent,opp,seed); results.push({name,opponentName,seed,seat:0,bank:g.banks[0],oppBank:g.banks[1],won:g.banks[0]>g.banks[1],tied:g.banks[0]===g.banks[1],s:g.stats[0]});\n g=await play(opp,agent,seed); results.push({name,opponentName,seed,seat:1,bank:g.banks[1],oppBank:g.banks[0],won:g.banks[1]>g.banks[0],tied:g.banks[1]===g.banks[0],s:g.stats[1]});\n }\n }\n}\n\nconst avg=(xs:number[])=>xs.reduce((a,b)=>a+b,0)/(xs.length||1);\nconst summary:any[]=[];\nfor(const name of Object.keys(variants).filter(n=>n!==\"K0\")){\n const rows=results.filter(r=>r.name===name);\n const byOpp:any={};\n for(const opp of [\"K0\",\"STARTER\"]){const rr=rows.filter(r=>r.opponentName===opp);byOpp[opp]={episodes:rr.length,wins:rr.filter(r=>r.won).length,ties:rr.filter(r=>r.tied).length,winRate:rr.filter(r=>r.won).length/rr.length,avgBank:avg(rr.map(r=>r.bank)),avgMargin:avg(rr.map(r=>r.bank-r.oppBank))};}\n summary.push({name,episodes:rows.length,wins:rows.filter(r=>r.won).length,winRate:rows.filter(r=>r.won).length/rows.length,avgBank:avg(rows.map(r=>r.bank)),avgMargin:avg(rows.map(r=>r.bank-r.oppBank)),moveRate:avg(rows.map(r=>r.s.move/r.s.unit)),passRate:avg(rows.map(r=>r.s.pass/r.s.unit)),workRate:avg(rows.map(r=>r.s.work/r.s.unit)),byOpp});\n}\nsummary.sort((a,b)=>b.winRate-a.winRate||b.avgMargin-a.avgMargin||b.avgBank-a.avgBank);\nconsole.log(JSON.stringify({status:\"PASS\",evidenceState:\"OFFICIAL_TS_PORT_SCREENING\",seeds,summary},null,2));\n",[305],"2d56ab4e-fb23-46ef-86e9-eba4e80d13d9","kaggriculture_rita_neuron_sweep_v1.ts","a8a8a4d8-aa39-11f1-a2b2-1607ee4eb77e",45,["D",1788730004418],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\n\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zres=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zres.ok)throw new Error(String(zres.status));const z=unzipSync(new Uint8Array(await zres.arrayBuffer()));\nconst ritaSrc=strFromU8(z['rancher_rita.py']),mateoSrc=strFromU8(z['melon_mateo.py']);\nconst variants:Record={\n RITA_BASE:{},\n H6:{hands:6},H10:{hands:10},\n FEED12:{feed_float_days:12},FEED20:{feed_float_days:20},\n C8S8:{animal_target:{COW:8,SHEEP:8}},\n C12S4:{animal_target:{COW:12,SHEEP:4}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n TOTAL12:{animal_target:{COW:8,SHEEP:4},buildTarget:12},\n TOTAL20:{animal_target:{COW:12,SHEEP:8},buildTarget:20},\n CARE_OFF:{care:false},\n LAND1:{land:1},\n};\nconst py=await loadPyodide();\npy.runPython(`import json, copy\\n_REG={}`);\npy.globals.set('rita_src',ritaSrc);py.globals.set('mateo_src',mateoSrc);\npy.runPython(`\n_m={}\\nexec(mateo_src,_m)\\n_REG['MATEO']=_m['agent']\n`);\nfor(const [name,patch] of Object.entries(variants)){\n py.globals.set('nm',name);py.globals.set('patch_json',JSON.stringify(patch));\n py.runPython(`\n_ns={}\\nexec(rita_src,_ns)\\n_p=json.loads(patch_json)\\n_bt=_p.pop('buildTarget',None)\\nfor _k,_v in _p.items(): _ns['POLICY'][_k]=_v\\nif _bt is not None and _ns['POLICY'].get('build'):\\n _ns['POLICY']['build'][0]['target']=_bt\\n_REG[nm]=_ns['agent']\n`);\n}\npy.runPython(`def call_ref(name,payload):\\n return json.dumps(_REG[name](json.loads(payload)))`);const call=py.globals.get('call_ref');\nconst seeds=[8101,8129,8171];\nasync function play(a:string,b:string,seed:number){const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);let errors=0;while(!s.done){const aa=[];for(const [pid,nm] of [[0,a],[1,b]] as any){try{aa[pid]=JSON.parse(String(call(nm,JSON.stringify(observationFor(s,pid)))));}catch(e){errors++;aa[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,aa,cfg);}return {a,b,seed,ba:s.farms[0].money,bb:s.farms[1].money,errors};}\nconst games:any[]=[];for(const name of Object.keys(variants).filter(n=>n!=='RITA_BASE'))for(const opp of ['RITA_BASE','MATEO'])for(const seed of seeds){games.push(await play(name,opp,seed));games.push(await play(opp,name,seed));}\nconst avg=(xs:number[])=>xs.reduce((a,b)=>a+b,0)/(xs.length||1);const summary:any={};for(const name of Object.keys(variants).filter(n=>n!=='RITA_BASE')){summary[name]={};for(const opp of ['RITA_BASE','MATEO']){const r=games.filter(g=>(g.a===name&&g.b===opp)||(g.a===opp&&g.b===name)).map(g=>g.a===name?{bank:g.ba,opp:g.bb,error:g.errors}:{bank:g.bb,opp:g.ba,error:g.errors});summary[name][opp]={episodes:r.length,wins:r.filter(x=>x.bank>x.opp).length,ties:r.filter(x=>x.bank===x.opp).length,winRate:r.filter(x=>x.bank>x.opp).length/r.length,avgBank:avg(r.map(x=>x.bank)),avgMargin:avg(r.map(x=>x.bank-x.opp)),errors:r.reduce((a,x)=>a+x.error,0)};}}\nconst ranking=Object.entries(summary).map(([name,s]:any)=>({name,parentWin:s.RITA_BASE.winRate,parentMargin:s.RITA_BASE.avgMargin,parentBank:s.RITA_BASE.avgBank,mateoWin:s.MATEO.winRate,mateoMargin:s.MATEO.avgMargin})).sort((a,b)=>b.parentWin-a.parentWin||b.parentMargin-a.parentMargin||b.mateoWin-a.mateoWin);\nconsole.log(JSON.stringify({status:'PASS',evidenceState:'MIT_RITA_POLICY_NEURON_SCREEN_ON_OFFICIAL_TS_PORT',seeds,ranking,summary},null,2));",[312],"72afe9f5-9c71-4ff3-a75f-60549a195150","kaggriculture_rita_gen2_sweep_v1.ts","02730b8e-aa3a-11f1-a463-1607ee4eb77e",46,["D",1788730155091],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zr.ok)throw new Error(String(zr.status));const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);\nconst patches:Record={RITA_BASE:{},C4S12:{animal_target:{COW:4,SHEEP:12}},C5S11:{animal_target:{COW:5,SHEEP:11}},C6S10:{animal_target:{COW:6,SHEEP:10}},C7S9:{animal_target:{COW:7,SHEEP:9}},C8S8:{animal_target:{COW:8,SHEEP:8}},C6S10_F20:{animal_target:{COW:6,SHEEP:10},feed_float_days:20},C6S10_L1:{animal_target:{COW:6,SHEEP:10},land:1},C6S10_H6:{animal_target:{COW:6,SHEEP:10},hands:6},C6S10_H10:{animal_target:{COW:6,SHEEP:10},hands:10}};\nconst py=await loadPyodide();py.runPython(`import json\\n_REG={}`);py.globals.set('src',src);for(const [name,patch] of Object.entries(patches)){py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n['agent']`);}py.runPython(`def call(name,payload):\\n return json.dumps(_REG[name](json.loads(payload)))`);const call=py.globals.get('call');\nconst seeds=[9101,9137,9187,9221,9277,9311];const challengers=Object.keys(patches).filter(x=>!['RITA_BASE','C6S10'].includes(x));\nasync function play(a:string,b:string,seed:number){const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);let errors=0;while(!s.done){const acts=[];for(const [pid,n] of [[0,a],[1,b]] as any){try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(observationFor(s,pid)))));}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,cfg);}return{a,b,ba:s.farms[0].money,bb:s.farms[1].money,errors};}\nconst games:any[]=[];for(const c of challengers)for(const opp of ['C6S10','RITA_BASE'])for(const seed of seeds){games.push(await play(c,opp,seed));games.push(await play(opp,c,seed));}\nconst avg=(x:number[])=>x.reduce((a,b)=>a+b,0)/(x.length||1);const out:any={};for(const c of challengers){out[c]={};for(const opp of ['C6S10','RITA_BASE']){const r=games.filter(g=>(g.a===c&&g.b===opp)||(g.a===opp&&g.b===c)).map(g=>g.a===c?{b:g.ba,o:g.bb,e:g.errors}:{b:g.bb,o:g.ba,e:g.errors});out[c][opp]={episodes:r.length,wins:r.filter(x=>x.b>x.o).length,ties:r.filter(x=>x.b===x.o).length,winRate:r.filter(x=>x.b>x.o).length/r.length,avgBank:avg(r.map(x=>x.b)),avgMargin:avg(r.map(x=>x.b-x.o)),errors:r.reduce((a,x)=>a+x.e,0)};}}\nconst rank=Object.entries(out).map(([n,s]:any)=>({name:n,vsC6S10:s.C6S10.winRate,marginVsC6S10:s.C6S10.avgMargin,vsRita:s.RITA_BASE.winRate,marginVsRita:s.RITA_BASE.avgMargin,avgBankVsRita:s.RITA_BASE.avgBank})).sort((a,b)=>b.vsC6S10-a.vsC6S10||b.marginVsC6S10-a.marginVsC6S10||b.vsRita-a.vsRita);\nconsole.log(JSON.stringify({status:'PASS',evidenceState:'RITA_GEN2_STATIC_MUTATION_SCREEN_OFFICIAL_TS_PORT',seeds,rank,out},null,2));",[319],"75d35ba4-43d8-44f7-96fd-2b8f3405f1c6","kaggriculture_rita_adaptive_race_v2.ts","18e2f87e-aa40-11f1-ad35-1607ee4eb77e",54,["D",1788732769678],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { sprt, wilson } from './lib/kaggriculture_adaptive_racing.ts';\n\nconst baseline='C6S10';\nconst patches:Record={\n RITA_BASE:{},\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C5S11:{animal_target:{COW:5,SHEEP:11}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n C7S9:{animal_target:{COW:7,SHEEP:9}},\n C8S8:{animal_target:{COW:8,SHEEP:8}},\n C6S10_F20:{animal_target:{COW:6,SHEEP:10},feed_float_days:20},\n C6S10_L1:{animal_target:{COW:6,SHEEP:10},land:1},\n C6S10_H6:{animal_target:{COW:6,SHEEP:10},hands:6},\n C6S10_H10:{animal_target:{COW:6,SHEEP:10},hands:10},\n};\nconst candidates=Object.keys(patches).filter(x=>!['RITA_BASE',baseline].includes(x));\nconst seeds=[9403,9419,9431,9461,9491,9511,9533,9551,9587,9613,9643,9677,9701,9721,9749,9769,9791,9811,9833,9857];\nconst now=new Date().toISOString();\n\n// Ensure resumable race rows exist.\nawait sqlite.batch(candidates.map(c=>({\n sql:`INSERT OR IGNORE INTO kag_race_state(candidate_id,baseline_id,updated_at) VALUES(?,?,?)`,\n args:[c,baseline,now]\n})));\nconst prior=await sqlite.execute(`SELECT * FROM kag_race_state WHERE baseline_id=? ORDER BY candidate_id`,[baseline]);\nconst active=(prior.rows as any[]).filter(r=>r.decision==='CONTINUE' && Number(r.next_seed_index)e.opp?'WIN':e.bank=8?test.decision:'CONTINUE';\n statements.push({sql:`UPDATE kag_race_state SET wins=?,losses=?,ties=?,margin_sum=?,episodes=?,llr=?,decision=?,next_seed_index=?,updated_at=? WHERE candidate_id=? AND baseline_id=?`,args:[wins,losses,ties,margin,n,test.llr,decision,idx+1,new Date().toISOString(),candidate,baseline]});\n round.push({candidate,seed,wins,losses,ties,episodes:n,avgMargin:margin/n,llr:test.llr,decision,wilson:wilson(wins,losses)});\n}\nif(statements.length)await sqlite.batch(statements);\nconst after=await sqlite.execute(`SELECT candidate_id,wins,losses,ties,episodes,CASE WHEN episodes>0 THEN margin_sum/episodes ELSE 0 END AS avg_margin,llr,decision,next_seed_index FROM kag_race_state WHERE baseline_id=? ORDER BY decision,candidate_id`,[baseline]);\nconsole.log(JSON.stringify({status:'PASS',method:'RESUMABLE_ADAPTIVE_RACING',baseline,processedCandidates:active.length,round,after:after.rows,caveat:'SPRT tests p=0.50 vs p=0.65 on decisive games; ties remain separate diagnostics. Promotion still requires broader league evaluation.'},null,2));\n",[326],"b8decdbc-71ee-4910-a732-3dd159011cbc","kaggriculture_research_fusion_selftest.ts","70ad93f8-aa3f-11f1-a880-1607ee4eb77e",52,["D",1788732487513],"import { EmpiricalLeague, regretMatchingMix, mixEntropy } from \"./lib/kaggriculture_league.ts\";\nimport { BayesianRouter, shouldReplanMacro, opponentFamilyLikelihood } from \"./lib/kaggriculture_bayesian_router.ts\";\nimport { lowerTailCVaR, riskAdjustedProfit, shadowValue, sellHoldDecision, reserveOptionValue, rankBottlenecks, liquidationPressure, returnOnCommittedCapital } from \"./lib/kaggriculture_farm_economics.ts\";\nimport { sprt, wilson, allocateBatch, dominanceDecision } from \"./lib/kaggriculture_adaptive_racing.ts\";\n\nconst checks:{name:string;pass:boolean;detail?:unknown}[]=[];\nconst check=(name:string,pass:boolean,detail?:unknown)=>{checks.push({name,pass,detail}); if(!pass) throw new Error(name)};\n\n// League / PSRO-like controls.\nconst L=new EmpiricalLeague();\nfor(const m of [\n {id:\"MAIN\",role:\"MAIN\" as const},\n {id:\"OLD\",role:\"HISTORICAL\" as const,frozen:true},\n {id:\"EXP\",role:\"EXPLOITER\" as const},\n {id:\"REF\",role:\"REFERENCE\" as const},\n]) L.add(m);\nfor(let i=0;i<8;i++) L.record(\"MAIN\",\"OLD\",\"WIN\");\nfor(let i=0;i<2;i++) L.record(\"MAIN\",\"OLD\",\"LOSS\");\nfor(let i=0;i<2;i++) L.record(\"MAIN\",\"EXP\",\"WIN\");\nfor(let i=0;i<8;i++) L.record(\"MAIN\",\"EXP\",\"LOSS\");\nconst weights=L.pfspWeights(\"MAIN\",[\"OLD\",\"EXP\",\"REF\"]);\nconst wMap=new Map(weights.map(x=>[x.id,x.probability]));\ncheck(\"PFSP prioritizes known weakness over easy historical\",(wMap.get(\"EXP\")??0)>(wMap.get(\"OLD\")??0),weights);\ncheck(\"weakness detector finds exploiter first\",L.weaknesses(\"MAIN\",1)[0].id===\"EXP\",L.weaknesses(\"MAIN\",3));\nL.freezeSnapshot(\"MAIN\",\"MAIN@1\");\ncheck(\"historical snapshot frozen\",L.members.get(\"MAIN@1\")?.frozen===true,L.members.get(\"MAIN@1\"));\n\n// RPS should retain diversity under regret matching, not collapse to one pure strategy.\nconst rps=[[0,-1,1],[1,0,-1],[-1,1,0]];\nconst mix=regretMatchingMix(rps,10000);\ncheck(\"RPS meta-solver preserves three-way mixture\",mix.every(p=>Math.abs(p-1/3)<0.04),mix);\ncheck(\"RPS entropy high\",mixEntropy(mix)>1.05,mixEntropy(mix));\n\n// Bayesian world/opponent routing.\nconst R=new BayesianRouter([{id:\"CROP\",prior:0.25},{id:\"LIVESTOCK\",prior:0.25},{id:\"MARKET_HEAVY\",prior:0.25},{id:\"MIXED\",prior:0.25}]);\nconst like=opponentFamilyLikelihood({cropShare:0.1,livestockCount:12,recentSellIntensity:0.15,landUnlocked:3});\nconst up=R.update({name:\"visible herd\",likelihood:like});\ncheck(\"Bayes raises livestock family\",R.best().id===\"LIVESTOCK\",{like,posterior:R.distribution()});\ncheck(\"macro does not replan every turn\",shouldReplanMacro({previousBest:\"LIVESTOCK\",currentBest:\"LIVESTOCK\",posteriorConfidence:R.confidence(),informationGainKL:up.kl,event:\"NO_EVENT\"})===false);\ncheck(\"horizon phase forces replan\",shouldReplanMacro({previousBest:\"LIVESTOCK\",currentBest:\"LIVESTOCK\",posteriorConfidence:R.confidence(),informationGainKL:0,event:\"HORIZON_PHASE\"})===true);\n\n// Farm economics.\nconst profits=[100,110,120,130,140,150,160,170,180,190];\ncheck(\"lower-tail CVaR uses worst tail\",lowerTailCVaR(profits,0.2)===105,lowerTailCVaR(profits,0.2));\ncheck(\"risk-adjusted profit below mean\",riskAdjustedProfit(profits,0.5,0.2)<145,riskAdjustedProfit(profits,0.5,0.2));\ncheck(\"positive shadow value detected\",shadowValue(1000,1250,5,50)===40,shadowValue(1000,1250,5,50));\nconst hold=sellHoldDecision({spotPrice:60,expectedFuturePrice:90,holdingCost:5,strategicExternality:0,optionFlexibilityValue:3});\ncheck(\"dynamic sell/hold can prefer hold\",hold.action===\"HOLD\",hold);\nconst strategic=sellHoldDecision({spotPrice:60,expectedFuturePrice:90,holdingCost:5,strategicExternality:35,optionFlexibilityValue:3});\ncheck(\"opponent externality can flip hold to sell\",strategic.action===\"SELL\",strategic);\nconst reserve=reserveOptionValue({interruptionProbability:0.25,lossIfInterrupted:1000,reserveCarryingCost:20,reservePurchaseCost:100});\ncheck(\"reserve option valued from avoided interruption\",reserve.shouldHoldReserve===true,reserve);\nconst bottlenecks=rankBottlenecks([{resource:\"LAND\",shadowValue:-5,utilization:1},{resource:\"FEED\",shadowValue:40,utilization:0.95},{resource:\"LABOR\",shadowValue:10,utilization:0.5}]);\ncheck(\"positive binding resource ranks first\",bottlenecks[0].resource===\"FEED\",bottlenecks);\ncheck(\"liquidation pressure rises near horizon\",liquidationPressure(3,3,0,100)>liquidationPressure(100,3,0,100),{near:liquidationPressure(3,3,0,100),far:liquidationPressure(100,3,0,100)});\ncheck(\"return on capital computed\",returnOnCommittedCapital(500,1000)===0.5);\n\n// Adaptive experiment racing.\nconst strong=sprt({wins:40,losses:10,p0:0.5,p1:0.65});\ncheck(\"SPRT can promote strong branch\",strong.decision===\"PROMOTE_H1\",strong);\nconst weak=sprt({wins:10,losses:40,p0:0.5,p1:0.65});\ncheck(\"SPRT can reject weak branch\",weak.decision===\"REJECT_H1\",weak);\nconst ci10=wilson(6,4), ci100=wilson(60,40);\ncheck(\"uncertainty shrinks with more matches\",(ci100.high-ci100.low)<(ci10.high-ci10.low),{ci10,ci100});\nconst batch=allocateBatch([\n {id:\"UNCERTAIN\",wins:6,losses:4,avgMargin:100},\n {id:\"OBVIOUS\",wins:95,losses:5,avgMargin:500},\n],20);\ncheck(\"adaptive racing spends more tests on uncertain branch\",(batch.find(x=>x.id===\"UNCERTAIN\")?.matches??0)>(batch.find(x=>x.id===\"OBVIOUS\")?.matches??0),batch);\nconst dom=dominanceDecision({id:\"A\",wins:95,losses:5,avgMargin:500},{id:\"B\",wins:20,losses:80,avgMargin:-100});\ncheck(\"clear fixed-checkpoint dominance detected\",dom.decision===\"A_DOMINATES\",dom);\n\nconsole.log(JSON.stringify({status:\"PASS\",checks:checks.length,details:checks},null,2));\n",[333],"c063ae72-97a0-458b-9ec5-d623aceade02","kaggriculture_remote_probe.ts","ded83b20-aa36-11f1-9d57-1607ee4eb77e",17,["D",1788728806872],"const urls = [\n \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/visualizer/playable/src/engine/constants.ts\",\n \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/visualizer/playable/src/engine/interpreter.ts\",\n];\n\nconst out = [];\nfor (const url of urls) {\n const res = await fetch(url);\n const text = await res.text();\n out.push({ url, status: res.status, ok: res.ok, length: text.length, head: text.slice(0, 120) });\n}\nconsole.log(JSON.stringify({ status: out.every(x => x.ok) ? \"PASS\" : \"FAIL\", out }, null, 2));\n",[340],"8def5161-d26b-4d52-b253-6dc0286e86f3","kaggriculture_reference_ladder_screen_v1.ts","60eb6e46-aa39-11f1-9aaa-1607ee4eb77e",42,["D",1788729884084],"import { unzipSync, strFromU8 } from \"npm:fflate\";\nimport { loadPyodide } from \"npm:pyodide\";\nimport { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst OUR:Record={\n H3_T8:buildAgent({crop:'CARROT',targetHands:3,maxTiles:8,persistent:true,seedBuffer:12}),\n H4_T10:buildAgent({crop:'CARROT',targetHands:4,maxTiles:10,persistent:true,seedBuffer:15}),\n H6_T12:buildAgent({crop:'CARROT',targetHands:6,maxTiles:12,persistent:true,seedBuffer:18}),\n};\nconst refs=['fallow_finn.py','wheat_walter.py','rotation_rosa.py','homestead_hana.py','melon_mateo.py','rancher_rita.py'];\nconst zipRes=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zipRes.ok)throw new Error(`dataset ${zipRes.status}`);const files=unzipSync(new Uint8Array(await zipRes.arrayBuffer()));\nconst py=await loadPyodide();py.runPython(`import json\\n_REG={}`);\nfor(const file of refs){py.globals.set('src',strFromU8(files[file]));py.globals.set('nm',file);py.runPython(`_ns={}\\nexec(src,_ns)\\n_REG[nm]=_ns['agent']`);}\npy.runPython(`def call_ref(name,payload):\\n return json.dumps(_REG[name](json.loads(payload)))`);const call=py.globals.get('call_ref');\nconst seeds=[7001,7027];\nasync function play(ourName:string,ref:string,seed:number,ourSeat:0|1){const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);let errors=0;while(!s.done){const actions:any[]=[null,null];actions[ourSeat]=OUR[ourName](observationFor(s,ourSeat));const rseat=(1-ourSeat) as 0|1;try{actions[rseat]=JSON.parse(String(call(ref,JSON.stringify(observationFor(s,rseat)))));}catch(e){errors++;actions[rseat]={farmer:['PASS'],hands:[],market:[]};}s=E.interpreter.step(s,actions,cfg);}const ob=s.farms[ourSeat].money,rb=s.farms[1-ourSeat].money;return {ourName,ref,seed,ourSeat,ourBank:ob,refBank:rb,win:ob>rb,tie:ob===rb,errors};}\nconst games:any[]=[];for(const ourName of Object.keys(OUR))for(const ref of refs)for(const seed of seeds){games.push(await play(ourName,ref,seed,0));games.push(await play(ourName,ref,seed,1));}\nconst avg=(xs:number[])=>xs.reduce((a,b)=>a+b,0)/(xs.length||1);const summary:any={};for(const ourName of Object.keys(OUR)){summary[ourName]={};for(const ref of refs){const r=games.filter(g=>g.ourName===ourName&&g.ref===ref);summary[ourName][ref]={episodes:r.length,wins:r.filter(g=>g.win).length,ties:r.filter(g=>g.tie).length,winRate:r.filter(g=>g.win).length/r.length,avgBank:avg(r.map(g=>g.ourBank)),avgRefBank:avg(r.map(g=>g.refBank)),avgMargin:avg(r.map(g=>g.ourBank-g.refBank)),errors:r.reduce((a,g)=>a+g.errors,0)};}}\nconsole.log(JSON.stringify({status:'PASS',evidenceState:'PYODIDE_MIT_REFERENCE_AGENTS_ON_OFFICIAL_TS_PORT',seeds,referenceDataset:'raykkretzschmar/kaggriculture-reference-agents v8 MIT',summary},null,2));",[347],"db972f17-15a7-4205-b117-04784524bad7","kaggriculture_py_reference_interop_probe.ts","4fb7c73c-aa39-11f1-8d5f-1607ee4eb77e",41,["D",1788729855237],"import { unzipSync, strFromU8 } from \"npm:fflate\";\nimport { loadPyodide } from \"npm:pyodide\";\nimport { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { K0 } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst zipRes=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');\nif(!zipRes.ok)throw new Error(`dataset ${zipRes.status}`);\nconst files=unzipSync(new Uint8Array(await zipRes.arrayBuffer()));\nconst source=strFromU8(files['rotation_rosa.py']);\nconst py=await loadPyodide();\npy.globals.set('agent_source',source);\npy.runPython(`\nimport json\n_ns={}\nexec(agent_source,_ns)\n_agent=_ns['agent']\ndef call_agent_json(payload):\n return json.dumps(_agent(json.loads(payload)))\n`);\nconst call=py.globals.get('call_agent_json');\nconst E=await loadOfficialKaggricultureEngine();const seed=4242;const cfg=E.state.resolveConfig({seed});let state=E.state.initGameState(2,cfg,seed);let calls=0,errors=0;\nwhile(!state.done){\n const a0=K0(observationFor(state,0));let a1:any;\n try{a1=JSON.parse(String(call(JSON.stringify(observationFor(state,1)))));calls++;}catch(e){errors++;a1={farmer:['PASS'],hands:[],market:[]};}\n state=E.interpreter.step(state,[a0,a1],cfg);\n}\nconsole.log(JSON.stringify({status:errors===0?'PASS':'PARTIAL',reference:'rotation_rosa.py',license:'MIT dataset',seed,calls,errors,finalBanks:state.farms.map((f:any)=>f.money),winner:state.farms[0].money===state.farms[1].money?'TIE':state.farms[0].money>state.farms[1].money?'K0':'ROTATION_ROSA'},null,2));",[354],"eb8dc61e-c883-49fb-bc6e-b83ce367c5dd","kaggriculture_official_port_probe.ts","ef9a676c-aa36-11f1-a686-1607ee4eb77e",18,["D",1788728834984],"const BASE = \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/visualizer/playable/src/engine/\";\nconst FILES = [\"types.ts\",\"constants.ts\",\"market.ts\",\"rng.ts\",\"state.ts\",\"interpreter.ts\"];\n\nfunction stripImports(src: string): string {\n // Remove multiline/single-line ES imports; concatenation supplies symbols in one module.\n return src.replace(/^import[\\s\\S]*?;\\s*$/gm, \"\");\n}\n\nconst chunks: string[] = [];\nconst fetched: Array> = [];\nfor (const file of FILES) {\n const url = BASE + file;\n const res = await fetch(url);\n const text = await res.text();\n if (!res.ok) throw new Error(`fetch failed ${file}: ${res.status}`);\n chunks.push(`\\n// ===== ${file} =====\\n` + stripImports(text));\n fetched.push({ file, bytes: text.length });\n}\n\nconst source = chunks.join(\"\\n\");\nconst dataUrl = \"data:application/typescript;base64,\" + btoa(unescape(encodeURIComponent(source)));\nconst engine = await import(dataUrl);\n\nconst cfg = engine.resolveConfig({ seed: 12345 });\nlet state = engine.initGameState(2, cfg, 12345);\nconst PASS = { farmer: [\"PASS\"], hands: [], market: [] };\nconst start = { step: state.step, day: state.day, hour: state.hour, money: state.farms.map((f: any)=>f.money) };\nstate = engine.step(state, [PASS, PASS], cfg);\nconst after = { step: state.step, day: state.day, hour: state.hour, money: state.farms.map((f: any)=>f.money), done: state.done };\n\nconsole.log(JSON.stringify({\n status: \"PASS\",\n fetched,\n sourceBytes: source.length,\n exports: Object.keys(engine).sort(),\n config: cfg,\n start,\n after,\n}, null, 2));\n",[361],"64d8c272-605c-49ab-bbc0-2124c3f4fc49","kaggriculture_official_module_probe.ts","4a004de8-aa37-11f1-9f0b-1607ee4eb77e",19,["D",1788728986637],"const RAW_BASE = \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/visualizer/playable/src/engine/\";\nconst SPEC_URL = \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/kaggriculture.json\";\n\nconst names = [\"types\", \"constants\", \"market\", \"rng\", \"state\", \"interpreter\"] as const;\ntype Name = typeof names[number];\nconst raw = new Map();\n\nfor (const name of names) {\n const res = await fetch(`${RAW_BASE}${name}.ts`);\n if (!res.ok) throw new Error(`fetch ${name}.ts failed: ${res.status}`);\n raw.set(name, await res.text());\n}\nconst specRes = await fetch(SPEC_URL);\nif (!specRes.ok) throw new Error(`fetch kaggriculture.json failed: ${specRes.status}`);\nconst specText = await specRes.text();\nJSON.parse(specText); // fail early if source is not valid JSON\n\nconst moduleUrls = new Map();\n\nfunction toDataUrl(source: string) {\n const bytes = new TextEncoder().encode(source);\n let binary = \"\";\n // chunk to avoid argument/stack limits\n for (let i = 0; i < bytes.length; i += 0x8000) {\n binary += String.fromCharCode(...bytes.subarray(i, i + 0x8000));\n }\n return `data:application/typescript;base64,${btoa(binary)}`;\n}\n\nfunction compileModule(name: Name): string {\n let src = raw.get(name)!;\n\n // Type-only imports have no runtime role and are removed.\n src = src.replace(/import\\s+type\\s+\\{[\\s\\S]*?\\}\\s+from\\s+['\"][^'\"]+['\"];?\\s*/g, \"\");\n\n // constants.ts intentionally reads defaults from the official JSON spec.\n if (name === \"constants\") {\n src = src.replace(\n /import\\s+spec\\s+from\\s+['\"]\\.\\.\\/\\.\\.\\/\\.\\.\\/\\.\\.\\/kaggriculture\\.json['\"];?\\s*/,\n `const spec = ${specText};\\n`,\n );\n }\n\n // Rewrite relative runtime imports to already-compiled data modules.\n src = src.replace(\n /import\\s+\\{([\\s\\S]*?)\\}\\s+from\\s+['\"]\\.\\/([A-Za-z0-9_-]+)['\"];?\\s*/g,\n (_all, symbols: string, dep: string) => {\n const depUrl = moduleUrls.get(dep as Name);\n if (!depUrl) throw new Error(`${name}: runtime dependency ${dep} was not compiled first`);\n return `import {${symbols}} from ${JSON.stringify(depUrl)};\\n`;\n },\n );\n\n const unresolved = [...src.matchAll(/from\\s+['\"](\\.\\.?\\/[^'\"]+)['\"]/g)].map((m) => m[1]);\n if (unresolved.length) throw new Error(`${name}: unresolved imports ${unresolved.join(\", \")}`);\n return src;\n}\n\nfor (const name of names) {\n const compiled = compileModule(name);\n moduleUrls.set(name, toDataUrl(compiled));\n}\n\nconst stateMod = await import(moduleUrls.get(\"state\")!);\nconst engine = await import(moduleUrls.get(\"interpreter\")!);\nconst constants = await import(moduleUrls.get(\"constants\")!);\n\nconst cfg = stateMod.resolveConfig({ seed: 12345 });\nlet state = stateMod.initGameState(2, cfg, 12345);\nconst PASS = { farmer: [\"PASS\"], hands: [], market: [] };\nconst initial = {\n step: state.step,\n day: state.day,\n hour: state.hour,\n money: state.farms.map((f: any) => f.money),\n carrot: constants.MARKET_PARAMS.CARROT,\n};\nstate = engine.step(state, [PASS, PASS], cfg);\nconst after1 = {\n step: state.step,\n day: state.day,\n hour: state.hour,\n money: state.farms.map((f: any) => f.money),\n done: state.done,\n};\n\nconsole.log(JSON.stringify({\n status: \"PASS\",\n fetched: names.map((name) => ({ name, bytes: raw.get(name)!.length })),\n officialCommitMode: \"master-at-runtime\",\n config: cfg,\n initial,\n after1,\n}, null, 2));\n",[368],"f4ce025a-bc5e-4790-82fd-156e381c5dd8","kaggriculture_market_timing_sweep_v1.ts","f7d5a476-aa38-11f1-9404-1607ee4eb77e",35,["D",1788729723611],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\nimport { withSellPolicy, AFTER_TOWN_HOURS, BEFORE_TOWN_HOURS } from \"./lib/kaggriculture_market_mutations.ts\";\n\nconst E=await loadOfficialKaggricultureEngine();\nconst base=()=>buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:true,seedBuffer:15});\nconst variants:Record={\n SELL_ALL:base(),\n AFTER_ALL:withSellPolicy(base(),{name:\"AFTER_ALL\",allowedHours:AFTER_TOWN_HOURS}),\n AFTER_L4:withSellPolicy(base(),{name:\"AFTER_L4\",allowedHours:AFTER_TOWN_HOURS,lotSize:4}),\n AFTER_L8:withSellPolicy(base(),{name:\"AFTER_L8\",allowedHours:AFTER_TOWN_HOURS,lotSize:8}),\n AFTER_L12:withSellPolicy(base(),{name:\"AFTER_L12\",allowedHours:AFTER_TOWN_HOURS,lotSize:12}),\n BEFORE_L8:withSellPolicy(base(),{name:\"BEFORE_L8\",allowedHours:BEFORE_TOWN_HOURS,lotSize:8}),\n FLOOR25_L8:withSellPolicy(base(),{name:\"FLOOR25_L8\",allowedHours:AFTER_TOWN_HOURS,lotSize:8,reservePrice:25,forceShedLoad:85}),\n FLOOR40_L8:withSellPolicy(base(),{name:\"FLOOR40_L8\",allowedHours:AFTER_TOWN_HOURS,lotSize:8,reservePrice:40,forceShedLoad:85}),\n FLOOR60_L8:withSellPolicy(base(),{name:\"FLOOR60_L8\",allowedHours:AFTER_TOWN_HOURS,lotSize:8,reservePrice:60,forceShedLoad:85}),\n};\nconst worlds:Record={LOW:[],D7:[\"FARMERS_MARKET\"],D13:[\"PET_CAFE\"],D19:[\"PET_CAFE\",\"FARMERS_MARKET\"],D31:[\"PET_CAFE\",\"PET_CAFE\",\"FARMERS_MARKET\"]};\n\nasync function play(agent:AgentFn,shops:string[]){\n const cfg=E.state.resolveConfig({seed:314159,weedSpawnChance:0,townShopUnlockInterval:9999});\n let s=E.state.initGameState(2,cfg,314159);s.town.unlocked_shops=[...shops];\n let sold=0,sellOrders=0;\n while(!s.done){const a=agent(observationFor(s,0)),b=STARTER(observationFor(s,1));for(const o of a.market??[]){if(o?.[0]===\"SELL\"&&o?.[1]===\"CARROT\"){sold+=Number(o?.[2]??0);sellOrders++;}}s=E.interpreter.step(s,[a,b],cfg);}\n return {bank:s.farms[0].money,starter:s.farms[1].money,margin:s.farms[0].money-s.farms[1].money,price:s.market.prices.CARROT,inventory:s.market.inventory.CARROT,shed:s.privates[0].shed.CARROT,soldRequested:sold,sellOrders};\n}\nconst out:any={};\nfor(const [world,shops] of Object.entries(worlds)){\n const rows=[];\n for(const [name,a] of Object.entries(variants)) rows.push({name,...await play(a,shops)});\n rows.sort((x,y)=>y.margin-x.margin||y.bank-x.bank);\n out[world]=rows;\n}\nconst compact=Object.fromEntries(Object.entries(out).map(([world,rows]:any)=>[world,rows.slice(0,4)]));\nconsole.log(JSON.stringify({status:\"PASS\",evidenceState:\"MARKET_TIMING_ABLATION_OFFICIAL_TS_PORT\",config:{seed:314159,weedSpawnChance:0,townShopUnlockInterval:9999},compact},null,2));",[375],"e28a79ad-37b5-4814-af3f-d7c903006e29","kaggriculture_livestock_portfolio_selftest.ts","0ba224fe-aa41-11f1-a1f2-1607ee4eb77e",61,["D",1788733176985],"import { marketPrice,caredProductionUnits,expectedTownDemandRemaining,choosePastureAnimal,scoreAnimalInvestment } from './lib/kaggriculture_livestock_portfolio.ts';\nconst checks:any[]=[];const check=(name:string,pass:boolean,detail?:any)=>{checks.push({name,pass,detail});if(!pass)throw new Error(name)};\nfunction obs(day=0,cash=3000,shops:string[]=[]){const mk={MILK:10000,WOOL:10000,EGG:10000,WHEAT:10000};const prices={MILK:160,WOOL:200,EGG:50,WHEAT:25};const farm={money:cash,tiles:Array.from({length:10},()=>Array(10).fill(null)),hands:[],unlocked_quadrants:['NW']};return{player:0,day,hour:0,market:{inventory:mk,prices},town:{unlocked_shops:shops},farms:[farm,structuredClone(farm)]};}\ncheck('base milk price exact',marketPrice('MILK',10000)===160,marketPrice('MILK',10000));\ncheck('base wool price exact',marketPrice('WOOL',10000)===200,marketPrice('WOOL',10000));\ncheck('cow cared production day0',caredProductionUnits('COW',0)===22,caredProductionUnits('COW',0));\ncheck('sheep cared production day0',caredProductionUnits('SHEEP',0)===16,caredProductionUnits('SHEEP',0));\ncheck('late horizon favors sheep production availability',caredProductionUnits('SHEEP',22)>caredProductionUnits('COW',22),{sheep:caredProductionUnits('SHEEP',22),cow:caredProductionUnits('COW',22)});\nconst d0=obs();check('expected milk demand > wool under unknown future shops',expectedTownDemandRemaining(d0,'MILK')>expectedTownDemandRemaining(d0,'WOOL'),{milk:expectedTownDemandRemaining(d0,'MILK'),wool:expectedTownDemandRemaining(d0,'WOOL')});\nconst early=choosePastureAnimal(obs(0,3000));check('early ranking has finite scores',early.ranking.every(x=>Number.isFinite(x.net)),early);\nconst late=choosePastureAnimal(obs(22,3000));check('late ranking can distinguish horizon',late.ranking[0].net!==late.ranking[1].net,late);\nconst poor=scoreAnimalInvestment({obs:obs(5,450),animal:'SHEEP',cashBuffer:300});check('liquidity penalty applies below buffer',poor.liquidityPenalty>0,poor);\nconsole.log(JSON.stringify({status:'PASS',checks:checks.length,details:checks,early,late},null,2));",[382],"419d02aa-12d1-4e8f-bd99-2a67d57c99b0","kaggriculture_knowledge_migrate_v1.ts","05390f3e-aa40-11f1-b79b-1607ee4eb77e",53,["D",1788732736730],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nconst now=new Date().toISOString();\nawait sqlite.batch([\n {sql:`CREATE TABLE IF NOT EXISTS kag_league_members(\n member_id TEXT PRIMARY KEY, role TEXT NOT NULL, lineage TEXT, frozen INTEGER NOT NULL DEFAULT 0,\n status TEXT NOT NULL DEFAULT 'ACTIVE', source TEXT, evidence_state TEXT, created_at TEXT NOT NULL, updated_at TEXT NOT NULL)`},\n {sql:`CREATE TABLE IF NOT EXISTS kag_match_results(\n match_id TEXT PRIMARY KEY, a_id TEXT NOT NULL, b_id TEXT NOT NULL, seed INTEGER, mirrored INTEGER NOT NULL DEFAULT 0,\n bank_a REAL, bank_b REAL, result_a TEXT, runtime_errors INTEGER NOT NULL DEFAULT 0,\n evidence_state TEXT NOT NULL, created_at TEXT NOT NULL)`},\n {sql:`CREATE INDEX IF NOT EXISTS idx_kag_match_pair ON kag_match_results(a_id,b_id,created_at)`},\n {sql:`CREATE TABLE IF NOT EXISTS kag_race_state(\n candidate_id TEXT NOT NULL, baseline_id TEXT NOT NULL, wins INTEGER NOT NULL DEFAULT 0, losses INTEGER NOT NULL DEFAULT 0,\n ties INTEGER NOT NULL DEFAULT 0, margin_sum REAL NOT NULL DEFAULT 0, episodes INTEGER NOT NULL DEFAULT 0,\n llr REAL NOT NULL DEFAULT 0, decision TEXT NOT NULL DEFAULT 'CONTINUE', next_seed_index INTEGER NOT NULL DEFAULT 0,\n updated_at TEXT NOT NULL, PRIMARY KEY(candidate_id,baseline_id))`},\n {sql:`CREATE TABLE IF NOT EXISTS kag_research_claims(\n claim_id TEXT PRIMARY KEY, track TEXT NOT NULL, source_type TEXT NOT NULL, title TEXT NOT NULL, url TEXT,\n mechanism TEXT NOT NULL, kag_mapping TEXT NOT NULL, hypothesis TEXT NOT NULL,\n status TEXT NOT NULL DEFAULT 'CANDIDATE', created_at TEXT NOT NULL, updated_at TEXT NOT NULL)`},\n {sql:`CREATE TABLE IF NOT EXISTS kag_strategy_lessons(\n lesson_id TEXT PRIMARY KEY, lesson_type TEXT NOT NULL, mechanism TEXT NOT NULL, preconditions TEXT,\n counterfactual TEXT, detector TEXT, evidence_state TEXT NOT NULL, created_at TEXT NOT NULL, updated_at TEXT NOT NULL)`},\n {sql:`INSERT OR IGNORE INTO kag_league_members(member_id,role,lineage,frozen,status,source,evidence_state,created_at,updated_at) VALUES\n ('RITA_BASE','REFERENCE','RITA',1,'ACTIVE','Kaggle reference agents','PUBLIC_REFERENCE',?,?),\n ('C6S10','MAIN','RITA→C6S10',1,'CHALLENGER','Neurônio mutation','LOCAL_SCREEN',?,?),\n ('MELON_MATEO','REFERENCE','REFERENCE',1,'ACTIVE','Kaggle reference agents','PUBLIC_REFERENCE',?,?),\n ('ROTATION_ROSA','REFERENCE','REFERENCE',1,'ACTIVE','Kaggle reference agents','PUBLIC_REFERENCE',?,?)`,args:[now,now,now,now,now,now,now,now]},\n {sql:`INSERT OR IGNORE INTO kag_research_claims(claim_id,track,source_type,title,url,mechanism,kag_mapping,hypothesis,status,created_at,updated_at) VALUES\n ('A-LEAGUE-HISTORY','AGENT','RESEARCH','Historical opponent pools','https://arxiv.org/abs/2011.12895','Training against historical opponent pools improves robustness and reduces overfitting','Freeze old champions and sample them during training/evaluation','Historical snapshots prevent forgetting and cyclic collapse','IMPLEMENTED',?,?),\n ('A-PSRO-BR','AGENT','RESEARCH','Policy Space Response Oracles','https://arxiv.org/abs/2408.01072','Iteratively add best responses to a strategy population','Maintain empirical payoff matrix plus specialized exploiters','Best-response offspring expose champion weaknesses faster than blind mutation','IMPLEMENTED',?,?),\n ('B-SELL-CUTOFF','ECONOMICS','RESEARCH','Optimal selling policies for farmer cooperatives','https://journals.sagepub.com/doi/abs/10.1111/poms.13091','Dynamic inventory models produce state-dependent cutoff selling policies','Replace fixed sell floor with expected future value, holding cost, horizon and opponent externality','State-dependent sell/hold beats fixed reservation price across market regimes','IMPLEMENTED',?,?),\n ('B-DUOPOLY-PRICE','ECONOMICS','RESEARCH','Dynamic pricing and inventory control under competition','https://pubsonline.informs.org/doi/abs/10.1287/opre.1090.0718','Competitor strategy changes the value of pricing/inventory decisions','Include opponent exposure as strategic externality in sell/hold threshold','Withholding is only valuable when rival cannot capture the same price lift','IMPLEMENTED',?,?),\n ('M-RACING','METHOD','RESEARCH','Best arm identification / racing','https://link.springer.com/article/10.1007/s10489-021-02719-2','Adaptive allocation eliminates weak candidates and spends samples on uncertain contenders','Replace exhaustive seed sweeps with resumable sequential races','Adaptive racing reduces simulation cost without promoting obvious losers','IMPLEMENTED',?,?)`,args:[now,now,now,now,now,now,now,now,now,now]}\n]);\nconst tables=await sqlite.execute(`SELECT name FROM sqlite_master WHERE type='table' AND name LIKE 'kag_%' ORDER BY name`);\nconst claims=await sqlite.execute(`SELECT claim_id,track,status FROM kag_research_claims ORDER BY claim_id`);\nconsole.log(JSON.stringify({status:'PASS',tables:tables.rows,claims:claims.rows},null,2));\n",[389],"9eed7f5f-9afe-4e17-8c0b-b1d15b65747c","kaggriculture_k1_diagnostic.ts","a031b828-aa37-11f1-91ab-1607ee4eb77e",23,["D",1788729131171],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { K1, STARTER } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst E = await loadOfficialKaggricultureEngine();\nconst seed = 11;\nconst cfg = E.state.resolveConfig({ seed });\nlet state = E.state.initGameState(2, cfg, seed);\nconst ledger = { K1: { hireOrders:0, seedQty:0, sellQty:0, moves:0, work:0, pass:0 }, STARTER: { hireOrders:0, seedQty:0, sellQty:0, moves:0, work:0, pass:0 } };\nconst daily: any[] = [];\n\nfunction scan(name: \"K1\"|\"STARTER\", a: any) {\n const l = ledger[name];\n for (const m of (a.market ?? [])) {\n if (m?.[0] === \"HIRE\") l.hireOrders++;\n if (m?.[0] === \"BUY_SEED\" && m?.[1] === \"CARROT\") l.seedQty += Number(m?.[2] ?? 0);\n if (m?.[0] === \"SELL\" && m?.[1] === \"CARROT\") l.sellQty += Number(m?.[2] ?? 0);\n }\n for (const u of [a.farmer ?? [\"PASS\"], ...(a.hands ?? [])]) {\n const op=String(u?.[0] ?? \"PASS\");\n if ([\"NORTH\",\"SOUTH\",\"EAST\",\"WEST\"].includes(op)) l.moves++;\n else if (op === \"PASS\") l.pass++;\n else l.work++;\n }\n}\n\nfunction tileCounts(farm:any) {\n const out:any={empty:0,weed:0,carrot:0,other:0};\n for(const row of farm.tiles) for(const t of row){\n if(t===null) out.empty++;\n else if(t===\"LOCKED\") continue;\n else if(t?.kind===\"WEED\") out.weed++;\n else if(t?.kind===\"PLANT\"&&t?.crop===\"CARROT\") out.carrot++;\n else out.other++;\n }\n return out;\n}\n\nwhile(!state.done){\n const a0=K1(observationFor(state,0));\n const a1=STARTER(observationFor(state,1));\n scan(\"K1\",a0); scan(\"STARTER\",a1);\n state=E.interpreter.step(state,[a0,a1],cfg);\n if(state.hour===0 || state.done){\n daily.push({\n step:state.step,day:state.day,\n bank:[state.farms[0].money,state.farms[1].money],\n carrotPrice:state.market.prices.CARROT,\n carrotInventory:state.market.inventory.CARROT,\n k1ShedCarrot:state.privates[0].shed.CARROT,\n k1Seeds:state.privates[0].seeds.CARROT,\n k1Tiles:tileCounts(state.farms[0]),\n shops:[...state.town.unlocked_shops],\n });\n }\n}\nconsole.log(JSON.stringify({status:\"PASS\",seed,finalBanks:state.farms.map((f:any)=>f.money),ledger,daily},null,2));\n",[396],"442c1080-d81c-4e09-a79b-5451642fa55f","kaggriculture_k10_opponent_gate_benchmark_v1.ts","2705ff5c-aa39-11f1-b1e4-1607ee4eb77e",38,["D",1788729786939],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\nimport { withSellPolicy, AFTER_TOWN_HOURS } from \"./lib/kaggriculture_market_mutations.ts\";\nimport { opponentAwareCarrotMarket } from \"./lib/kaggriculture_opponent_market.ts\";\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst factory=()=>buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:true,seedBuffer:15});\nconst BASE=factory();const RESERVE=withSellPolicy(factory(),{name:\"R60\",allowedHours:AFTER_TOWN_HOURS,lotSize:8,reservePrice:60,forceShedLoad:85,liquidationDay:29});\nconst agents:Record={BASE,RESERVE,G2:opponentAwareCarrotMarket(factory,2),G3:opponentAwareCarrotMarket(factory,3),G5:opponentAwareCarrotMarket(factory,5),STARTER};\nconst seeds=Array.from({length:20},(_,i)=>5003+i*53);\nconst challengerNames=['RESERVE','G2','G3','G5'];const opponents=['BASE','STARTER'];\nasync function play(a:string,b:string,seed:number){const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);while(!s.done)s=E.interpreter.step(s,[agents[a](observationFor(s,0)),agents[b](observationFor(s,1))],cfg);return {a,b,ba:s.farms[0].money,bb:s.farms[1].money};}\nconst games:any[]=[];for(const c of challengerNames)for(const o of opponents)for(const seed of seeds){games.push(await play(c,o,seed));games.push(await play(o,c,seed));}\nconst avg=(x:number[])=>x.reduce((a,b)=>a+b,0)/(x.length||1);const summary:any={};\nfor(const c of challengerNames){summary[c]={};for(const o of opponents){const rows=games.filter(g=>(g.a===c&&g.b===o)||(g.a===o&&g.b===c)).map(g=>g.a===c?{bank:g.ba,opp:g.bb}:{bank:g.bb,opp:g.ba});summary[c][o]={episodes:rows.length,wins:rows.filter(r=>r.bank>r.opp).length,ties:rows.filter(r=>r.bank===r.opp).length,winRate:rows.filter(r=>r.bank>r.opp).length/rows.length,avgBank:avg(rows.map(r=>r.bank)),avgMargin:avg(rows.map(r=>r.bank-r.opp))};}}\nconsole.log(JSON.stringify({status:'PASS',evidenceState:'OPPONENT_EXPOSURE_GATE_SCREEN_OFFICIAL_TS_PORT',seeds,summary},null,2));",[403],"90523511-0d25-4598-9e86-a65985e604ff","kaggriculture_k10_market_benchmark_v1.ts","0e16571c-aa39-11f1-b2b1-1607ee4eb77e",36,["D",1788729745125],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\nimport { withSellPolicy, AFTER_TOWN_HOURS } from \"./lib/kaggriculture_market_mutations.ts\";\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst makeBase=()=>buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:true,seedBuffer:15});\nconst BASE=makeBase();const K10=withSellPolicy(makeBase(),{name:\"K10_FLOOR60_AFTER\",allowedHours:AFTER_TOWN_HOURS,lotSize:8,reservePrice:60,forceShedLoad:85,liquidationDay:29});\nconst agents:Record={BASE,K10,STARTER};\nconst seeds=Array.from({length:30},(_,i)=>1001+i*37);\nconst pairs:Array<[string,string]>=[[\"K10\",\"BASE\"],[\"BASE\",\"K10\"],[\"K10\",\"STARTER\"],[\"STARTER\",\"K10\"],[\"BASE\",\"STARTER\"],[\"STARTER\",\"BASE\"]];\nasync function play(a:string,b:string,seed:number){const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);while(!s.done)s=E.interpreter.step(s,[agents[a](observationFor(s,0)),agents[b](observationFor(s,1))],cfg);return {a,b,seed,ba:s.farms[0].money,bb:s.farms[1].money,winner:s.farms[0].money===s.farms[1].money?\"TIE\":s.farms[0].money>s.farms[1].money?a:b,shops:[...s.town.unlocked_shops]};}\nconst games=[];for(const seed of seeds)for(const [a,b] of pairs)games.push(await play(a,b,seed));\nconst avg=(x:number[])=>x.reduce((a,b)=>a+b,0)/(x.length||1);const summary:any={};\nfor(const name of Object.keys(agents)){const r:any[]=[];for(const g of games){if(g.a===name)r.push({bank:g.ba,opp:g.bb,win:g.ba>g.bb,tie:g.ba===g.bb});if(g.b===name)r.push({bank:g.bb,opp:g.ba,win:g.bb>g.ba,tie:g.bb===g.ba});}summary[name]={episodes:r.length,wins:r.filter(x=>x.win).length,ties:r.filter(x=>x.tie).length,losses:r.filter(x=>!x.win&&!x.tie).length,winRate:r.filter(x=>x.win).length/r.length,avgBank:avg(r.map(x=>x.bank)),avgMargin:avg(r.map(x=>x.bank-x.opp))};}\nconst h2h=games.filter(g=>(g.a==='K10'&&g.b==='BASE')||(g.a==='BASE'&&g.b==='K10'));const k10h=h2h.map(g=>g.a==='K10'?{bank:g.ba,opp:g.bb,win:g.ba>g.bb,tie:g.ba===g.bb}:{bank:g.bb,opp:g.ba,win:g.bb>g.ba,tie:g.bb===g.ba});\nconsole.log(JSON.stringify({status:'PASS',evidenceState:'K10_NATURAL_SHOP_SCREEN_OFFICIAL_TS_PORT',seeds,pairCount:games.length,summary,h2hK10vsBase:{episodes:k10h.length,wins:k10h.filter(x=>x.win).length,ties:k10h.filter(x=>x.tie).length,losses:k10h.filter(x=>!x.win&&!x.tie).length,winRate:k10h.filter(x=>x.win).length/k10h.length,avgBank:avg(k10h.map(x=>x.bank)),avgMargin:avg(k10h.map(x=>x.bank-x.opp))}},null,2));",[410],"d5944d8b-b305-47c6-a559-0efea817fb65","kaggriculture_herd_mix_telemetry_v1.ts","8b957950-aa40-11f1-9f75-1607ee4eb77e",58,["D",1788732996656],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\n\nconst seed=9403;\nconst variants:Record={\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n};\nconst E=await loadOfficialKaggricultureEngine(); const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');\nif(!zr.ok)throw new Error(`REF_DATASET_HTTP_${zr.status}`);\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer())); const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide(); py.runPython(`import json\\n_REG={}`); py.globals.set('src',src);\nfor(const [name,patch] of Object.entries(variants)){\n py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));\n py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n['agent']`);\n}\npy.runPython(`def call(name,payload):\\n return json.dumps(_REG[name](json.loads(payload)))`); const call=py.globals.get('call');\n\nfunction animalCounts(farm:any){\n const out:any={COW:0,SHEEP:0,GOOSE:0,PASTURE:0,COOP:0};\n for(const row of farm?.tiles??[])for(const t of row??[]){\n if(!t||typeof t!=='object')continue;\n const a=String(t.animal??t.species??t.animal_type??'');\n if(a in out)out[a]++;\n const k=String(t.kind??''); if(k==='PASTURE')out.PASTURE++; if(k==='COOP')out.COOP++;\n }\n return out;\n}\nfunction snapObs(obs:any){\n const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};\n return {\n money:Number(f.money??0), hands:(f.hands??[]).length, land:(f.unlocked_quadrants??[]).length,\n animals:animalCounts(f), shed:{...(obs?.private?.shed??{})}, seeds:{...(obs?.private?.seeds??{})},\n };\n}\nfunction aggOrder(a:any,acc:any){\n for(const o of a?.market??[]){if(!Array.isArray(o)||!o.length)continue;const op=String(o[0]),item=String(o[1]??''),qty=Number(o[2]??1);const k=item?`${op}:${item}`:op;acc[k]=(acc[k]??0)+qty;}\n}\nfunction unitOps(a:any,acc:any){for(const u of [a?.farmer??['PASS'],...(a?.hands??[])]){const op=String(u?.[0]??'PASS');acc[op]=(acc[op]??0)+1;}}\n\nasync function play(aName:string,bName:string){\n const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);let errors=0;\n const T:any={}; for(const n of [aName,bName])T[n]={minCash:Infinity,maxCash:-Infinity,market:{},unitOps:{},daily:[],events:[],pricePath:[]};\n let prev:any={};\n while(!s.done){\n const before=s;\n const acts:any[]=[]; const obs:any[]=[];\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n obs[pid]=observationFor(s,pid); const ss=snapObs(obs[pid]);\n T[n].minCash=Math.min(T[n].minCash,ss.money);T[n].maxCash=Math.max(T[n].maxCash,ss.money);\n try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs[pid]))));}catch(e){errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}\n aggOrder(acts[pid],T[n].market);unitOps(acts[pid],T[n].unitOps);\n }\n const day=s.day,hour=s.hour;\n if(hour===0){\n for(const [pid,n] of [[0,aName],[1,bName]] as any)T[n].daily.push({day,hour,before:snapObs(obs[pid]),marketPrice:{MILK:s.market.prices.MILK,WOOL:s.market.prices.WOOL,WHEAT:s.market.prices.WHEAT},marketInventory:{MILK:s.market.inventory.MILK,WOOL:s.market.inventory.WOOL,WHEAT:s.market.inventory.WHEAT},shops:[...s.town.unlocked_shops]});\n }\n s=E.interpreter.step(s,acts,cfg);\n if(hour===23){\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n const oo=observationFor(s,pid); const after=snapObs(oo);\n const rec=T[n].daily.find((x:any)=>x.day===day); if(rec)rec.after=after;\n }\n }\n // Record market trajectory at each shop unlock + every 3 days.\n if((s.hour===0 && s.day%3===0) || s.town.unlocked_shops.length!==(prev.shops??-1)){\n for(const n of [aName,bName])T[n].pricePath.push({day:s.day,hour:s.hour,MILK:s.market.prices.MILK,WOOL:s.market.prices.WOOL,WHEAT:s.market.prices.WHEAT,invMILK:s.market.inventory.MILK,invWOOL:s.market.inventory.WOOL,invWHEAT:s.market.inventory.WHEAT,shops:[...s.town.unlocked_shops]});\n prev.shops=s.town.unlocked_shops.length;\n }\n }\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n const oo=observationFor(s,pid);T[n].final=snapObs(oo);T[n].bank=s.farms[pid].money;T[n].opponentBank=s.farms[1-pid].money;T[n].margin=T[n].bank-T[n].opponentBank;\n }\n return {a:aName,b:bName,errors,telemetry:T,finalMarket:{prices:s.market.prices,inventory:s.market.inventory},shops:s.town.unlocked_shops};\n}\nconst g1=await play('C4S12','C6S10'); const g2=await play('C6S10','C4S12');\nfunction summarize(g:any){\n const out:any={};\n for(const n of ['C4S12','C6S10']){\n const t=g.telemetry[n];\n const d=t.daily;\n const minDay=[...d].sort((a:any,b:any)=>(a.after?.money??Infinity)-(b.after?.money??Infinity))[0];\n const firstWool=d.find((x:any)=>Number(x.after?.shed?.WOOL??0)>0);\n const firstMilk=d.find((x:any)=>Number(x.after?.shed?.MILK??0)>0);\n const firstCowTarget=d.find((x:any)=>Number(x.after?.animals?.COW??0)>=Number(variants[n].animal_target.COW));\n const firstSheepTarget=d.find((x:any)=>Number(x.after?.animals?.SHEEP??0)>=Number(variants[n].animal_target.SHEEP));\n const checkpoints=[0,4,6,8,10,12,15,18,21,24,27,29].map(day=>{const x=d.find((y:any)=>y.day===day);return x?{day,cash:x.after?.money,cows:x.after?.animals?.COW,sheep:x.after?.animals?.SHEEP,wheat:x.after?.shed?.WHEAT,milk:x.after?.shed?.MILK,wool:x.after?.shed?.WOOL}:null}).filter(Boolean);\n out[n]={bank:t.bank,margin:t.margin,minCash:t.minCash,minCashDay:minDay?.day,maxCash:t.maxCash,marketOrders:t.market,unitOps:t.unitOps,firstWoolInventoryDay:firstWool?.day??null,firstMilkInventoryDay:firstMilk?.day??null,cowTargetDay:firstCowTarget?.day??null,sheepTargetDay:firstSheepTarget?.day??null,checkpoints};\n }\n return out;\n}\nconst A=summarize(g1),B=summarize(g2);\nfunction seatNeutral(name:string){\n const x=[A[name],B[name]];\n return {avgBank:(x[0].bank+x[1].bank)/2,avgMargin:(x[0].margin+x[1].margin)/2,minCash:Math.min(x[0].minCash,x[1].minCash),seatBanks:x.map(y=>y.bank),seatMargins:x.map(y=>y.margin),marketOrders:x.map(y=>y.marketOrders),targetDays:x.map(y=>({cow:y.cowTargetDay,sheep:y.sheepTargetDay})),cashCheckpoints:x.map(y=>y.checkpoints)};\n}\nconsole.log(JSON.stringify({status:'PASS',seed,seatNeutral:{C4S12:seatNeutral('C4S12'),C6S10:seatNeutral('C6S10')},seatA:A,seatB:B,shops:g1.shops,caveat:'Official TS port + Pyodide public MIT Rancher Rita policy. Only animal_target differs.'},null,2));\n",[417],"df6ccd57-bff2-4952-8376-34cacfdadace","kaggriculture_herd_mix_telemetry_detail_v1.ts","01a078cb-4c07-74ba-b128-3085fcd62e67",57,["D",1788732984329],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\n\nconst seed=9403;\nconst variants:Record={\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n};\nconst E=await loadOfficialKaggricultureEngine(); const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');\nif(!zr.ok)throw new Error(`REF_DATASET_HTTP_${zr.status}`);\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer())); const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide(); py.runPython(`import json\\n_REG={}`); py.globals.set('src',src);\nfor(const [name,patch] of Object.entries(variants)){\n py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));\n py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n['agent']`);\n}\npy.runPython(`def call(name,payload):\\n return json.dumps(_REG[name](json.loads(payload)))`); const call=py.globals.get('call');\n\nfunction animalCounts(farm:any){\n const out:any={COW:0,SHEEP:0,GOOSE:0,PASTURE:0,COOP:0};\n for(const row of farm?.tiles??[])for(const t of row??[]){\n if(!t||typeof t!=='object')continue;\n const a=String(t.animal??t.species??t.animal_type??'');\n if(a in out)out[a]++;\n const k=String(t.kind??''); if(k==='PASTURE')out.PASTURE++; if(k==='COOP')out.COOP++;\n }\n return out;\n}\nfunction snapObs(obs:any){\n const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};\n return {\n money:Number(f.money??0), hands:(f.hands??[]).length, land:(f.unlocked_quadrants??[]).length,\n animals:animalCounts(f), shed:{...(obs?.private?.shed??{})}, seeds:{...(obs?.private?.seeds??{})},\n };\n}\nfunction aggOrder(a:any,acc:any){\n for(const o of a?.market??[]){if(!Array.isArray(o)||!o.length)continue;const op=String(o[0]),item=String(o[1]??''),qty=Number(o[2]??1);const k=item?`${op}:${item}`:op;acc[k]=(acc[k]??0)+qty;}\n}\nfunction unitOps(a:any,acc:any){for(const u of [a?.farmer??['PASS'],...(a?.hands??[])]){const op=String(u?.[0]??'PASS');acc[op]=(acc[op]??0)+1;}}\n\nasync function play(aName:string,bName:string){\n const cfg={...cfg0,seed};let s=E.state.initGameState(2,cfg,seed);let errors=0;\n const T:any={}; for(const n of [aName,bName])T[n]={minCash:Infinity,maxCash:-Infinity,market:{},unitOps:{},daily:[],events:[],pricePath:[]};\n let prev:any={};\n while(!s.done){\n const before=s;\n const acts:any[]=[]; const obs:any[]=[];\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n obs[pid]=observationFor(s,pid); const ss=snapObs(obs[pid]);\n T[n].minCash=Math.min(T[n].minCash,ss.money);T[n].maxCash=Math.max(T[n].maxCash,ss.money);\n try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs[pid]))));}catch(e){errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}\n aggOrder(acts[pid],T[n].market);unitOps(acts[pid],T[n].unitOps);\n }\n const day=s.day,hour=s.hour;\n if(hour===0){\n for(const [pid,n] of [[0,aName],[1,bName]] as any)T[n].daily.push({day,hour,before:snapObs(obs[pid]),marketPrice:{MILK:s.market.prices.MILK,WOOL:s.market.prices.WOOL,WHEAT:s.market.prices.WHEAT},marketInventory:{MILK:s.market.inventory.MILK,WOOL:s.market.inventory.WOOL,WHEAT:s.market.inventory.WHEAT},shops:[...s.town.unlocked_shops]});\n }\n s=E.interpreter.step(s,acts,cfg);\n if(hour===23){\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n const oo=observationFor(s,pid); const after=snapObs(oo);\n const rec=T[n].daily.find((x:any)=>x.day===day); if(rec)rec.after=after;\n }\n }\n // Record market trajectory at each shop unlock + every 3 days.\n if((s.hour===0 && s.day%3===0) || s.town.unlocked_shops.length!==(prev.shops??-1)){\n for(const n of [aName,bName])T[n].pricePath.push({day:s.day,hour:s.hour,MILK:s.market.prices.MILK,WOOL:s.market.prices.WOOL,WHEAT:s.market.prices.WHEAT,invMILK:s.market.inventory.MILK,invWOOL:s.market.inventory.WOOL,invWHEAT:s.market.inventory.WHEAT,shops:[...s.town.unlocked_shops]});\n prev.shops=s.town.unlocked_shops.length;\n }\n }\n for(const [pid,n] of [[0,aName],[1,bName]] as any){\n const oo=observationFor(s,pid);T[n].final=snapObs(oo);T[n].bank=s.farms[pid].money;T[n].opponentBank=s.farms[1-pid].money;T[n].margin=T[n].bank-T[n].opponentBank;\n }\n return {a:aName,b:bName,errors,telemetry:T,finalMarket:{prices:s.market.prices,inventory:s.market.inventory},shops:s.town.unlocked_shops};\n}\nconst g1=await play('C4S12','C6S10'); const g2=await play('C6S10','C4S12');\nfunction compact(g:any){const out:any={};for(const n of ['C4S12','C6S10']){const t=g.telemetry[n];out[n]={bank:t.bank,margin:t.margin,minCash:t.minCash,maxCash:t.maxCash,market:t.market,unitOps:t.unitOps,daily:t.daily.map((d:any)=>({day:d.day,cash0:d.before.money,cash24:d.after?.money,hands:d.after?.hands,land:d.after?.land,animals:d.after?.animals,shed:d.after?.shed,prices:d.marketPrice,shops:d.shops}))};}return out;}\nconsole.log(JSON.stringify({status:'PASS',seed,seatA:compact(g1),seatB:compact(g2),shops:g1.shops,finalMarket:g1.finalMarket,caveat:'Telemetry derives from official TS port + Pyodide execution of the public MIT Rancher Rita policy with only animal_target mutated.'},null,2));\n",[424],"85c0fee9-2170-4b0f-9bbc-5a87da87b689","kaggriculture_dynport_register_v1.ts","47634b7a-aa42-11f1-ae55-1607ee4eb77e",75,["D",1788733706729],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nconst now=new Date().toISOString();\nawait sqlite.batch([\n {sql:`INSERT OR REPLACE INTO kag_league_members(member_id,role,lineage,frozen,status,source,evidence_state,created_at,updated_at) VALUES(?,?,?,?,?,?,?,?,?)`,args:['DYN_PORT_V1','SPECIALIST','RITA→DYN_PORT_V1',1,'CHALLENGER','research-derived closed-loop livestock portfolio','SMALL_MIRRORED_SCREEN_10_OF_12',now,now]},\n {sql:`INSERT OR REPLACE INTO kag_strategy_lessons(lesson_id,lesson_type,mechanism,preconditions,counterfactual,detector,evidence_state,created_at,updated_at) VALUES(?,?,?,?,?,?,?,?,?)`,args:['FAIL-TARGET-RATCHET','FAILURE','TARGET_RATCHET_WITHOUT_EXECUTION','planner changes desired asset count while prior purchase remains unexecuted','rebase desired target on actual committed/owned assets each macro cycle','desired_target - actual_owned grows across cycles without a matching purchase receipt','FALSIFIED_IN_SIM',now,now]},\n {sql:`INSERT OR REPLACE INTO kag_strategy_lessons(lesson_id,lesson_type,mechanism,preconditions,counterfactual,detector,evidence_state,created_at,updated_at) VALUES(?,?,?,?,?,?,?,?,?)`,args:['FAIL-NPV-FINANCE','FAILURE','POSITIVE_NPV_NOT_FINANCIALLY_FEASIBLE','asset scorer ignores feed float, land reserve or working-capital constraint','require scheduler-equivalent financeability gate before ranking as actionable','NPV>0 AND cash={\n DYN_PORT:{animal_target:{COW:0,SHEEP:0}},\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n RITA_BASE:{},\n};\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zr.ok)throw new Error(String(zr.status));\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);\nfor(const [name,patch] of Object.entries(patches)){py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}\npy.runPython(`\ndef call(name,payload):\n return json.dumps(_REG[name]['agent'](json.loads(payload)))\ndef set_herd(name,cows,sheep,order):\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\n _REG[name]['POLICY']['animals']=json.loads(order)\ndef reset(name):\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\n`);\nconst call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\n\nfunction countOwned(obs:any,animal:string){const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};let n=Number(obs?.private?.shed?.[animal]??0);for(const inv of obs?.private?.inventories??[])n+=Number(inv?.[animal]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===animal)n++;return n;}\nfunction enforceAnimalTargets(obs:any,action:any,targets:{COW:number;SHEEP:number}){const actual:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const out={...action,market:[] as any[]};for(const order of action?.market??[]){if(Array.isArray(order)&&order[0]==='BUY_ANIMAL'&&(order[1]==='COW'||order[1]==='SHEEP')){const a=order[1] as 'COW'|'SHEEP';const allowed=Math.max(0,Math.min(Number(order[2]??1),targets[a]-actual[a]));if(allowed>0){out.market.push(['BUY_ANIMAL',a,allowed]);actual[a]+=allowed;}}else out.market.push(order);}return out;}\nasync function play(a:string,b:string,seed:number){\n reset(a);reset(b);let s=E.state.initGameState(2,{...cfg0,seed},seed);let errors=0;let targets={COW:0,SHEEP:0};const decisions:any[]=[];\n while(!s.done){const acts:any[]=[];\n for(const [pid,n] of [[0,a],[1,b]] as any){const obs=observationFor(s,pid);\n if(n==='DYN_PORT'&&Number(obs.hour)===0){\n const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};\n // An unexecuted target is a revocable option, not committed capital. Rebase intent on actual scheduler-visible ownership every macro cycle.\n targets={COW:owned.COW,SHEEP:owned.SHEEP};\n const actualTotal=owned.COW+owned.SHEEP;const choice=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:1.0});\n if(actualTotal<16 && choice.choice){const room=16-actualTotal,batch=Math.min(2,room);targets[choice.choice]+=batch;}\n const order=[...choice.ranking].map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP');\n setHerd('DYN_PORT',targets.COW,targets.SHEEP,JSON.stringify(order));\n decisions.push({day:obs.day,player:pid,money:obs.farms[pid].money,owned,targets:{...targets},choice:choice.choice,ranking:choice.ranking.map(x=>({animal:x.animal,net:Math.round(x.net),roi:Number(x.roi.toFixed(2)),currentPrice:x.currentPrice,projectedPrice:x.projectedPrice,townDemand:Number(x.townDemand.toFixed(1)),ownSupply:x.ownCommittedSupply,oppSupply:x.opponentSupply,liquidityPenalty:x.liquidityPenalty}))});\n }\n try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN_PORT')acts[pid]=enforceAnimalTargets(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}\n }\n s=E.interpreter.step(s,acts,{...cfg0,seed});\n }\n return{a,b,seed,bankA:s.farms[0].money,bankB:s.farms[1].money,errors,decisions};\n}\nconst games:any[]=[];for(const opp of opponents)for(const seed of seeds){games.push(await play('DYN_PORT',opp,seed));games.push(await play(opp,'DYN_PORT',seed));}\nconst summary:any={};for(const opp of opponents){const r=games.filter(g=>g.a===opp||g.b===opp).map(g=>g.a==='DYN_PORT'?{ours:g.bankA,opp:g.bankB,e:g.errors}:{ours:g.bankB,opp:g.bankA,e:g.errors});summary[opp]={episodes:r.length,wins:r.filter(x=>x.ours>x.opp).length,losses:r.filter(x=>x.oursx.ours===x.opp).length,avgBank:r.reduce((s,x)=>s+x.ours,0)/r.length,avgMargin:r.reduce((s,x)=>s+x.ours-x.opp,0)/r.length,errors:r.reduce((s,x)=>s+x.e,0)};}\nconst decisionDigest=games.filter(g=>g.a==='DYN_PORT').map(g=>({opponent:g.b,seed:g.seed,first12:g.decisions.slice(0,12),finalDecision:g.decisions[g.decisions.length-1]}));\nconsole.log(JSON.stringify({status:'PASS',agent:'DYN_PORT',mechanism:'GREEDY_MARGINAL_LIVESTOCK_PORTFOLIO_WITH_EVENT_DAILY_REALLOCATION',seeds,summary,decisionDigest,caveat:'Research prototype. Uses an NPV-like heuristic, not a proven optimal policy; requires ablation and broader league evaluation.'},null,2));",[438],"0525c8ee-d719-4cdd-b18a-4d1bd5c33d95","kaggriculture_demand_thresholds_v1.ts","080e77ba-aa38-11f1-89da-1607ee4eb77e",27,["D",1788729305458],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\nconst E=await loadOfficialKaggricultureEngine();\nconst variants:Record={\n H4_T10:buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:true,seedBuffer:15}),\n H6_T12:buildAgent({crop:\"CARROT\",targetHands:6,maxTiles:12,persistent:true,seedBuffer:18}),\n H8_T16:buildAgent({crop:\"CARROT\",targetHands:8,maxTiles:16,persistent:true,seedBuffer:22}),\n H10_T25:buildAgent({crop:\"CARROT\",targetHands:10,maxTiles:25,persistent:true,seedBuffer:30}),\n};\nconst worlds:Record={D1:[],D7:[\"FARMERS_MARKET\"],D13:[\"PET_CAFE\"],D19:[\"PET_CAFE\",\"FARMERS_MARKET\"],D25:[\"PET_CAFE\",\"PET_CAFE\"],D31:[\"PET_CAFE\",\"PET_CAFE\",\"FARMERS_MARKET\"],D37:[\"PET_CAFE\",\"PET_CAFE\",\"PET_CAFE\"]};\nasync function play(agent:AgentFn,shops:string[]){const cfg=E.state.resolveConfig({seed:999,weedSpawnChance:0,townShopUnlockInterval:9999});let s=E.state.initGameState(2,cfg,999);s.town.unlocked_shops=[...shops];while(!s.done){s=E.interpreter.step(s,[agent(observationFor(s,0)),STARTER(observationFor(s,1))],cfg);}return {bank:s.farms[0].money,starter:s.farms[1].money,margin:s.farms[0].money-s.farms[1].money,price:s.market.prices.CARROT,inventory:s.market.inventory.CARROT};}\nconst out:any={};for(const [world,shops] of Object.entries(worlds)){const rows=[];for(const [variant,a] of Object.entries(variants))rows.push({variant,...await play(a,shops)});rows.sort((x,y)=>y.margin-x.margin);out[world]={shops,rank:rows};}\nconsole.log(JSON.stringify({status:\"PASS\",evidenceState:\"CONTROLLED_CARROT_DEMAND_THRESHOLD_MAP\",sinkFormula:\"1 + 12*PET_CAFE + 6*FARMERS_MARKET units/day\",out},null,2));\n",[446],"f784c391-fa5d-4231-939d-1ba6e0e1b30e","kaggriculture_demand_control_v1.ts","dab53ba0-aa37-11f1-b30e-1607ee4eb77e",26,["D",1788729252852],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { buildAgent, K0, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst E=await loadOfficialKaggricultureEngine();\nconst variants:Record={\n K0,\n R2_H2_T6:buildAgent({crop:\"CARROT\",targetHands:2,maxTiles:6,persistent:true,seedBuffer:10}),\n R3_H3_T8:buildAgent({crop:\"CARROT\",targetHands:3,maxTiles:8,persistent:true,seedBuffer:12}),\n R4_H4_T10:buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:true,seedBuffer:15}),\n R4NP_H4_T10:buildAgent({crop:\"CARROT\",targetHands:4,maxTiles:10,persistent:false,seedBuffer:15}),\n R5_H6_T12:buildAgent({crop:\"CARROT\",targetHands:6,maxTiles:12,persistent:true,seedBuffer:18}),\n R7_H10_T25:buildAgent({crop:\"CARROT\",targetHands:10,maxTiles:25,persistent:true,seedBuffer:30}),\n};\nconst worlds:Record={\n LOW:[],\n MID_FARMERS:[\"FARMERS_MARKET\"],\n HIGH_PET:[\"PET_CAFE\"],\n VERY_HIGH:[\"PET_CAFE\",\"PET_CAFE\",\"FARMERS_MARKET\"],\n};\n\nfunction stats(){return {unit:0,move:0,pass:0,work:0};}\nfunction count(s:any,a:any){for(const u of [a?.farmer??[\"PASS\"],...(a?.hands??[])]){s.unit++;const op=String(u?.[0]??\"PASS\");if([\"NORTH\",\"SOUTH\",\"EAST\",\"WEST\"].includes(op))s.move++;else if(op===\"PASS\")s.pass++;else s.work++;}}\nasync function play(agent:AgentFn,shops:string[]){\n const cfg=E.state.resolveConfig({seed:424242,weedSpawnChance:0,townShopUnlockInterval:9999});\n let state=E.state.initGameState(2,cfg,424242); state.town.unlocked_shops=[...shops]; const s=stats();\n while(!state.done){const a=agent(observationFor(state,0)),b=STARTER(observationFor(state,1));count(s,a);state=E.interpreter.step(state,[a,b],cfg);}\n return {bank:state.farms[0].money,starterBank:state.farms[1].money,margin:state.farms[0].money-state.farms[1].money,finalPrice:state.market.prices.CARROT,finalInventory:state.market.inventory.CARROT,moveRate:s.move/s.unit,passRate:s.pass/s.unit,workRate:s.work/s.unit};\n}\nconst rows:any[]=[];\nfor(const [world,shops] of Object.entries(worlds))for(const [variant,agent] of Object.entries(variants))rows.push({world,shops,variant,...await play(agent,shops)});\nconst byWorld:any={};\nfor(const world of Object.keys(worlds))byWorld[world]=rows.filter(r=>r.world===world).sort((a,b)=>b.margin-a.margin||b.bank-a.bank);\nconst compact=Object.fromEntries(Object.entries(byWorld).map(([world,rows]:any)=>[world,{top3:rows.slice(0,3).map((r:any)=>({variant:r.variant,bank:r.bank,margin:r.margin,finalPrice:r.finalPrice,finalInventory:r.finalInventory,moveRate:r.moveRate})),R7:rows.find((r:any)=>r.variant===\"R7_H10_T25\"),K0:rows.find((r:any)=>r.variant===\"K0\")} ]));\nconsole.log(JSON.stringify({status:\"PASS\",evidenceState:\"CONTROLLED_DEMAND_ABLATION_OFFICIAL_TS_PORT\",config:{seed:424242,weedSpawnChance:0,townShopUnlockInterval:9999},compact},null,2));\n",[453],"565c3d43-035c-4f4f-b624-8261d09ef0e8","kaggriculture_config_probe_v1.ts","e3916fce-aa40-11f1-bb9f-1607ee4eb77e",59,["D",1788733109760],"import { loadOfficialKaggricultureEngine } from './lib/kaggriculture_engine_loader.ts';\nconst E=await loadOfficialKaggricultureEngine(); const c=E.state.resolveConfig();\nconsole.log(JSON.stringify({status:'PASS',config:c},null,2));",[460],"568fe673-8bee-4941-b72d-6e04ec879d9b","kaggriculture_benchmark_g0_v1.ts","83c5465a-aa37-11f1-8f9e-1607ee4eb77e",22,["D",1788729083534],"import { loadOfficialKaggricultureEngine, observationFor } from \"./lib/kaggriculture_engine_loader.ts\";\nimport { K0, K1, STARTER, type AgentFn } from \"./lib/kaggriculture_agents_v1.ts\";\n\nconst engine = await loadOfficialKaggricultureEngine();\nconst cfgBase = engine.state.resolveConfig();\n\nconst AGENTS: Record = { K0, K1, STARTER };\nconst SEEDS = [11, 23, 37, 53, 71];\nconst PAIRS: Array<[string,string]> = [\n [\"K0\", \"STARTER\"],\n [\"STARTER\", \"K0\"],\n [\"K1\", \"STARTER\"],\n [\"STARTER\", \"K1\"],\n [\"K1\", \"K0\"],\n [\"K0\", \"K1\"],\n];\n\nfunction freshStats() {\n return { unit: 0, move: 0, pass: 0, work: 0, marketOrders: 0, runtimeErrors: 0 };\n}\nfunction countAction(stats: any, action: any) {\n const units = [action?.farmer ?? [\"PASS\"], ...(Array.isArray(action?.hands) ? action.hands : [])];\n for (const u of units) {\n stats.unit++;\n const op = Array.isArray(u) && u.length ? String(u[0]) : \"PASS\";\n if ([\"NORTH\",\"SOUTH\",\"EAST\",\"WEST\"].includes(op)) stats.move++;\n else if (op === \"PASS\") stats.pass++;\n else stats.work++;\n }\n stats.marketOrders += Array.isArray(action?.market) ? action.market.length : 0;\n}\n\nasync function play(aName: string, bName: string, seed: number) {\n const cfg = { ...cfgBase, seed };\n let state = engine.state.initGameState(2, cfg, seed);\n const stats = [freshStats(), freshStats()];\n let turns = 0;\n while (!state.done) {\n const actions: any[] = [];\n for (let pid = 0; pid < 2; pid++) {\n const name = pid === 0 ? aName : bName;\n try {\n const action = AGENTS[name](observationFor(state, pid));\n actions.push(action);\n countAction(stats[pid], action);\n } catch (err) {\n stats[pid].runtimeErrors++;\n const pass = { farmer: [\"PASS\"], hands: [], market: [] };\n actions.push(pass);\n countAction(stats[pid], pass);\n }\n }\n state = engine.interpreter.step(state, actions, cfg);\n turns++;\n if (turns > 1000) throw new Error(`episode did not terminate seed=${seed}`);\n }\n const banks = state.farms.map((f: any) => Number(f.money));\n return {\n seed, aName, bName, turns, banks,\n winner: banks[0] === banks[1] ? \"TIE\" : banks[0] > banks[1] ? aName : bName,\n marginP0: banks[0] - banks[1],\n stats: stats.map((s: any) => ({\n ...s,\n moveRate: s.unit ? s.move / s.unit : 0,\n passRate: s.unit ? s.pass / s.unit : 0,\n workRate: s.unit ? s.work / s.unit : 0,\n })),\n };\n}\n\nconst games = [];\nfor (const seed of SEEDS) {\n for (const [a,b] of PAIRS) games.push(await play(a,b,seed));\n}\n\nconst summary: Record = {};\nfor (const name of Object.keys(AGENTS)) {\n const rows: any[] = [];\n for (const g of games as any[]) {\n if (g.aName === name) rows.push({ bank: g.banks[0], won: g.banks[0] > g.banks[1], tied: g.banks[0] === g.banks[1], stat: g.stats[0] });\n if (g.bName === name) rows.push({ bank: g.banks[1], won: g.banks[1] > g.banks[0], tied: g.banks[1] === g.banks[0], stat: g.stats[1] });\n }\n rows.sort((a,b)=>a.bank-b.bank);\n const n = rows.length;\n const avg = (xs: number[]) => xs.reduce((a,b)=>a+b,0)/(xs.length || 1);\n summary[name] = {\n games: n,\n wins: rows.filter(r=>r.won).length,\n ties: rows.filter(r=>r.tied).length,\n losses: rows.filter(r=>!r.won && !r.tied).length,\n winRate: rows.filter(r=>r.won).length/n,\n avgBank: avg(rows.map(r=>r.bank)),\n medianBank: n % 2 ? rows[Math.floor(n/2)].bank : (rows[n/2-1].bank+rows[n/2].bank)/2,\n minBank: rows[0]?.bank ?? null,\n maxBank: rows[n-1]?.bank ?? null,\n avgMoveRate: avg(rows.map(r=>r.stat.moveRate)),\n avgPassRate: avg(rows.map(r=>r.stat.passRate)),\n avgWorkRate: avg(rows.map(r=>r.stat.workRate)),\n runtimeErrors: rows.reduce((a,r)=>a+r.stat.runtimeErrors,0),\n };\n}\n\nconsole.log(JSON.stringify({\n status: \"PASS\",\n evidenceState: \"OFFICIAL_TYPESCRIPT_PORT_TESTED_RNG_NOT_PYTHON_BIT_PARITY\",\n seeds: SEEDS,\n pairingsPerSeed: PAIRS,\n gameCount: games.length,\n summary,\n games,\n caveat: \"Official Kaggle playable TypeScript interpreter is a port of kaggriculture.py, but its RNG seeding documents non-bit-identical stochastic parity with CPython. Treat these as strong mechanics/control tests, not exact Python replay parity.\",\n}, null, 2));\n",[467],"7c65030b-2ecd-4fb2-a11c-d4404cbe0b9b","kaggle_rita_capital_logic_exact.ts","3eefcc44-aa41-11f1-9650-1607ee4eb77e",66,["D",1788733263058],"import { unzipSync,strFromU8 } from 'npm:fflate';const r=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await r.arrayBuffer()));const s=strFromU8(z['rancher_rita.py']).split('\\n');console.log(s.slice(365,441).map((x,i)=>`${366+i}|${x}`).join('\\n'));",[474],"0dd746a7-6361-487a-925b-93a535daf6bf","kaggle_rita_animal_logic_probe.ts","2b81efa2-aa41-11f1-9bce-1607ee4eb77e",64,["D",1788733230456],"import { unzipSync,strFromU8 } from 'npm:fflate';\nconst r=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!r.ok)throw new Error(String(r.status));const z=unzipSync(new Uint8Array(await r.arrayBuffer()));const s=strFromU8(z['rancher_rita.py']);const lines=s.split('\\n');const hits:number[]=[];for(let i=0;i({line:i+1,text:lines.slice(Math.max(0,i-15),Math.min(lines.length,i+25)).map((x,j)=>`${Math.max(0,i-15)+j+1}|${x}`).join('\\n')}));console.log(JSON.stringify({status:'PASS',hits:hits.map(x=>x+1),ranges},null,2));",[481],"a1a50443-17e8-47e6-a3d4-e81d6f04fc68","kaggle_rita_animal_logic_exact.ts","3429dfde-aa41-11f1-ab5f-1607ee4eb77e",65,["D",1788733244974],"import { unzipSync,strFromU8 } from 'npm:fflate';const r=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await r.arrayBuffer()));const s=strFromU8(z['rancher_rita.py']).split('\\n');console.log(s.slice(440,485).map((x,i)=>`${441+i}|${x}`).join('\\n'));",[488],"66ba8c1f-293b-40e4-8438-0756b2c94ff9","kaggle_reference_policy_only.ts","922827d8-aa39-11f1-9c43-1607ee4eb77e",44,["D",1788729966698],"import { unzipSync,strFromU8 } from 'npm:fflate';\nconst r=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!r.ok)throw new Error(String(r.status));const z=unzipSync(new Uint8Array(await r.arrayBuffer()));const out:any={};for(const n of ['rotation_rosa.py','homestead_hana.py','melon_mateo.py','rancher_rita.py']){const s=strFromU8(z[n]);const a=s.indexOf('POLICY = '),b=s.indexOf('\\n\\n\\n#',a);out[n]=s.slice(a,b>0?b:a+5000);}console.log(JSON.stringify({status:'PASS',out},null,2));",[495],"f0e4e78d-ebca-42cc-9346-d227f7bd39c4","kaggle_reference_policy_extract.ts","80e39002-aa39-11f1-82f3-1607ee4eb77e",43,["D",1788729937723],"import { unzipSync, strFromU8 } from \"npm:fflate\";\nconst res=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!res.ok)throw new Error(String(res.status));const files=unzipSync(new Uint8Array(await res.arrayBuffer()));\nconst out:any={};for(const n of ['rotation_rosa.py','homestead_hana.py','melon_mateo.py','rancher_rita.py']){const src=strFromU8(files[n]);const lines=src.split(/\\r?\\n/);out[n]={head:lines.slice(0,180).join('\\n'),market:lines.slice(Math.max(0,lines.findIndex(l=>l.includes('def _plan_market'))),Math.max(0,lines.findIndex(l=>l.includes('def _plan_market')))+150).join('\\n')};}\nconsole.log(JSON.stringify({status:'PASS',out},null,2));",[502],"59fd3792-a66e-4c9b-8854-480075891c46","kaggle_reference_agents_audit.ts","4bf767de-aa38-11f1-a4ac-1607ee4eb77e",29,["D",1788729419450],"import { unzipSync, strFromU8 } from \"npm:fflate\";\n\nconst slug=\"raykkretzschmar/kaggriculture-reference-agents\";\nconst [zipRes,metaRes]=await Promise.all([\n fetch(`https://www.kaggle.com/api/v1/datasets/download/${slug}`),\n fetch(`https://www.kaggle.com/api/v1/datasets/view/${slug}`),\n]);\nif(!zipRes.ok) throw new Error(`zip ${zipRes.status}`);\nif(!metaRes.ok) throw new Error(`meta ${metaRes.status}`);\nconst meta=await metaRes.json();\nconst files=unzipSync(new Uint8Array(await zipRes.arrayBuffer()));\nconst names=Object.keys(files).sort();\nconst text=(name:string,max=6000)=>files[name]?strFromU8(files[name]).slice(0,max):null;\nconst py=names.filter(n=>n.endsWith('.py'));\nconst hashes:any={};\nfor(const n of py){const d=await crypto.subtle.digest('SHA-256',files[n]);hashes[n]=Array.from(new Uint8Array(d)).map(x=>x.toString(16).padStart(2,'0')).join('');}\nconsole.log(JSON.stringify({\n status:\"PASS\",\n metadata:{title:meta.title,subtitle:meta.subtitle,licenseName:meta.licenseName,ownerName:meta.ownerName,lastUpdated:meta.lastUpdated,datasetId:meta.id,versionNumber:meta.currentVersionNumber},\n zipBytes:Number(zipRes.headers.get('content-length')??0),\n fileCount:names.length,\n names,\n pythonHashes:hashes,\n manifest:text('agents_manifest.csv',10000),\n baselineLeague:text('baseline_league.csv',5000),\n readme:names.find(n=>/readme/i.test(n))?text(names.find(n=>/readme/i.test(n))!,10000):null,\n sampleHeaders:Object.fromEntries(py.map(n=>[n,text(n,1200)])),\n},null,2));",[509],"4546adee-4395-4e0d-9c83-bb1fbafd1aef","kaggle_reference_agent_structure.ts","5a9de1d2-aa38-11f1-a4ef-1607ee4eb77e",30,["D",1788729444028],"import { unzipSync, strFromU8 } from \"npm:fflate\";\nconst res=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!res.ok)throw new Error(String(res.status));const files=unzipSync(new Uint8Array(await res.arrayBuffer()));\nconst targets=['melon_mateo.py','rancher_rita.py','broker_bea.py','ledger_lena.py','slotter_silas.py','closer_cleo.py'];\nconst out:any={};\nfor(const name of targets){const src=strFromU8(files[name]);const lines=src.split(/\\r?\\n/);out[name]={bytes:files[name].length,lines:lines.length,defs:lines.filter(l=>/^def\\s+/.test(l)).map(l=>l.trim()),classes:lines.filter(l=>/^class\\s+/.test(l)).map(l=>l.trim()),constants:lines.filter(l=>/^[A-Z][A-Z0-9_]{2,}\\s*=/.test(l)).slice(0,50),comments:lines.filter(l=>/^#/.test(l)).slice(0,80)};}\nconsole.log(JSON.stringify({status:'PASS',out},null,2));",[516],"b586b96b-9e11-4e44-b5bf-043c3f4e453f","kaggle_public_dataset_probe.ts","3cb189d0-aa38-11f1-a244-1607ee4eb77e",28,["D",1788729393822],"const urls = [\n \"https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents\",\n \"https://www.kaggle.com/api/v1/datasets/download/dariushafshar/kaggriculture-engine-reference-tables\",\n];\nconst out=[];\nfor(const url of urls){\n const res=await fetch(url,{redirect:\"follow\"});\n const buf=await res.arrayBuffer();\n out.push({url,status:res.status,ok:res.ok,contentType:res.headers.get(\"content-type\"),contentLength:res.headers.get(\"content-length\"),finalUrl:res.url,bytes:buf.byteLength,head:Array.from(new Uint8Array(buf.slice(0,8)))});\n}\nconsole.log(JSON.stringify({status:out.every(x=>x.ok)?\"PASS\":\"PARTIAL\",out},null,2));",[523],"abac1049-43ae-43c3-b266-a6bc36ba6803","kag_world_regime_diag_v1.ts","9dc18f04-aa42-11f1-894c-1607ee4eb77e",81,["D",1788733851634],"import { loadOfficialKaggricultureEngine } from './lib/kaggriculture_engine_loader.ts';\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst seeds=[9403,9419,9431,9461,9491];const PASS={farmer:['PASS'],hands:[],market:[]};\nconst items=['WHEAT','CARROT','TOMATO','STRAWBERRY','MELON','EGG','MILK','WOOL'];const out:any[]=[];\nfor(const seed of seeds){let s=E.state.initGameState(2,{...cfg0,seed},seed);const unlocks:any[]=[];let last=0;while(!s.done){if(s.town.unlocked_shops.length!==last){unlocks.push({day:s.day,hour:s.hour,new:s.town.unlocked_shops.slice(last),all:[...s.town.unlocked_shops]});last=s.town.unlocked_shops.length;}s=E.interpreter.step(s,[PASS,PASS],{...cfg0,seed});}const counts:any={};for(const sh of s.town.unlocked_shops)counts[sh]=(counts[sh]??0)+1;const final:any={};for(const p of items)final[p]={demand:10000-s.market.inventory[p],price:s.market.prices[p]};out.push({seed,counts,unlocks,final});}\nconsole.log(JSON.stringify({status:'PASS',worlds:out},null,2));",[530],"3e488cd7-7742-499d-a2e2-5688c77b8853",["D",1788739831777],[28],"3016c188-82ae-448e-8b25-f71be72dc9a5","kag_recourse_vs_preemption_probe_v1.ts","8fa86e72-aa4e-11f1-b2f6-1607ee4eb77e",83,["D",1788738981936],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst variants=['PREEMPT','RECOURSE4','RECOURSE6'];\nconst seeds=[9403,9419,9431,9461,9491]; const opponents=['C4S12','C6S10','RITA_BASE'];\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zr.ok)throw new Error(String(zr.status));const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);const patches:Record={DYN:{animal_target:{COW:0,SHEEP:0}},C4S12:{animal_target:{COW:4,SHEEP:12}},C6S10:{animal_target:{COW:6,SHEEP:10}},RITA_BASE:{}};for(const [n,p] of Object.entries(patches)){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name):\\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction countOwned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:{COW:number;SHEEP:number}){const x:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1] as 'COW'|'SHEEP',q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction capFor(v:string,obs:any){if(v==='PREEMPT')return 16;const k=(obs.town?.unlocked_shops??[]).length;return Math.min(16,(v==='RECOURSE4'?4:6)+2*k);}\nasync function play(v:string,opp:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets={COW:0,SHEEP:0},errors=0;while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const total=owned.COW+owned.SHEEP,cap=capFor(v,obs);const c=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:0});if(totalx.animal).filter(x=>x==='COW'||x==='SHEEP')));}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,opp,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors};}\nconst games:any[]=[];for(const v of variants)for(const o of opponents)for(const seed of seeds){games.push(await play(v,o,seed,0));games.push(await play(v,o,seed,1));}\nconst summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,byOpponent:{}};for(const o of opponents){const xs=rs.filter(r=>r.opp===o);summary[v].byOpponent[o]={wins:xs.filter(r=>r.win).length,winRate:xs.filter(r=>r.win).length/xs.length,avgMargin:xs.reduce((a,r)=>a+r.margin,0)/xs.length};}}\nconst p=games.filter(g=>g.v==='PREEMPT');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgPairedMarginDelta:r.reduce((s,g,i)=>s+(g.margin-p[i].margin),0)/r.length,betterEpisodes:r.filter((g,i)=>g.margin>p[i].margin).length,worseEpisodes:r.filter((g,i)=>g.margin0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction lexChoice(obs:any,v:string){const r=rankAnimalInvestments(obs,{cashBuffer:400,strategicWeight:0}).filter(x=>x.animal==='COW'||x.animal==='SHEEP');const positive=r.filter(x=>x.financeable&&x.net>0);if(!positive.length)return{choice:null,ranking:r,switched:false};const best=positive[0];if(v==='PURE')return{choice:best.animal,ranking:r,switched:false};const band=best.net*(1-eps[v]);const eligible=positive.filter(x=>x.net>=band);eligible.sort((a,b)=>(a.rivalPriceImpact-b.rivalPriceImpact)||(b.net-a.net));return{choice:eligible[0].animal,ranking:r,switched:eligible[0].animal!==best.animal};}\nasync function play(v:string,opp:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0,switches=0;while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const total=owned.COW+owned.SHEEP,c=lexChoice(obs,v);if(total<16&&c.choice){targets[c.choice]+=Math.min(2,16-total);if(c.switched)switches++;}const order=[c.choice,...c.ranking.map(x=>x.animal)].filter((x,i,a)=>x&&(x==='COW'||x==='SHEEP')&&a.indexOf(x)===i);setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(order));}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,opp,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors,switches};}\nconst games:any[]=[];for(const v of variants)for(const o of opponents)for(const seed of seeds){games.push(await play(v,o,seed,0));games.push(await play(v,o,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,switches:rs.reduce((a,r)=>a+r.switches,0),byOpponent:{}};for(const o of opponents){const xs=rs.filter(r=>r.opp===o);summary[v].byOpponent[o]={wins:xs.filter(r=>r.win).length,winRate:xs.filter(r=>r.win).length/xs.length,avgMargin:xs.reduce((a,r)=>a+r.margin,0)/xs.length,switches:xs.reduce((a,r)=>a+r.switches,0)};}}const b=games.filter(g=>g.v==='PURE');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgMarginDelta:r.reduce((s,g,i)=>s+(g.margin-b[i].margin),0)/r.length,better:r.filter((g,i)=>g.margin>b[i].margin).length,worse:r.filter((g,i)=>g.margina+g.switches,0)};});console.log(JSON.stringify({status:'PASS',hypothesis:'HARM_RIVAL_ONLY_AS_SECONDARY_LEXICOGRAPHIC_TIEBREAKER_SHOULD_AVOID_SELF_DESTRUCTIVE_STRATEGIC_WEIGHTING',rule:'maximize own positive financeable NPV first; only within epsilon-band choose animal causing larger rival price damage',summary,paired},null,2));",[547],"cc122abf-ce35-4b78-a952-a65e99bbd61d","kag_initial_commitment_counterfactual_v1.ts","dbd2a276-aa4f-11f1-86a2-1607ee4eb77e",89,["D",1788739539181],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst variants=['BASE','COW2','SHEEP2','MIX11','WAIT3'];const seeds=[9403,9461,9491];const opp='RITA_BASE';const E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();const zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);for(const [n,p] of Object.entries({DYN:{animal_target:{COW:0,SHEEP:0}},RITA_BASE:{}})){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name):\\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction countOwned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:any){const x:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1],q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nasync function play(v:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0;const diary:any[]=[];while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};let order:string[]=[];if(+obs.day===0&&v!=='BASE'&&v!=='WAIT3'){if(v==='COW2'){targets.COW=2;order=['COW','SHEEP'];}if(v==='SHEEP2'){targets.SHEEP=2;order=['SHEEP','COW'];}if(v==='MIX11'){targets={COW:1,SHEEP:1};order=['SHEEP','COW'];}}else if(v==='WAIT3'&&+obs.day<3){order=['COW','SHEEP'];}else{const total=owned.COW+owned.SHEEP,c=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:0});if(total<16&&c.choice)targets[c.choice]+=Math.min(2,16-total);order=c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP') as string[];}setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(order));if([0,3,6,9,12,15,18].includes(+obs.day))diary.push({day:+obs.day,cash:obs.farms[pid].money,owned:{...owned},targets:{...targets},shops:[...(obs.town?.unlocked_shops??[])]});}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors,diary};}\nconst games:any[]=[];for(const v of variants)for(const seed of seeds){games.push(await play(v,seed,0));games.push(await play(v,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,bySeed:Object.fromEntries(seeds.map(seed=>{const x=rs.filter(r=>r.seed===seed);return[seed,{wins:x.filter(r=>r.win).length,avgMargin:x.reduce((a,r)=>a+r.margin,0)/x.length,avgBank:x.reduce((a,r)=>a+r.ours,0)/x.length}]}))};}const b=games.filter(g=>g.v==='BASE');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgMarginDelta:r.reduce((s,g,i)=>s+(g.margin-b[i].margin),0)/r.length,better:r.filter((g,i)=>g.margin>b[i].margin).length,worse:r.filter((g,i)=>g.marging.seed===9491&&g.seat===0).map(g=>({v:g.v,diary:g.diary}))},null,2));",[554],"f71c2a35-9d1c-4a6f-8cee-86616e05dd0d","kag_initial_action_shadow_probe_v1.ts","402a660a-aa50-11f1-b41f-1607ee4eb77e",90,["D",1788739707571],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();const r=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await r.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);for(const [n,p] of Object.entries({BASE:{animal_target:{COW:0,SHEEP:0}},COW2:{animal_target:{COW:2,SHEEP:0},animals:['COW','SHEEP']},SHEEP2:{animal_target:{COW:0,SHEEP:2},animals:['SHEEP','COW']},MIX11:{animal_target:{COW:1,SHEEP:1},animals:['SHEEP','COW']}})){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef reset(name): _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call');\nfunction owned(s:any,pid:number){const f=s.farms[pid];const c:any={COW:0,SHEEP:0};for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&(t.animal==='COW'||t.animal==='SHEEP'))c[t.animal]++;const pr=observationFor(s,pid)?.private;for(const a of ['COW','SHEEP']){c[a]+=Number(pr?.shed?.[a]??0);for(const inv of pr?.inventories??[])c[a]+=Number(inv?.[a]??0);}return c;}\nconst out:any={};for(const name of ['BASE','COW2','SHEEP2','MIX11']){let s=E.state.initGameState(2,{...cfg0,seed:9491},9491);const steps:any[]=[];for(let t=0;t<72;t++){const obs=observationFor(s,0);const act=JSON.parse(String(call(name,JSON.stringify(obs))));if(t<8||act.market?.some((x:any)=>x?.[0]==='BUY_ANIMAL'))steps.push({turn:t,day:s.day,hour:s.hour,money:s.farms[0].money,owned:owned(s,0),market:act.market});s=E.interpreter.step(s,[act,{farmer:['PASS'],hands:[],market:[]}],{...cfg0,seed:9491});}out[name]=steps;}console.log(JSON.stringify({status:'PASS',seed:9491,out},null,2));",[561],"e44842fa-fa97-46bb-8b6f-ac25e1677432","kag_first_commitment_persistent_v2.ts","57b8d1d0-aa50-11f1-b615-1607ee4eb77e",91,["D",1788739747088],[568],"a3e623f8-18d9-45ea-a31c-4a569c8edf57","kag_financial_flexibility_probe_v1.ts","f2e2e918-aa4e-11f1-8789-1607ee4eb77e",85,["D",1788739148386],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst variants=['BASE400','ACCEL0','FLEX100'];const seeds=[9403,9419,9431,9461,9491],opponents=['C4S12','C6S10','RITA_BASE'];\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();const zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);const patches:any={DYN:{animal_target:{COW:0,SHEEP:0}},C4S12:{animal_target:{COW:4,SHEEP:12}},C6S10:{animal_target:{COW:6,SHEEP:10}},RITA_BASE:{}};for(const [n,p] of Object.entries(patches)){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name):\\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction countOwned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:any){const x:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1],q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction bufferFor(v:string,obs:any){if(v==='ACCEL0')return +obs.day<8?0:400;if(v==='FLEX100'){const unseen=Math.max(0,8-(obs.town?.unlocked_shops??[]).length);return 400+100*unseen;}return 400;}\nasync function play(v:string,opp:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0;while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const total=owned.COW+owned.SHEEP;const c=choosePastureAnimal(obs,{cashBuffer:bufferFor(v,obs),strategicWeight:0});if(total<16&&c.choice)targets[c.choice]+=Math.min(2,16-total);setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP')));}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,opp,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors};}\nconst games:any[]=[];for(const v of variants)for(const o of opponents)for(const seed of seeds){games.push(await play(v,o,seed,0));games.push(await play(v,o,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,byOpponent:{}};for(const o of opponents){const xs=rs.filter(r=>r.opp===o);summary[v].byOpponent[o]={wins:xs.filter(r=>r.win).length,winRate:xs.filter(r=>r.win).length/xs.length,avgBank:xs.reduce((a,r)=>a+r.ours,0)/xs.length,avgMargin:xs.reduce((a,r)=>a+r.margin,0)/xs.length};}}const b=games.filter(g=>g.v==='BASE400');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgMarginDelta:r.reduce((s,g,i)=>s+(g.margin-b[i].margin),0)/r.length,better:r.filter((g,i)=>g.margin>b[i].margin).length,worse:r.filter((g,i)=>g.margin0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nfunction bufferFor(v:string,obs:any){if(v==='ACCEL0')return +obs.day<8?0:400;if(v==='FLEX100'){const unseen=Math.max(0,8-(obs.town?.unlocked_shops??[]).length);return 400+100*unseen;}return 400;}\nasync function play(v:string,opp:string,seed:number,seat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0},errors=0;while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===seat?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const total=owned.COW+owned.SHEEP;const c=choosePastureAnimal(obs,{cashBuffer:bufferFor(v,obs),strategicWeight:0});if(total<16&&c.choice)targets[c.choice]+=Math.min(2,16-total);setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP')));}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[seat].money,theirs=s.farms[1-seat].money;return{v,opp,seed,seat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors};}\nconst games:any[]=[];for(const v of variants)for(const o of opponents)for(const seed of seeds){games.push(await play(v,o,seed,0));games.push(await play(v,o,seed,1));}const summary:any={};for(const v of variants){const rs=games.filter(g=>g.v===v);summary[v]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length,byOpponent:{}};for(const o of opponents){const xs=rs.filter(r=>r.opp===o);summary[v].byOpponent[o]={wins:xs.filter(r=>r.win).length,winRate:xs.filter(r=>r.win).length/xs.length,avgBank:xs.reduce((a,r)=>a+r.ours,0)/xs.length,avgMargin:xs.reduce((a,r)=>a+r.margin,0)/xs.length};}}const b=games.filter(g=>g.v==='BASE400');const paired=variants.slice(1).map(v=>{const r=games.filter(g=>g.v===v);return{variant:v,avgMarginDelta:r.reduce((s,g,i)=>s+(g.margin-b[i].margin),0)/r.length,better:r.filter((g,i)=>g.margin>b[i].margin).length,worse:r.filter((g,i)=>g.margin={\n DYN_PORT:{animal_target:{COW:0,SHEEP:0}},\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n RITA_BASE:{},\n};\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zr.ok)throw new Error(String(zr.status));\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);\nfor(const [name,patch] of Object.entries(patches)){py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}\npy.runPython(`\ndef call(name,payload):\n return json.dumps(_REG[name]['agent'](json.loads(payload)))\ndef set_herd(name,cows,sheep,order):\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\n _REG[name]['POLICY']['animals']=json.loads(order)\ndef reset(name):\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\n`);\nconst call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\n\nfunction countOwned(obs:any,animal:string){const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};let n=Number(obs?.private?.shed?.[animal]??0);for(const inv of obs?.private?.inventories??[])n+=Number(inv?.[animal]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===animal)n++;return n;}\nfunction enforceAnimalTargets(obs:any,action:any,targets:{COW:number;SHEEP:number}){const actual:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const out={...action,market:[] as any[]};for(const order of action?.market??[]){if(Array.isArray(order)&&order[0]==='BUY_ANIMAL'&&(order[1]==='COW'||order[1]==='SHEEP')){const a=order[1] as 'COW'|'SHEEP';const allowed=Math.max(0,Math.min(Number(order[2]??1),targets[a]-actual[a]));if(allowed>0){out.market.push(['BUY_ANIMAL',a,allowed]);actual[a]+=allowed;}}else out.market.push(order);}return out;}\nasync function play(a:string,b:string,seed:number){\n reset(a);reset(b);let s=E.state.initGameState(2,{...cfg0,seed},seed);let errors=0;let targets={COW:0,SHEEP:0};const decisions:any[]=[];\n while(!s.done){const acts:any[]=[];\n for(const [pid,n] of [[0,a],[1,b]] as any){const obs=observationFor(s,pid);\n if(n==='DYN_PORT'&&Number(obs.hour)===0){\n const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};\n // An unexecuted target is a revocable option, not committed capital. Rebase intent on actual scheduler-visible ownership every macro cycle.\n targets={COW:owned.COW,SHEEP:owned.SHEEP};\n const actualTotal=owned.COW+owned.SHEEP;const choice=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:1.0});\n if(actualTotal<16 && choice.choice){const room=16-actualTotal,batch=Math.min(2,room);targets[choice.choice]+=batch;}\n const order=[...choice.ranking].map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP');\n setHerd('DYN_PORT',targets.COW,targets.SHEEP,JSON.stringify(order));\n decisions.push({day:obs.day,player:pid,money:obs.farms[pid].money,owned,targets:{...targets},choice:choice.choice,ranking:choice.ranking.map(x=>({animal:x.animal,net:Math.round(x.net),roi:Number(x.roi.toFixed(2)),currentPrice:x.currentPrice,projectedPrice:x.projectedPrice,townDemand:Number(x.townDemand.toFixed(1)),ownSupply:x.ownCommittedSupply,oppSupply:x.opponentSupply,liquidityPenalty:x.liquidityPenalty}))});\n }\n try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN_PORT')acts[pid]=enforceAnimalTargets(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}\n }\n s=E.interpreter.step(s,acts,{...cfg0,seed});\n }\n return{a,b,seed,bankA:s.farms[0].money,bankB:s.farms[1].money,errors,decisions};\n}\nconst games:any[]=[];for(const opp of opponents)for(const seed of seeds){games.push(await play('DYN_PORT',opp,seed));games.push(await play(opp,'DYN_PORT',seed));}\nconst summary:any={};for(const opp of opponents){const r=games.filter(g=>g.a===opp||g.b===opp).map(g=>g.a==='DYN_PORT'?{ours:g.bankA,opp:g.bankB,e:g.errors}:{ours:g.bankB,opp:g.bankA,e:g.errors});summary[opp]={episodes:r.length,wins:r.filter(x=>x.ours>x.opp).length,losses:r.filter(x=>x.oursx.ours===x.opp).length,avgBank:r.reduce((s,x)=>s+x.ours,0)/r.length,avgMargin:r.reduce((s,x)=>s+x.ours-x.opp,0)/r.length,errors:r.reduce((s,x)=>s+x.e,0)};}\nconst decisionDigest=games.filter(g=>g.a==='DYN_PORT'&&g.seed===seeds[0]).map(g=>({opponent:g.b,seed:g.seed,first8:g.decisions.slice(0,8),finalDecision:g.decisions[g.decisions.length-1]}));\nconsole.log(JSON.stringify({status:'PASS',agent:'DYN_PORT',mechanism:'GREEDY_MARGINAL_LIVESTOCK_PORTFOLIO_WITH_EVENT_DAILY_REALLOCATION',seeds,summary,decisionDigest,caveat:'Research prototype. Uses an NPV-like heuristic, not a proven optimal policy; requires ablation and broader league evaluation.'},null,2));",[588],"4f472327-6146-4ba4-bebd-26acc1823c9e","kag_dynport_diag_v3.ts","01a078d7-bb34-770f-a990-c7be4a90e8d6",80,["D",1788733808160],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\n\nconst seeds=[9403,9419,9431,9461,9491];\nconst opponents=['C4S12','C6S10','RITA_BASE'];\nconst patches:Record={\n DYN_PORT:{animal_target:{COW:0,SHEEP:0}},\n C4S12:{animal_target:{COW:4,SHEEP:12}},\n C6S10:{animal_target:{COW:6,SHEEP:10}},\n RITA_BASE:{},\n};\nconst E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');if(!zr.ok)throw new Error(String(zr.status));\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);\nfor(const [name,patch] of Object.entries(patches)){py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}\npy.runPython(`\ndef call(name,payload):\n return json.dumps(_REG[name]['agent'](json.loads(payload)))\ndef set_herd(name,cows,sheep,order):\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\n _REG[name]['POLICY']['animals']=json.loads(order)\ndef reset(name):\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\n`);\nconst call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\n\nfunction countOwned(obs:any,animal:string){const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};let n=Number(obs?.private?.shed?.[animal]??0);for(const inv of obs?.private?.inventories??[])n+=Number(inv?.[animal]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===animal)n++;return n;}\nfunction enforceAnimalTargets(obs:any,action:any,targets:{COW:number;SHEEP:number}){const actual:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const out={...action,market:[] as any[]};for(const order of action?.market??[]){if(Array.isArray(order)&&order[0]==='BUY_ANIMAL'&&(order[1]==='COW'||order[1]==='SHEEP')){const a=order[1] as 'COW'|'SHEEP';const allowed=Math.max(0,Math.min(Number(order[2]??1),targets[a]-actual[a]));if(allowed>0){out.market.push(['BUY_ANIMAL',a,allowed]);actual[a]+=allowed;}}else out.market.push(order);}return out;}\nasync function play(a:string,b:string,seed:number){\n reset(a);reset(b);let s=E.state.initGameState(2,{...cfg0,seed},seed);let errors=0;let targets={COW:0,SHEEP:0};const decisions:any[]=[];\n while(!s.done){const acts:any[]=[];\n for(const [pid,n] of [[0,a],[1,b]] as any){const obs=observationFor(s,pid);\n if(n==='DYN_PORT'&&Number(obs.hour)===0){\n const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};\n // An unexecuted target is a revocable option, not committed capital. Rebase intent on actual scheduler-visible ownership every macro cycle.\n targets={COW:owned.COW,SHEEP:owned.SHEEP};\n const actualTotal=owned.COW+owned.SHEEP;const choice=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:1.0});\n if(actualTotal<16 && choice.choice){const room=16-actualTotal,batch=Math.min(2,room);targets[choice.choice]+=batch;}\n const order=[...choice.ranking].map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP');\n setHerd('DYN_PORT',targets.COW,targets.SHEEP,JSON.stringify(order));\n decisions.push({day:obs.day,player:pid,money:obs.farms[pid].money,owned,targets:{...targets},choice:choice.choice,ranking:choice.ranking.map(x=>({animal:x.animal,net:Math.round(x.net),roi:Number(x.roi.toFixed(2)),currentPrice:x.currentPrice,projectedPrice:x.projectedPrice,townDemand:Number(x.townDemand.toFixed(1)),ownSupply:x.ownCommittedSupply,oppSupply:x.opponentSupply,liquidityPenalty:x.liquidityPenalty}))});\n }\n try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN_PORT')acts[pid]=enforceAnimalTargets(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}\n }\n s=E.interpreter.step(s,acts,{...cfg0,seed});\n }\n return{a,b,seed,bankA:s.farms[0].money,bankB:s.farms[1].money,errors,decisions};\n}\nconst games:any[]=[];for(const opp of opponents)for(const seed of seeds){games.push(await play('DYN_PORT',opp,seed));games.push(await play(opp,'DYN_PORT',seed));}\nconst summary:any={};for(const opp of opponents){const r=games.filter(g=>g.a===opp||g.b===opp).map(g=>g.a==='DYN_PORT'?{ours:g.bankA,opp:g.bankB,e:g.errors}:{ours:g.bankB,opp:g.bankA,e:g.errors});summary[opp]={episodes:r.length,wins:r.filter(x=>x.ours>x.opp).length,losses:r.filter(x=>x.oursx.ours===x.opp).length,avgBank:r.reduce((s,x)=>s+x.ours,0)/r.length,avgMargin:r.reduce((s,x)=>s+x.ours-x.opp,0)/r.length,errors:r.reduce((s,x)=>s+x.e,0)};}\nconst decisionDigest=games.filter(g=>g.a==='DYN_PORT'&&g.seed===seeds[0]).map(g=>({opponent:g.b,seed:g.seed,first8:g.decisions.slice(0,8),finalDecision:g.decisions[g.decisions.length-1]}));\nconst gameResults=games.map(g=>({seed:g.seed,seat:g.a==='DYN_PORT'?'A':'B',opponent:g.a==='DYN_PORT'?g.b:g.a,ours:g.a==='DYN_PORT'?g.bankA:g.bankB,theirs:g.a==='DYN_PORT'?g.bankB:g.bankA,margin:(g.a==='DYN_PORT'?g.bankA-g.bankB:g.bankB-g.bankA),result:(g.a==='DYN_PORT'?g.bankA:g.bankB)>(g.a==='DYN_PORT'?g.bankB:g.bankA)?'WIN':(g.a==='DYN_PORT'?g.bankA:g.bankB)<(g.a==='DYN_PORT'?g.bankB:g.bankA)?'LOSS':'TIE'}));\nconsole.log(JSON.stringify({status:'PASS',agent:'DYN_PORT',mechanism:'GREEDY_MARGINAL_LIVESTOCK_PORTFOLIO_WITH_EVENT_DAILY_REALLOCATION',seeds,summary,gameResults,decisionDigest,caveat:'Research prototype. Uses an NPV-like heuristic, not a proven optimal policy; requires ablation and broader league evaluation.'},null,2));",[596],"2011cb78-670c-4266-a8b3-95978fdc5ac2","kag_adversarial_weight_probe_v1.ts","33356816-aa4e-11f1-8e71-1607ee4eb77e",82,["D",1788738826791],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\n\nconst weights=[0,0.5,1,1.5,2.5];\nconst seeds=[9403,9419,9431,9461,9491];\nconst opponents=['C4S12','C6S10','RITA_BASE'];\nconst E=await loadOfficialKaggricultureEngine(); const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents'); if(!zr.ok) throw new Error(String(zr.status));\nconst z=unzipSync(new Uint8Array(await zr.arrayBuffer())); const src=strFromU8(z['rancher_rita.py']);\nconst py=await loadPyodide(); py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`); py.globals.set('src',src);\nconst patches:Record={DYN:{animal_target:{COW:0,SHEEP:0}},C4S12:{animal_target:{COW:4,SHEEP:12}},C6S10:{animal_target:{COW:6,SHEEP:10}},RITA_BASE:{}};\nfor(const [name,patch] of Object.entries(patches)){py.globals.set('nm',name);py.globals.set('patch',JSON.stringify(patch));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}\npy.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name):\\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);\nconst call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction countOwned(obs:any,animal:string){const me=Number(obs?.player??0),f=obs?.farms?.[me]??{};let n=Number(obs?.private?.shed?.[animal]??0);for(const inv of obs?.private?.inventories??[])n+=Number(inv?.[animal]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===animal)n++;return n;}\nfunction enforce(obs:any,action:any,targets:{COW:number;SHEEP:number}){const actual:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const out={...action,market:[] as any[]};for(const order of action?.market??[]){if(Array.isArray(order)&&order[0]==='BUY_ANIMAL'&&(order[1]==='COW'||order[1]==='SHEEP')){const a=order[1] as 'COW'|'SHEEP';const allowed=Math.max(0,Math.min(Number(order[2]??1),targets[a]-actual[a]));if(allowed>0){out.market.push(['BUY_ANIMAL',a,allowed]);actual[a]+=allowed;}} else out.market.push(order);}return out;}\nasync function play(sw:number,opp:string,seed:number,dynSeat:0|1){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed);let targets={COW:0,SHEEP:0},errors=0;const choices:any[]=[];while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===dynSeat?'DYN':opp;const obs=observationFor(s,pid);if(n==='DYN'&&Number(obs.hour)===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const total=owned.COW+owned.SHEEP;const choice=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:sw});if(total<16&&choice.choice){const batch=Math.min(2,16-total);targets[choice.choice]+=batch;}const order=[...choice.ranking].map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP');setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(order));choices.push({day:obs.day,choice:choice.choice,top:choice.ranking[0]?.animal,topNet:Math.round(choice.ranking[0]?.net??0),rivalImpact:Math.round(choice.ranking[0]?.rivalPriceImpact??0)});}try{acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}catch{errors++;acts[pid]={farmer:['PASS'],hands:[],market:[]};}}s=E.interpreter.step(s,acts,{...cfg0,seed});}const ours=s.farms[dynSeat].money,theirs=s.farms[1-dynSeat].money;return{sw,opp,seed,dynSeat,ours,theirs,margin:ours-theirs,win:ours>theirs,errors,firstChoices:choices.slice(0,6)};}\nconst games:any[]=[];for(const sw of weights)for(const opp of opponents)for(const seed of seeds){games.push(await play(sw,opp,seed,0));games.push(await play(sw,opp,seed,1));}\nconst summary:any={};for(const sw of weights){const rows=games.filter(g=>g.sw===sw);summary[String(sw)]={overall:{episodes:rows.length,wins:rows.filter(r=>r.win).length,winRate:rows.filter(r=>r.win).length/rows.length,avgBank:rows.reduce((a,r)=>a+r.ours,0)/rows.length,avgMargin:rows.reduce((a,r)=>a+r.margin,0)/rows.length,errors:rows.reduce((a,r)=>a+r.errors,0)},byOpponent:{}};for(const opp of opponents){const rs=rows.filter(r=>r.opp===opp);summary[String(sw)].byOpponent[opp]={episodes:rs.length,wins:rs.filter(r=>r.win).length,winRate:rs.filter(r=>r.win).length/rs.length,avgBank:rs.reduce((a,r)=>a+r.ours,0)/rs.length,avgMargin:rs.reduce((a,r)=>a+r.margin,0)/rs.length};}}\nconsole.log(JSON.stringify({status:'PASS',hypothesis:'VALUING_RIVAL_PRICE_DAMAGE_CAN_IMPROVE_RELATIVE_OUTCOME_BUT_TOO_MUCH_WEIGHT_MAY_DESTROY_OWN_VALUE',weights,seeds,summary,pairedDeltas:weights.slice(1).map(sw=>({sw,vs0:games.filter(g=>g.sw===sw).reduce((s,g,i)=>s+(g.margin-games.filter(x=>x.sw===0)[i].margin),0)/games.filter(g=>g.sw===sw).length}))},null,2));",[603],"6ea9880f-6b1c-4116-b408-0728001f9122","kag_active_constraint_probe_v1.ts","d005d360-aa4e-11f1-bec9-1607ee4eb77e",84,["D",1788739089926],"import { unzipSync,strFromU8 } from 'npm:fflate';\nimport { loadPyodide } from 'npm:pyodide';\nimport { loadOfficialKaggricultureEngine,observationFor } from './lib/kaggriculture_engine_loader.ts';\nimport { choosePastureAnimal } from './lib/kaggriculture_livestock_portfolio.ts';\nconst seeds=[9403,9419,9431,9461,9491],opponents=['C4S12','C6S10','RITA_BASE'];const E=await loadOfficialKaggricultureEngine();const cfg0=E.state.resolveConfig();\nconst zr=await fetch('https://www.kaggle.com/api/v1/datasets/download/raykkretzschmar/kaggriculture-reference-agents');const z=unzipSync(new Uint8Array(await zr.arrayBuffer()));const src=strFromU8(z['rancher_rita.py']);const py=await loadPyodide();py.runPython(`import json,copy\\n_REG={}\\n_BASE={}`);py.globals.set('src',src);const patches:any={DYN:{animal_target:{COW:0,SHEEP:0}},C4S12:{animal_target:{COW:4,SHEEP:12}},C6S10:{animal_target:{COW:6,SHEEP:10}},RITA_BASE:{}};for(const [n,p] of Object.entries(patches)){py.globals.set('nm',n);py.globals.set('patch',JSON.stringify(p));py.runPython(`_n={}\\nexec(src,_n)\\nfor _k,_v in json.loads(patch).items(): _n['POLICY'][_k]=_v\\n_REG[nm]=_n\\n_BASE[nm]=copy.deepcopy(_n['POLICY'])`);}py.runPython(`\\ndef call(name,payload): return json.dumps(_REG[name]['agent'](json.loads(payload)))\\ndef set_herd(name,cows,sheep,order):\\n _REG[name]['POLICY']['animal_target']={'COW':int(cows),'SHEEP':int(sheep)}\\n _REG[name]['POLICY']['animals']=json.loads(order)\\ndef reset(name):\\n _REG[name]['POLICY'].clear();_REG[name]['POLICY'].update(copy.deepcopy(_BASE[name]))\\n`);const call=py.globals.get('call'),setHerd=py.globals.get('set_herd'),reset=py.globals.get('reset');\nfunction countOwned(obs:any,a:string){const me=+obs.player,f=obs.farms[me];let n=+(obs.private?.shed?.[a]??0);for(const inv of obs.private?.inventories??[])n+=+(inv?.[a]??0);for(const row of f.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal===a)n++;return n;}\nfunction enforce(obs:any,act:any,t:any){const x:any={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};const o={...act,market:[] as any[]};for(const m of act?.market??[]){if(Array.isArray(m)&&m[0]==='BUY_ANIMAL'&&(m[1]==='COW'||m[1]==='SHEEP')){const a=m[1],q=Math.max(0,Math.min(+m[2]||1,t[a]-x[a]));if(q>0){o.market.push(['BUY_ANIMAL',a,q]);x[a]+=q;}}else o.market.push(m);}return o;}\nasync function play(opp:string,seed:number){reset('DYN');reset(opp);let s=E.state.initGameState(2,{...cfg0,seed},seed),targets:any={COW:0,SHEEP:0};const d:any[]=[];while(!s.done){const acts:any[]=[];for(const pid of [0,1] as const){const n=pid===0?'DYN':opp,obs=observationFor(s,pid);if(n==='DYN'&&+obs.hour===0){const owned={COW:countOwned(obs,'COW'),SHEEP:countOwned(obs,'SHEEP')};targets={...owned};const c=choosePastureAnimal(obs,{cashBuffer:400,strategicWeight:0});const top=c.ranking[0];const total=owned.COW+owned.SHEEP;let reason='CHOICE';if(total>=16)reason='HERD_CAP';else if(!top.financeable)reason='LIQUIDITY';else if(top.net<=0)reason='NONPOSITIVE_NET';else if(!c.choice)reason='NO_CHOICE';if(total<16&&c.choice){targets[c.choice]+=Math.min(2,16-total);}setHerd('DYN',targets.COW,targets.SHEEP,JSON.stringify(c.ranking.map(x=>x.animal).filter(x=>x==='COW'||x==='SHEEP')));d.push({day:obs.day,reason,cash:obs.farms[0].money,knownShops:(obs.town?.unlocked_shops??[]).length,owned,total,choice:c.choice,top:top.animal,net:Math.round(top.net),requiredLiquidity:Math.round(top.requiredLiquidity),financeable:top.financeable});}acts[pid]=JSON.parse(String(call(n,JSON.stringify(obs))));if(n==='DYN')acts[pid]=enforce(obs,acts[pid],targets);}s=E.interpreter.step(s,acts,{...cfg0,seed});}return{opp,seed,decisions:d};}\nconst runs:any[]=[];for(const o of opponents)for(const seed of seeds)runs.push(await play(o,seed));const all=runs.flatMap(r=>r.decisions.map((d:any)=>({...d,opp:r.opp,seed:r.seed})));const counts:any={};for(const d of all)counts[d.reason]=(counts[d.reason]??0)+1;const byDay:any={};for(const d of all){const k=String(d.day);byDay[k]=byDay[k]??{};byDay[k][d.reason]=(byDay[k][d.reason]??0)+1;}console.log(JSON.stringify({status:'PASS',dailyDecisions:all.length,constraintCounts:counts,byDay,examples:all.filter(d=>d.reason!=='CHOICE').slice(0,20)},null,2));",[610],"cc6d6013-d074-40d9-86d1-e032efb5f9ed","economic_trial_migrate.ts","c6c01576-aa18-11f1-9bd9-1607ee4eb77e",10,["D",1788715881407],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst now = new Date().toISOString();\n\nawait sqlite.batch([\n {\n sql: `CREATE TABLE IF NOT EXISTS economic_trials (\n trial_id TEXT PRIMARY KEY,\n agent_id TEXT NOT NULL,\n opportunity_id TEXT,\n lifecycle_state TEXT NOT NULL,\n operationally_eligible INTEGER NOT NULL DEFAULT 0,\n terminal INTEGER NOT NULL DEFAULT 0,\n gross_revenue REAL NOT NULL DEFAULT 0,\n browser_cost REAL NOT NULL DEFAULT 0,\n llm_cost REAL NOT NULL DEFAULT 0,\n api_cost REAL NOT NULL DEFAULT 0,\n hosting_cost REAL NOT NULL DEFAULT 0,\n platform_fee REAL NOT NULL DEFAULT 0,\n transaction_cost REAL NOT NULL DEFAULT 0,\n net_revenue REAL NOT NULL DEFAULT 0,\n currency TEXT NOT NULL DEFAULT 'BRL',\n evidence_json TEXT,\n started_at TEXT NOT NULL,\n updated_at TEXT NOT NULL,\n finished_at TEXT,\n FOREIGN KEY(agent_id) REFERENCES economic_agents(agent_id),\n FOREIGN KEY(opportunity_id) REFERENCES opportunities(opportunity_id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS agent_fitness (\n agent_id TEXT PRIMARY KEY,\n selection_state TEXT NOT NULL DEFAULT 'INCUBATION',\n lifetime_gross REAL NOT NULL DEFAULT 0,\n lifetime_cost REAL NOT NULL DEFAULT 0,\n lifetime_net REAL NOT NULL DEFAULT 0,\n benchmark_net REAL NOT NULL DEFAULT 0,\n terminal_trials INTEGER NOT NULL DEFAULT 0,\n successful_trials INTEGER NOT NULL DEFAULT 0,\n failed_trials INTEGER NOT NULL DEFAULT 0,\n rank INTEGER,\n offspring_count INTEGER NOT NULL DEFAULT 0,\n updated_at TEXT NOT NULL,\n FOREIGN KEY(agent_id) REFERENCES economic_agents(agent_id)\n )`,\n },\n { sql: `CREATE INDEX IF NOT EXISTS idx_trials_agent_state ON economic_trials(agent_id,lifecycle_state)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_trials_opportunity ON economic_trials(opportunity_id,lifecycle_state)` },\n {\n sql: `INSERT OR IGNORE INTO agent_fitness(agent_id,selection_state,updated_at)\n SELECT agent_id,'INCUBATION',? FROM economic_agents`,\n args: [now],\n },\n {\n sql: `INSERT INTO schema_meta(key,value,updated_at) VALUES('economic_trial_schema_version','0.6.1-candidate',?)\n ON CONFLICT(key) DO UPDATE SET value=excluded.value,updated_at=excluded.updated_at`,\n args: [now],\n },\n]);\n\nconst tables = await sqlite.execute(`SELECT name FROM sqlite_master WHERE type='table' AND name IN ('economic_trials','agent_fitness') ORDER BY name`);\nconst fitness = await sqlite.execute(`SELECT agent_id,selection_state,lifetime_net,terminal_trials FROM agent_fitness ORDER BY agent_id`);\nconsole.log(JSON.stringify({ status: 'PASS', version: '0.6.1-candidate', tables: tables.rows, fitness: fitness.rows }, null, 2));\n",[617],"3746465a-cdd1-4c28-a3bd-e17821cba719","economic_status.ts","af4f16f4-aa17-11f1-a15c-1607ee4eb77e",14,["D",1788716592876],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { ECONOMIC_POLICY } from \"./lib/economic_policy.ts\";\n\nconst agents = await sqlite.execute(`SELECT status, COUNT(*) AS count FROM economic_agents GROUP BY status ORDER BY status`);\nconst opportunities = await sqlite.execute(`SELECT status, COUNT(*) AS count FROM opportunities GROUP BY status ORDER BY status`);\nconst runs = await sqlite.execute(`SELECT state, COUNT(*) AS count, COALESCE(SUM(net_revenue),0) AS net_revenue FROM economic_runs GROUP BY state ORDER BY state`);\nconst trials = await sqlite.execute(`SELECT lifecycle_state,COUNT(*) AS count,COALESCE(SUM(net_revenue),0) AS net_revenue FROM economic_trials GROUP BY lifecycle_state ORDER BY lifecycle_state`);\nconst fitness = await sqlite.execute(`SELECT agent_id,selection_state,lifetime_gross,lifetime_cost,lifetime_net,benchmark_net,terminal_trials,successful_trials,failed_trials,rank,offspring_count,updated_at FROM agent_fitness ORDER BY generation IS NULL, rank IS NULL, rank, agent_id`).catch(async () =>\n await sqlite.execute(`SELECT agent_id,selection_state,lifetime_gross,lifetime_cost,lifetime_net,benchmark_net,terminal_trials,successful_trials,failed_trials,rank,offspring_count,updated_at FROM agent_fitness ORDER BY rank IS NULL,rank,agent_id`)\n);\nconst variants = await sqlite.execute(`SELECT variant_id,agent_id,parent_variant_id,generation,name,mutation,status,evidence_state,benchmark_metric,benchmark_value,artifact_pointer,updated_at FROM strategy_variants ORDER BY agent_id,generation,variant_id`);\nconst variantEvals = await sqlite.execute(`SELECT variant_id,COUNT(*) AS evaluations,COALESCE(SUM(episodes),0) AS episodes,COALESCE(SUM(wins),0) AS wins,COALESCE(SUM(losses),0) AS losses,COALESCE(SUM(ties),0) AS ties,COALESCE(SUM(runtime_errors),0) AS runtime_errors FROM variant_evaluations GROUP BY variant_id ORDER BY variant_id`);\nconst champions = await sqlite.execute(`SELECT champion_class,agent_id,run_id,metric_value,currency,updated_at FROM economic_champions ORDER BY champion_class`);\nconst latestAgents = await sqlite.execute(`SELECT agent_id,parent_id,generation,lineage,status,hypothesis,strategy,updated_at FROM economic_agents ORDER BY generation DESC,agent_id LIMIT 20`);\nconst latestOpportunities = await sqlite.execute(`SELECT opportunity_id,title,source,url,category,deadline,payout_currency,payout_max,estimated_cost,human_dependency,evidence_state,status,score,updated_at FROM opportunities ORDER BY score DESC,updated_at DESC LIMIT 30`);\nconst latestTrials = await sqlite.execute(`SELECT trial_id,agent_id,opportunity_id,lifecycle_state,operationally_eligible,terminal,gross_revenue,net_revenue,currency,updated_at,finished_at FROM economic_trials ORDER BY updated_at DESC LIMIT 30`);\nconst failures = await sqlite.execute(`SELECT failure_class,COUNT(*) AS count,MAX(created_at) AS latest FROM negative_knowledge GROUP BY failure_class ORDER BY latest DESC,failure_class`);\nconst success = await sqlite.execute(`SELECT COUNT(*) AS count, COALESCE(MAX(replication_count),0) AS max_replications FROM success_patterns`);\nconst totals = await sqlite.execute(`SELECT\n COALESCE(SUM(gross_revenue),0) AS gross_revenue,\n COALESCE(SUM(browser_cost+llm_cost+api_cost+hosting_cost+platform_fee+transaction_cost),0) AS total_cost,\n COALESCE(SUM(net_revenue),0) AS net_revenue\n FROM economic_trials`);\nconst schema = await sqlite.execute(`SELECT key,value,updated_at FROM schema_meta WHERE key LIKE '%version%' ORDER BY key`);\n\nconst totalRow = totals.rows[0] ?? {};\nconst realRevenue = Number(totalRow.gross_revenue ?? 0);\nconst realNet = Number(totalRow.net_revenue ?? 0);\nconst terminalTrialCount = latestTrials.rows.filter((x: Record) => Number(x.terminal ?? 0) === 1).length;\n\nconsole.log(JSON.stringify({\n service: \"chat-native-maestro/economic\",\n version: ECONOMIC_POLICY.version,\n schema: schema.rows,\n agents: agents.rows,\n opportunities: opportunities.rows,\n runs: runs.rows,\n trials: trials.rows,\n fitness: fitness.rows,\n variants: variants.rows,\n variantEvaluations: variantEvals.rows,\n champions: champions.rows,\n latestAgents: latestAgents.rows,\n rankedOpportunities: latestOpportunities.rows,\n latestTrials: latestTrials.rows,\n failureClasses: failures.rows,\n successPatterns: success.rows,\n totals: totalRow,\n terminalTrialCount,\n realRevenueState: realRevenue > 0 ? \"NONZERO\" : \"ZERO\",\n netRevenueState: realNet > 0 ? \"POSITIVE\" : realNet < 0 ? \"NEGATIVE\" : \"ZERO\",\n selfSustaining: realNet > 0 && terminalTrialCount > 0,\n timestamp: new Date().toISOString(),\n}, null, 2));\n",[624],"aa858d97-bbd1-487f-951e-c22790b9a453","economic_selftest.ts","66d41424-aa17-11f1-9a39-1607ee4eb77e",4,["D",1788715291111],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { ECONOMIC_POLICY, evaluateEconomicAction, netRevenue } from \"./lib/economic_policy.ts\";\n\nconst cases = {\n r0: evaluateEconomicAction({ actionClass: \"R0_OBSERVE\" }),\n r1: evaluateEconomicAction({ actionClass: \"R1_PREPARE\" }),\n r2: evaluateEconomicAction({ actionClass: \"R2_REVERSIBLE_WRITE\" }),\n r3Blocked: evaluateEconomicAction({ actionClass: \"R3_COMMIT_SUBMIT\", approved: false }),\n r3Approved: evaluateEconomicAction({ actionClass: \"R3_COMMIT_SUBMIT\", approved: true }),\n r4BlockedNoApproval: evaluateEconomicAction({ actionClass: \"R4_ECONOMIC_SPEND\", amount: 1, maxBudget: 5, approved: false }),\n r4BlockedBudget: evaluateEconomicAction({ actionClass: \"R4_ECONOMIC_SPEND\", amount: 6, maxBudget: 5, approved: true }),\n r4Approved: evaluateEconomicAction({ actionClass: \"R4_ECONOMIC_SPEND\", amount: 4, maxBudget: 5, approved: true }),\n r5: evaluateEconomicAction({ actionClass: \"R5_IDENTITY_LEGAL\", approved: true }),\n};\n\nconst profitCase = netRevenue({ grossRevenue: 10, browserCost: 1, llmCost: 2, apiCost: 0.5, platformFee: 1 });\nconst lossCase = netRevenue({ grossRevenue: 5, browserCost: 4, llmCost: 3 });\nconst tables = await sqlite.execute(`SELECT name FROM sqlite_master WHERE type='table' AND name IN (\n 'economic_agents','opportunities','economic_runs','negative_knowledge','success_patterns','economic_champions'\n) ORDER BY name`);\nconst root = await sqlite.execute(`SELECT agent_id,parent_id,generation,lineage,status FROM economic_agents WHERE agent_id='A0'`);\n\nconst checks = [\n { name: \"R0 auto\", pass: cases.r0.allowed && !cases.r0.humanGate },\n { name: \"R1 auto\", pass: cases.r1.allowed && !cases.r1.humanGate },\n { name: \"R2 auto\", pass: cases.r2.allowed && !cases.r2.humanGate },\n { name: \"R3 blocks without approval\", pass: !cases.r3Blocked.allowed && cases.r3Blocked.reason === \"NEEDS_COMMIT_APPROVAL\" },\n { name: \"R3 allows approved\", pass: cases.r3Approved.allowed },\n { name: \"R4 blocks no approval\", pass: !cases.r4BlockedNoApproval.allowed },\n { name: \"R4 enforces budget\", pass: !cases.r4BlockedBudget.allowed && cases.r4BlockedBudget.reason === \"BUDGET_EXCEEDED\" },\n { name: \"R4 permits approved in-budget\", pass: cases.r4Approved.allowed },\n { name: \"R5 always human gate\", pass: !cases.r5.allowed && cases.r5.humanGate },\n { name: \"net revenue profit\", pass: profitCase === 5.5 },\n { name: \"net revenue loss\", pass: lossCase === -2 },\n { name: \"all economic tables present\", pass: tables.rows.length === 6 },\n { name: \"A0 root present\", pass: root.rows.length === 1 && root.rows[0].generation === 0 },\n];\n\nconst failed = checks.filter((x) => !x.pass);\nconsole.log(JSON.stringify({\n status: failed.length ? \"FAIL\" : \"PASS\",\n version: ECONOMIC_POLICY.version,\n checks,\n failed,\n cases,\n profitCase,\n lossCase,\n tables: tables.rows,\n root: root.rows,\n}, null, 2));\nif (failed.length) throw new Error(`economic_selftest failed: ${failed.map((x) => x.name).join(', ')}`);\n",[631],"c2e35226-ae2c-4a39-bfb8-3af34f7addf3","economic_migrate.ts","5a85f9ee-aa17-11f1-8f39-1607ee4eb77e",3,["D",1788715270460],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst now = new Date().toISOString();\n\nawait sqlite.batch([\n {\n sql: `CREATE TABLE IF NOT EXISTS economic_agents (\n agent_id TEXT PRIMARY KEY,\n parent_id TEXT,\n generation INTEGER NOT NULL DEFAULT 0,\n lineage TEXT NOT NULL,\n hypothesis TEXT NOT NULL,\n strategy TEXT NOT NULL,\n status TEXT NOT NULL,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL,\n FOREIGN KEY(parent_id) REFERENCES economic_agents(agent_id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS opportunities (\n opportunity_id TEXT PRIMARY KEY,\n title TEXT NOT NULL,\n source TEXT NOT NULL,\n url TEXT,\n category TEXT NOT NULL,\n deadline TEXT,\n payout_currency TEXT,\n payout_max REAL,\n estimated_cost REAL NOT NULL DEFAULT 0,\n human_dependency REAL NOT NULL DEFAULT 1,\n evidence_state TEXT NOT NULL,\n status TEXT NOT NULL,\n score REAL,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS economic_runs (\n run_id TEXT PRIMARY KEY,\n agent_id TEXT NOT NULL,\n opportunity_id TEXT,\n browser_run_id TEXT,\n action_class TEXT NOT NULL,\n strategy_variant TEXT,\n provider TEXT,\n state TEXT NOT NULL,\n gross_revenue REAL NOT NULL DEFAULT 0,\n currency TEXT NOT NULL DEFAULT 'BRL',\n browser_cost REAL NOT NULL DEFAULT 0,\n llm_cost REAL NOT NULL DEFAULT 0,\n api_cost REAL NOT NULL DEFAULT 0,\n hosting_cost REAL NOT NULL DEFAULT 0,\n platform_fee REAL NOT NULL DEFAULT 0,\n transaction_cost REAL NOT NULL DEFAULT 0,\n net_revenue REAL NOT NULL DEFAULT 0,\n evidence_json TEXT,\n started_at TEXT NOT NULL,\n finished_at TEXT,\n FOREIGN KEY(agent_id) REFERENCES economic_agents(agent_id),\n FOREIGN KEY(opportunity_id) REFERENCES opportunities(opportunity_id)\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS negative_knowledge (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n agent_id TEXT,\n opportunity_id TEXT,\n failure_class TEXT NOT NULL,\n cause TEXT NOT NULL,\n context TEXT,\n detector TEXT,\n avoid_rule TEXT,\n evidence_json TEXT,\n created_at TEXT NOT NULL\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS success_patterns (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n agent_id TEXT,\n opportunity_id TEXT,\n mechanism TEXT NOT NULL,\n preconditions TEXT,\n counterfactual TEXT,\n boundaries TEXT,\n replication_count INTEGER NOT NULL DEFAULT 0,\n confidence REAL NOT NULL DEFAULT 0,\n evidence_json TEXT,\n created_at TEXT NOT NULL,\n updated_at TEXT NOT NULL\n )`,\n },\n {\n sql: `CREATE TABLE IF NOT EXISTS economic_champions (\n champion_class TEXT PRIMARY KEY,\n agent_id TEXT NOT NULL,\n run_id TEXT,\n metric_value REAL NOT NULL DEFAULT 0,\n currency TEXT NOT NULL DEFAULT 'BRL',\n updated_at TEXT NOT NULL\n )`,\n },\n { sql: `CREATE INDEX IF NOT EXISTS idx_economic_agents_parent ON economic_agents(parent_id)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_opportunities_status_score ON opportunities(status, score)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_economic_runs_agent ON economic_runs(agent_id, started_at)` },\n { sql: `CREATE INDEX IF NOT EXISTS idx_economic_runs_opportunity ON economic_runs(opportunity_id, started_at)` },\n {\n sql: `INSERT OR IGNORE INTO economic_agents(agent_id,parent_id,generation,lineage,hypothesis,strategy,status,created_at,updated_at)\n VALUES('A0',NULL,0,'A0','Find economically viable opportunities with minimal human dependency','Neurônio root: branch, measure, falsify, replicate winners','INCUBATION',?,?)`,\n args: [now, now],\n },\n {\n sql: `INSERT INTO schema_meta(key,value,updated_at) VALUES('economic_schema_version','0.6.0-candidate',?)\n ON CONFLICT(key) DO UPDATE SET value=excluded.value, updated_at=excluded.updated_at`,\n args: [now],\n },\n]);\n\nconst tables = await sqlite.execute(`SELECT name FROM sqlite_master WHERE type='table' AND name IN (\n 'economic_agents','opportunities','economic_runs','negative_knowledge','success_patterns','economic_champions'\n) ORDER BY name`);\nconst root = await sqlite.execute(`SELECT agent_id,generation,lineage,status FROM economic_agents WHERE agent_id='A0'`);\nconsole.log(JSON.stringify({ status: 'PASS', economicSchemaVersion: '0.6.0-candidate', tables: tables.rows, root: root.rows }, null, 2));\n",[638],"ae39bf64-442c-408a-a4d7-fb176828672b","README.md","01a077bc-2b99-740d-9881-4e48ec93504b",["D",1788715215771],"# Chat-Native Maestro V0.5.0\n\nCloud runtime controlled from normal ChatGPT mobile/web.\n\n## Canonical constraint\n\n- No Codex.\n- No user PC.\n- No local browser runtime.\n- Normal ChatGPT is the control plane.\n- Val Town is the persistent cloud compute/state plane.\n- No automatic browser schedule is enabled.\n\n## Runtime path\n\n`ChatGPT -> authenticated Val Town plugin -> val-scoped SQLite -> runner.ts -> provider router -> cloud browser -> verified receipt`\n\nThe public HTTP endpoint is liveness-only. Provider configuration, task state, receipts, health and cost metrics are available only through authenticated `status.ts` execution.\n\n## Browser routing\n\n1. Kernel — primary/champion.\n2. Browserless — recurring-free fallback.\n3. Browserbase — researched fallback, not implemented.\n4. Steel — one-time-credit fallback, not preferred for steady state.\n\nCross-provider fallback is allowed only for `read_only`. A write failure is never replayed automatically on another provider because failure is not proof of zero side effects.\n\n## Current provider economics (research snapshot 2026-09-06)\n\n### Kernel Free\n\n- $0/month plus usage costs.\n- $5/month free credits.\n- 5 concurrent browsers.\n- live view.\n- stealth mode with CAPTCHA solver/proxy.\n- managed auth.\n- no card required to get started.\n- usage model: GB-second.\n\n### Browserless Free\n\n- 1,000 units/month.\n- 2 concurrent browsers.\n- 2-minute max session.\n- no card required.\n- browser time: 1 unit per 30-second block.\n- successful CAPTCHA solve: additional units.\n- built-in proxies: additional units.\n- provider supports an overage cap that should be set to $0 for this project's zero-surprise-cost policy.\n\n## Browser DSL\n\nSupported:\n- `goto`\n- `wait_for`\n- `click`\n- `fill`\n- `fill_secret`\n- `type`\n- `select`\n- `extract_text`\n- `extract_attribute`\n- `expect_text`\n- `expect_url`\n\nArbitrary JavaScript and shell input are intentionally absent from the task schema.\n\nThe `value` attribute is blocked from `extract_attribute` to reduce accidental credential exfiltration after form fill.\n\n## Risk gates\n\n- `read_only`: normal execution.\n- `reversible_write`: requires explicit `approved=true`.\n- `consequential`: requires explicit `approved=true`.\n- `fill_secret`: separately requires explicit approval, even during a read-oriented flow.\n\n## Secret handling\n\nPasswords, cookies and provider tokens must never be stored in `task_json`.\n\nUse:\n\n```json\n{\"action\":\"fill_secret\",\"selector\":\"#password\",\"envVar\":\"PORTAL_PASSWORD\"}\n```\n\nOnly the environment-variable name is stored. The value is resolved in memory immediately before execution.\n\nProvider credentials belong only in Val Town env vars:\n- `KERNEL_API_KEY`\n- `BROWSERLESS_TOKEN`\n- optional `BROWSERLESS_BASE_URL`\n\n## Network / SSRF boundary\n\nBefore any provider call, `runner.ts` runs a fail-closed network preflight:\n\n- only HTTP/HTTPS;\n- URL userinfo is blocked;\n- nonstandard ports are blocked;\n- localhost/private/link-local/reserved/documentation IP ranges are blocked;\n- known metadata/internal hostnames are blocked;\n- `allowedHosts` are validated;\n- hostnames are resolved with DNS-over-HTTPS and all A/AAAA results must be public.\n\nThe browser program itself also restricts main-frame navigation to the original target host plus explicit `allowedHosts`.\n\nDNS preflight reduces SSRF/DNS-rebinding risk but is not a mathematical proof against DNS rebinding after the preflight. Provider isolation and post-action validation remain required.\n\n## Read-only browser firewall\n\nWhen `risk=read_only`, browser network requests using methods other than GET/HEAD/OPTIONS are aborted. Popups are closed.\n\nThis prevents common POST/PUT/PATCH/DELETE side effects. It cannot guarantee zero side effects on badly designed GET endpoints.\n\n## Reliability controls\n\n- task `run_id` is unique/idempotent;\n- atomic queue claim;\n- 90-second RUNNING lease;\n- stale lease recovery;\n- max 2 task attempts;\n- read-only FAIL retry delay: 10 seconds;\n- writes are not auto-retried;\n- browser timeout: 25 seconds;\n- Kernel cleanup timeout: 5 seconds;\n- provider circuit opens after 3 consecutive provider FAILs;\n- circuit cooldown: 15 minutes;\n- BLOCKED configuration errors do not degrade provider health;\n- no cron/automatic runner, so eligible retries still require an explicit ChatGPT runner invocation.\n\n## Evidence retention\n\nDefault is `minimal`:\n- status;\n- final URL;\n- expectations/checks;\n- error;\n- duration;\n- fallback metadata;\n- DNS preflight evidence.\n\nExtracted outputs and provider session IDs are not persisted by default.\n\nUse `evidenceRetention: \"full\"` only when the extracted output is intentionally safe to retain.\n\n## Cost telemetry\n\n`browser_attempts` records per-attempt provider/status/duration and an estimated Browserless browser-time unit count.\n\nBrowserless estimates exclude CAPTCHA/proxy add-ons. Kernel usage is not estimated locally because its billing basis is GB-second; actual account usage must be observed from Kernel.\n\n## PASS rule\n\n`TOOL_SUCCESS_RESPONSE != BEHAVIOR_PROOF`.\n\nA browser execution with no positive expectation remains `PARTIAL`. `PASS` requires all explicit expectations to succeed.\n\n## Current live evidence\n\nPASS:\n- Val Town plugin authenticated.\n- Free workspace.\n- create/edit/run/deploy.\n- public liveness endpoint.\n- authenticated diagnostics.\n- val-scoped SQLite.\n- schema versioning.\n- atomic task claim.\n- stale lease recovery.\n- persisted task/attempt receipts.\n- retry decision logic.\n- timeout control.\n- provider circuit breaker and restore test.\n- risk approval gate.\n- secret approval gate.\n- invalid provider rejection.\n- `value` attribute extraction rejection.\n- DNS-over-HTTPS preflight.\n- private/metadata URL blocking in both self-test and runner pipeline.\n- Kernel SDK module loading.\n- Browserless adapter module loading.\n- safe missing-provider-credential classification.\n\nUNVERIFIED:\n- Kernel API authentication for this account.\n- live Kernel browser creation.\n- live Kernel Playwright execution.\n- Kernel actual credit consumption.\n- Browserless API authentication for this account.\n- live Browserless `/function` execution.\n- Browserless actual unit consumption.\n\nNo user-created environment variables are currently configured, so no live browser provider has been promoted to OPERATIONAL.\n\n## Next milestone\n\n`docs/SMOKE_TASK.json` is deliberately a DRAFT, not a queued task. After exactly one provider credential is configured, ChatGPT can enqueue that read-only smoke task, run `runner.ts`, persist the attempt and promote the provider only if the explicit expectations PASS.\n\nSee:\n- `docs/CURRENT_STATE.md`\n- `docs/PROVIDER_CENSUS.md`\n- `docs/ACTIVATION_RUNBOOK.md`\n- `docs/TASK_SCHEMA.md`\n- 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type { BrowserReceipt, BrowserTask, ProviderName } from \"../lib/types.ts\";\nimport { executeKernel, kernelConfigured } from \"./kernel.ts\";\nimport { browserlessConfigured, executeBrowserless } from \"./browserless.ts\";\nimport { providerAvailable, recordProviderOutcome } from \"../lib/provider_health.ts\";\n\nexport function providerState() {\n const kernel = kernelConfigured();\n const browserless = browserlessConfigured();\n return {\n kernel: { priority: 1, configured: kernel, state: kernel ? \"READY\" : \"ACCOUNT_KEY_REQUIRED\" },\n browserless: { priority: 2, configured: browserless, state: browserless ? \"READY\" : \"ACCOUNT_TOKEN_REQUIRED\" },\n };\n}\n\nasync function runProvider(provider: ProviderName, task: BrowserTask): Promise {\n const health = await providerAvailable(provider);\n if (!health.available) {\n return { runId: task.runId, provider, status: \"BLOCKED\", error: health.reason ?? \"provider circuit open\" };\n }\n\n const receipt = provider === \"kernel\" ? 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return withFallbackMeta(fallback, primary);\n }\n return primary;\n }\n\n if (browserlessConfigured()) return runProvider(\"browserless\", task);\n return runProvider(\"kernel\", task);\n}\n",[],[651,975],"fc83999d-4ff9-4e7c-abc1-af6110dc1d07","kernel.ts","01a077bc-2b99-740d-9881-42c7df42306f",["D",1788715215771],"import Kernel from \"npm:@onkernel/sdk\";\nimport type { BrowserReceipt, BrowserTask } from \"../lib/types.ts\";\nimport { buildKernelPlaywrightCode, resolveSecrets } from \"../lib/dsl.ts\";\nimport { POLICY, withTimeout } from \"../lib/policy.ts\";\n\nexport function kernelConfigured(): boolean {\n return Boolean(Deno.env.get(\"KERNEL_API_KEY\"));\n}\n\nexport async function executeKernel(task: BrowserTask): Promise {\n const apiKey = Deno.env.get(\"KERNEL_API_KEY\");\n if (!apiKey) {\n return { runId: task.runId, provider: \"kernel\", status: \"BLOCKED\", error: \"KERNEL_API_KEY missing\" };\n }\n\n let resolvedTask: BrowserTask;\n try {\n resolvedTask = resolveSecrets(task);\n } catch (error) {\n return { runId: task.runId, provider: \"kernel\", status: \"BLOCKED\", error: error instanceof Error ? error.message : String(error) };\n }\n\n const started = Date.now();\n const kernel = new Kernel({ apiKey });\n let sessionId: string | undefined;\n try {\n const kernelBrowser = await withTimeout(\n kernel.browsers.create({ headless: true, stealth: true }),\n 10_000,\n \"kernel browser create\",\n );\n sessionId = kernelBrowser.session_id;\n\n const response = await withTimeout(\n kernel.browsers.playwright.execute(sessionId, {\n code: buildKernelPlaywrightCode(resolvedTask),\n }),\n POLICY.browserTimeoutMs,\n \"kernel playwright execute\",\n );\n const result = (response as any).result ?? response;\n const verified = Boolean(result?.verified);\n return {\n runId: task.runId,\n provider: \"kernel\",\n status: verified ? \"PASS\" : \"PARTIAL\",\n finalUrl: result?.finalUrl,\n outputs: result?.outputs ?? {},\n checks: result?.checks ?? [],\n durationMs: Date.now() - started,\n providerMeta: { sessionId, headless: true, stealth: true },\n };\n } catch (error) {\n return {\n runId: task.runId,\n provider: \"kernel\",\n status: \"FAIL\",\n error: error instanceof Error ? error.message : String(error),\n durationMs: Date.now() - started,\n providerMeta: sessionId ? { sessionId } : {},\n };\n } finally {\n if (sessionId) {\n try {\n await withTimeout(kernel.browsers.deleteByID(sessionId), 5_000, \"kernel browser cleanup\");\n } catch (cleanupError) {\n console.error(\"kernel cleanup failed\", cleanupError);\n }\n }\n }\n}\n",[],[651,982],"26c3a975-f21b-42bd-bb91-c1a4c17ea40b","browserless.ts","01a077bc-2b99-740d-9881-3f2f98b23d50",["D",1788715215771],"import type { BrowserReceipt, BrowserTask } from \"../lib/types.ts\";\nimport { resolveSecrets } from \"../lib/dsl.ts\";\nimport { POLICY } from \"../lib/policy.ts\";\n\nconst FUNCTION_CODE = String.raw`\nexport default async ({ page, context }) => {\n const plan = context.plan;\n const outputs = {};\n const checks = [];\n const targetHost = new URL(plan.targetUrl).hostname;\n const allowedHosts = new Set([targetHost, ...(plan.allowedHosts || [])]);\n const allowedMethods = new Set([\"GET\", \"HEAD\", \"OPTIONS\"]);\n const assertUrl = (value) => {\n const u = new URL(value);\n if (![\"http:\", \"https:\"].includes(u.protocol)) throw new Error(\"blocked protocol\");\n if (!allowedHosts.has(u.hostname)) throw new Error(\"blocked host: \" + u.hostname);\n };\n\n await page.setRequestInterception(true);\n page.on(\"request\", (req) => {\n try {\n if (req.isNavigationRequest() && req.frame() === page.mainFrame()) assertUrl(req.url());\n if (plan.risk === \"read_only\" && !allowedMethods.has(req.method().toUpperCase())) return req.abort(\"blockedbyclient\");\n return req.continue();\n } catch {\n return req.abort(\"blockedbyclient\");\n }\n });\n page.on(\"popup\", async (popup) => { try { await popup.close(); } catch {} });\n\n assertUrl(plan.targetUrl);\n await page.goto(plan.targetUrl, { waitUntil: \"domcontentloaded\" });\n assertUrl(page.url());\n\n for (const step of plan.steps) {\n switch (step.action) {\n case \"goto\": {\n const url = step.url || plan.targetUrl;\n assertUrl(url);\n await page.goto(url, { waitUntil: \"domcontentloaded\" });\n break;\n }\n case \"wait_for\":\n await page.waitForSelector(step.selector, { visible: true, timeout: step.timeoutMs || 10000 });\n break;\n case \"click\":\n if (step.waitForNavigation) {\n await Promise.all([page.waitForNavigation({ waitUntil: \"domcontentloaded\" }), page.click(step.selector)]);\n } else await page.click(step.selector);\n break;\n case \"fill\":\n await page.click(step.selector, { clickCount: 3 });\n await page.keyboard.press(\"Backspace\");\n await page.type(step.selector, step.text);\n break;\n case \"type\":\n await page.type(step.selector, step.text, { delay: step.delayMs || 0 });\n break;\n case \"select\":\n await page.select(step.selector, step.value);\n break;\n case \"extract_text\":\n outputs[step.key] = await page.$eval(step.selector, (el) => el.textContent || \"\");\n break;\n case \"extract_attribute\":\n outputs[step.key] = await page.$eval(step.selector, (el, attr) => el.getAttribute(attr), step.attribute);\n break;\n case \"expect_text\": {\n const body = await page.evaluate(() => document.body?.innerText || \"\");\n checks.push({ type: \"text\", expected: step.text, ok: body.includes(step.text) });\n break;\n }\n case \"expect_url\": {\n const actual = page.url();\n checks.push({ type: \"url\", expected: step.contains, actual, ok: actual.includes(step.contains) });\n break;\n }\n }\n assertUrl(page.url());\n }\n\n return {\n data: {\n finalUrl: page.url(),\n outputs,\n checks,\n verified: checks.length > 0 && checks.every((x) => x.ok),\n },\n type: \"application/json\",\n };\n};\n`;\n\nexport function browserlessConfigured(): boolean {\n return Boolean(Deno.env.get(\"BROWSERLESS_TOKEN\"));\n}\n\nexport async function executeBrowserless(task: BrowserTask): Promise {\n const token = Deno.env.get(\"BROWSERLESS_TOKEN\");\n if (!token) return { runId: task.runId, provider: \"browserless\", status: \"BLOCKED\", error: \"BROWSERLESS_TOKEN missing\" };\n\n let resolvedTask: BrowserTask;\n try {\n resolvedTask = resolveSecrets(task);\n } catch (error) {\n return { runId: task.runId, provider: \"browserless\", status: \"BLOCKED\", error: error instanceof Error ? error.message : String(error) };\n }\n\n const started = Date.now();\n const base = (Deno.env.get(\"BROWSERLESS_BASE_URL\") || \"https://production-sfo.browserless.io\").replace(/\\/+$/, \"\");\n try {\n const response = await fetch(`${base}/function?token=${encodeURIComponent(token)}`, {\n method: \"POST\",\n headers: { \"content-type\": \"application/json\" },\n body: JSON.stringify({ code: FUNCTION_CODE, context: { plan: resolvedTask } }),\n signal: AbortSignal.timeout(POLICY.browserTimeoutMs),\n });\n const text = await response.text();\n let result: any;\n try { result = JSON.parse(text); } catch { result = { raw: text }; }\n if (!response.ok) {\n return { runId: task.runId, provider: \"browserless\", status: \"FAIL\", error: `HTTP ${response.status}: ${text.slice(0, 500)}`, durationMs: Date.now() - started };\n }\n return {\n runId: task.runId,\n provider: \"browserless\",\n status: result?.verified ? \"PASS\" : \"PARTIAL\",\n finalUrl: result?.finalUrl,\n outputs: result?.outputs ?? {},\n checks: result?.checks ?? [],\n durationMs: Date.now() - started,\n providerMeta: { base },\n };\n } catch (error) {\n return { runId: task.runId, provider: \"browserless\", status: \"FAIL\", error: error instanceof Error ? error.message : String(error), durationMs: Date.now() - started };\n }\n}\n",[],[651,989],["D",1788715215771],[714,715,716],[651],"55c421c5-2ce5-4f82-9115-c76d40c7214a","url_security.ts","01a077bc-2b99-740d-9881-355e348197e4",["D",1788715215771],"import type { BrowserTask } from \"./types.ts\";\n\ntype DnsAnswer = { name?: string; type?: number; data?: string };\ntype DnsJson = { Status?: number; Answer?: DnsAnswer[] };\n\nconst BLOCKED_HOST_NAMES = new Set([\n \"localhost\",\n \"localhost.localdomain\",\n \"metadata.google.internal\",\n \"metadata\",\n]);\n\nfunction stripBrackets(host: string): string {\n return host.startsWith(\"[\") && host.endsWith(\"]\") ? host.slice(1, -1) : host;\n}\n\nfunction parseIpv4(value: string): number[] | null {\n const parts = value.split(\".\");\n if (parts.length !== 4) return null;\n const nums = parts.map((p) => Number(p));\n if (nums.some((n) => !Number.isInteger(n) || n < 0 || n > 255)) return null;\n return nums;\n}\n\nexport function isNonPublicIp(value: string): boolean {\n const ip = stripBrackets(value.trim().toLowerCase());\n const v4 = parseIpv4(ip);\n if (v4) {\n const [a, b, c] = v4;\n if (a === 0 || a === 10 || a === 127 || a >= 224) return true;\n if (a === 100 && b >= 64 && b <= 127) return true;\n if (a === 169 && b === 254) return true;\n if (a === 172 && b >= 16 && b <= 31) return true;\n if (a === 192 && b === 0 && c === 0) return true;\n if (a === 192 && b === 0 && c === 2) return true;\n if (a === 192 && b === 168) return true;\n if (a === 198 && (b === 18 || b === 19)) return true;\n if (a === 198 && b === 51 && c === 100) return true;\n if (a === 203 && b === 0 && c === 113) return true;\n return false;\n }\n\n if (ip.includes(\":\")) {\n if (ip === \"::\" || ip === \"::1\") return true;\n if (ip.startsWith(\"fc\") || ip.startsWith(\"fd\")) return true;\n if (/^fe[89ab]/.test(ip)) return true;\n if (ip.startsWith(\"ff\")) return true;\n if (ip.startsWith(\"2001:db8\")) return true;\n const mapped = ip.match(/::ffff:(\\d+\\.\\d+\\.\\d+\\.\\d+)$/);\n if (mapped) return isNonPublicIp(mapped[1]);\n return false;\n }\n\n return false;\n}\n\nfunction blockedHostname(hostname: string): boolean {\n const host = stripBrackets(hostname.toLowerCase().replace(/\\.$/, \"\"));\n if (BLOCKED_HOST_NAMES.has(host)) return true;\n if (host.endsWith(\".localhost\") || host.endsWith(\".local\") || host.endsWith(\".internal\") || host.endsWith(\".home.arpa\")) return true;\n if (isNonPublicIp(host)) return true;\n return false;\n}\n\nasync function doh(hostname: string, type: \"A\" | \"AAAA\"): Promise {\n const url = new URL(\"https://cloudflare-dns.com/dns-query\");\n url.searchParams.set(\"name\", hostname);\n url.searchParams.set(\"type\", type);\n const response = await fetch(url, {\n headers: { accept: \"application/dns-json\" },\n signal: AbortSignal.timeout(5_000),\n });\n if (!response.ok) throw new Error(`DoH ${type} failed with HTTP ${response.status}`);\n return await response.json() as DnsJson;\n}\n\nexport async function resolvePublicIps(hostname: string): Promise {\n const host = stripBrackets(hostname.toLowerCase().replace(/\\.$/, \"\"));\n if (blockedHostname(host)) throw new Error(`blocked hostname: ${host}`);\n if (parseIpv4(host) || host.includes(\":\")) return [host];\n\n const [a, aaaa] = await Promise.all([doh(host, \"A\"), doh(host, \"AAAA\")]);\n const answers = [...(a.Answer ?? []), ...(aaaa.Answer ?? [])];\n const ips = answers\n .filter((x) => x.type === 1 || x.type === 28)\n .map((x) => String(x.data ?? \"\"))\n .filter(Boolean);\n\n if (ips.length === 0) throw new Error(`no A/AAAA records resolved for ${host}`);\n const blocked = ips.filter(isNonPublicIp);\n if (blocked.length) throw new Error(`hostname ${host} resolved to blocked IP(s): ${blocked.join(\", \")}`);\n return [...new Set(ips)];\n}\n\nexport async function assertSafeUrl(value: string): Promise<{ url: string; host: string; ips: string[] }> {\n const url = new URL(value);\n if (![\"http:\", \"https:\"].includes(url.protocol)) throw new Error(\"only http/https URLs are allowed\");\n if (url.username || url.password) throw new Error(\"URL userinfo is blocked\");\n if (url.port && ![\"80\", \"443\"].includes(url.port)) throw new Error(`nonstandard port blocked: ${url.port}`);\n if (blockedHostname(url.hostname)) throw new Error(`blocked hostname: ${url.hostname}`);\n const ips = await resolvePublicIps(url.hostname);\n return { url: url.toString(), host: url.hostname, ips };\n}\n\nexport async function preflightTaskNetwork(task: BrowserTask) {\n const checked: Array<{ host: string; ips: string[] }> = [];\n const seen = new Set();\n\n const checkUrl = async (value: string) => {\n const result = await assertSafeUrl(value);\n if (!seen.has(result.host)) {\n seen.add(result.host);\n checked.push({ host: result.host, ips: result.ips });\n }\n };\n\n await checkUrl(task.targetUrl);\n for (const step of task.steps) {\n if (step.action === \"goto\" && step.url) await checkUrl(step.url);\n }\n for (const host of task.allowedHosts ?? []) {\n const clean = host.trim().toLowerCase();\n if (!clean || clean.includes(\"/\") || clean.includes(\"://\") || clean.includes(\"@\")) throw new Error(`invalid allowedHost: ${host}`);\n await checkUrl(`https://${clean}/`);\n }\n\n return checked;\n}\n",[],[657,999],"b13f2e19-c7f4-4bcb-935b-b449dfda8b0e","types.ts","01a077bc-2b99-740d-9881-31a5d93088f8",["D",1788715215771],"export type Risk = \"read_only\" | \"reversible_write\" | \"consequential\";\nexport type ProviderName = \"kernel\" | \"browserless\";\nexport type EvidenceRetention = \"minimal\" | \"full\";\n\nexport type Step =\n | { action: \"goto\"; url?: string }\n | { action: \"wait_for\"; selector: string; timeoutMs?: number }\n | { action: \"click\"; selector: string; waitForNavigation?: boolean }\n | { action: \"fill\"; selector: string; text: string }\n | { action: \"fill_secret\"; selector: string; envVar: string }\n | { action: \"type\"; selector: string; text: string; delayMs?: number }\n | { action: \"select\"; selector: string; value: string }\n | { action: \"extract_text\"; selector: string; key: string }\n | { action: \"extract_attribute\"; selector: string; attribute: string; key: string }\n | { action: \"expect_text\"; text: string }\n | { action: \"expect_url\"; contains: string };\n\nexport type BrowserTask = {\n runId: string;\n targetUrl: string;\n risk: Risk;\n approved?: boolean;\n purpose: string;\n allowedHosts?: string[];\n preferredProvider?: ProviderName;\n evidenceRetention?: EvidenceRetention;\n steps: Step[];\n};\n\nexport type BrowserReceipt = {\n runId: string;\n provider: ProviderName;\n status: \"PASS\" | \"PARTIAL\" | \"FAIL\" | \"BLOCKED\";\n finalUrl?: string;\n outputs?: Record;\n checks?: Array>;\n error?: string;\n durationMs?: number;\n providerMeta?: Record;\n};\n",[],[657,1006],"5257a923-09fd-451f-b4c5-eaa39b641d34","provider_health.ts","01a077bc-2b99-740d-9881-2d5b14823b37",["D",1788715215771],"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport type { BrowserReceipt, ProviderName } from \"./types.ts\";\nimport { POLICY } from \"./policy.ts\";\n\nexport async function providerAvailable(provider: ProviderName): Promise<{ available: boolean; reason?: string }> {\n const row = (await sqlite.execute({ sql: \"SELECT * FROM provider_health WHERE provider=?\", args: [provider] })).rows[0] as any;\n if (!row) return { available: true };\n if (row.circuit_state !== \"OPEN\") return { available: true };\n if (!row.open_until) return { available: false, reason: \"provider circuit open\" };\n const until = Date.parse(String(row.open_until));\n if (Number.isFinite(until) && Date.now() >= until) {\n await sqlite.execute({\n sql: \"UPDATE provider_health SET circuit_state='HALF_OPEN', updated_at=? WHERE provider=?\",\n args: [new Date().toISOString(), provider],\n });\n return { available: true };\n }\n return { available: false, reason: `provider circuit open until ${row.open_until}` };\n}\n\nexport async function recordProviderOutcome(provider: ProviderName, receipt: BrowserReceipt): Promise {\n const now = new Date().toISOString();\n if (receipt.status === \"PASS\" || receipt.status === \"PARTIAL\") {\n await sqlite.execute({\n sql: `UPDATE provider_health SET circuit_state='CLOSED', consecutive_failures=0, open_until=NULL,\n last_success_at=?, last_error=NULL, updated_at=? WHERE provider=?`,\n args: [now, now, provider],\n });\n return;\n }\n\n if (receipt.status === \"BLOCKED\") return;\n\n const row = (await sqlite.execute({ sql: \"SELECT consecutive_failures FROM provider_health WHERE provider=?\", args: [provider] })).rows[0] as any;\n const failures = Number(row?.consecutive_failures ?? 0) + 1;\n const shouldOpen = failures >= POLICY.providerCircuitFailureThreshold;\n const openUntil = shouldOpen ? new Date(Date.now() + POLICY.providerCircuitCooldownMs).toISOString() : null;\n await sqlite.execute({\n sql: `UPDATE provider_health SET circuit_state=?, consecutive_failures=?, open_until=?,\n last_failure_at=?, last_error=?, updated_at=? WHERE provider=?`,\n args: [shouldOpen ? \"OPEN\" : \"CLOSED\", failures, openUntil, now, receipt.error ?? receipt.status, now, provider],\n });\n}\n\nexport async function getProviderHealth() {\n return (await sqlite.execute(\"SELECT * FROM provider_health ORDER BY provider\")).rows;\n}\n",[],[657,1013],"7ad8bdee-273b-4d7c-abcf-bb2f5d966c86","policy.ts","01a077bc-2b99-740d-9881-280da64a368a",["D",1788715215771],"import type { Risk } from \"./types.ts\";\n\nexport const POLICY = {\n version: \"0.5.0\",\n maxAttemptsPerTask: 2,\n retryDelayMs: 10_000,\n runningLeaseMs: 90_000,\n readOnlyFallbackAllowed: true,\n browserTimeoutMs: 25_000,\n providerFailureWindow: 5,\n providerCircuitFailureThreshold: 3,\n providerCircuitCooldownMs: 15 * 60_000,\n} as const;\n\nexport function isTerminalStatus(status: string): boolean {\n return [\"PASS\", \"PARTIAL\", \"FAIL\", \"BLOCKED\", \"CANCELLED\"].includes(status);\n}\n\nexport function decideDisposition(risk: Risk, receiptStatus: string, attemptCount: number) {\n const retryable = risk === \"read_only\" && receiptStatus === \"FAIL\" && attemptCount < POLICY.maxAttemptsPerTask;\n return {\n retryable,\n taskStatus: retryable ? \"PENDING\" : receiptStatus,\n retryDelayMs: retryable ? POLICY.retryDelayMs : 0,\n } as const;\n}\n\nexport async function withTimeout(promise: Promise, ms: number, label: string): Promise {\n let timer: number | undefined;\n const timeout = new Promise((_, reject) => {\n timer = setTimeout(() => reject(new Error(`${label} timed out after ${ms}ms`)), ms);\n });\n try {\n return await Promise.race([promise, timeout]);\n } finally {\n if (timer !== undefined) clearTimeout(timer);\n }\n}\n",[],[657,1020],"7d31d3a0-a36d-43fe-acc2-6664bd750149","neuron_evolution.ts","7063f21a-aa18-11f1-84d5-1607ee4eb77e",8,["D",1788715736660],"export type SelectionCandidate = {\n agentId: string;\n netRevenue: number;\n operationallyEligible: boolean;\n terminal: boolean;\n};\n\nexport type SelectionState = \"INCUBATION\" | \"DEAD\" | \"SURVIVOR\";\n\nexport type SelectionResult = SelectionCandidate & {\n state: SelectionState;\n benchmark: number;\n rank?: number;\n offspringCount: number;\n};\n\nexport const MUTATION_ARCHETYPES = [\n \"faithful_replica\",\n \"tool_or_provider_mutation\",\n \"channel_or_market_mutation\",\n \"opposite_hypothesis\",\n \"causal_ablation\",\n] as const;\n\nexport function classifyCandidate(candidate: SelectionCandidate): SelectionResult {\n if (!candidate.operationallyEligible || !candidate.terminal) {\n return { ...candidate, state: \"INCUBATION\", benchmark: 0, offspringCount: 0 };\n }\n if (candidate.netRevenue <= 0) {\n return { ...candidate, state: \"DEAD\", benchmark: 0, offspringCount: 0 };\n }\n return { ...candidate, state: \"SURVIVOR\", benchmark: candidate.netRevenue, offspringCount: 1 };\n}\n\nexport function rankGeneration(candidates: SelectionCandidate[]): SelectionResult[] {\n const classified = candidates.map(classifyCandidate);\n const survivors = classified\n .filter((x) => x.state === \"SURVIVOR\")\n .sort((a, b) => b.netRevenue - a.netRevenue || a.agentId.localeCompare(b.agentId));\n\n const count = survivors.length;\n survivors.forEach((item, index) => {\n item.rank = index + 1;\n if (count === 1) item.offspringCount = 5;\n else {\n const percentile = index / count;\n item.offspringCount = percentile < 0.2 ? 5 : percentile < 0.5 ? 3 : 1;\n }\n });\n\n const byId = new Map(survivors.map((x) => [x.agentId, x]));\n return classified.map((x) => byId.get(x.agentId) ?? x);\n}\n\nexport function offspringPlan(parent: SelectionResult) {\n if (parent.state !== \"SURVIVOR\" || parent.offspringCount <= 0) return [];\n const count = Math.min(parent.offspringCount, MUTATION_ARCHETYPES.length);\n return Array.from({ length: count }, (_, index) => ({\n parentId: parent.agentId,\n childIndex: index + 1,\n mutation: MUTATION_ARCHETYPES[index],\n targetNetRevenue: parent.benchmark,\n }));\n}\n",[],[657,1027],"ab63c4ed-e481-4aab-bec5-fdae429eae8c","kaggriculture_opponent_market.ts","1f8c3fca-aa39-11f1-b627-1607ee4eb77e",37,["D",1788729774423],"import type { AgentFn } from \"./kaggriculture_agents_v1.ts\";\nimport { withSellPolicy, AFTER_TOWN_HOURS } from \"./kaggriculture_market_mutations.ts\";\n\nfunction publicCropTiles(farm: any, crop: string) {\n let n = 0;\n for (const row of farm?.tiles ?? []) for (const tile of row ?? []) {\n if (tile && typeof tile === \"object\" && tile.kind === \"PLANT\" && tile.crop === crop) n++;\n }\n return n;\n}\n\nexport function opponentAwareCarrotMarket(baseFactory: () => AgentFn, threshold = 3): AgentFn {\n const aggressive = baseFactory(); // original immediate SELL-all behavior\n const reserve = withSellPolicy(baseFactory(), {\n name: \"reserve60_after\",\n item: \"CARROT\",\n allowedHours: AFTER_TOWN_HOURS,\n lotSize: 8,\n reservePrice: 60,\n forceShedLoad: 85,\n liquidationDay: 29,\n });\n\n return (obs: any) => {\n const me = Number(obs?.player ?? 0);\n const farms = obs?.farms ?? [];\n const opponent = farms.length === 2 ? farms[1 - me] : null;\n const exposure = publicCropTiles(opponent, \"CARROT\");\n // If the opponent is visibly committed to carrots, withholding supply raises\n // THEIR sale price too. Do not subsidize a same-product rival.\n return exposure >= threshold ? aggressive(obs) : reserve(obs);\n };\n}\n",[],[657,1035],"9eb933ab-1945-4b60-8472-d88a83dc7ac7","kaggriculture_market_mutations.ts","f05a1d3a-aa38-11f1-bcf5-1607ee4eb77e",33,["D",1788729695212],"import type { AgentFn } from \"./kaggriculture_agents_v1.ts\";\n\nexport type SellPolicy = {\n name: string;\n item?: string;\n allowedHours?: number[] | null;\n lotSize?: number | null;\n reservePrice?: number | null;\n forceShedLoad?: number;\n liquidationDay?: number;\n};\n\nfunction shedTotal(shed: Record | undefined) {\n return Object.values(shed ?? {}).reduce((a, b) => a + Number(b || 0), 0);\n}\n\nexport function withSellPolicy(base: AgentFn, policy: SellPolicy): AgentFn {\n const item = policy.item ?? \"CARROT\";\n const allowed = policy.allowedHours ? new Set(policy.allowedHours) : null;\n const forceLoad = policy.forceShedLoad ?? 80;\n const liquidationDay = policy.liquidationDay ?? 29;\n\n return (obs: any) => {\n const action = base(obs);\n const market = Array.isArray(action?.market) ? action.market.filter((o: any) => !(Array.isArray(o) && o[0] === \"SELL\" && o[1] === item)) : [];\n const shed = obs?.private?.shed ?? {};\n const qty = Math.max(0, Math.floor(Number(shed[item] ?? 0)));\n if (qty <= 0) return { ...action, market };\n\n const day = Number(obs?.day ?? 0);\n const hour = Number(obs?.hour ?? 0);\n const price = Number(obs?.market?.prices?.[item] ?? 0);\n const mustLiquidate = day >= liquidationDay || shedTotal(shed) >= forceLoad;\n const timeOk = !allowed || allowed.has(hour);\n const priceOk = policy.reservePrice == null || price >= policy.reservePrice;\n\n if ((mustLiquidate || (timeOk && priceOk)) && market.length < 10) {\n const lot = mustLiquidate || policy.lotSize == null ? qty : Math.min(qty, policy.lotSize);\n // SELL first so proceeds can finance any later BUY_SEED/BUY_PRODUCT order.\n market.unshift([\"SELL\", item, lot]);\n }\n return { ...action, market: market.slice(0, 10) };\n };\n}\n\nexport const AFTER_TOWN_HOURS = [1, 5, 9, 13, 17, 21];\nexport const BEFORE_TOWN_HOURS = [0, 4, 8, 12, 16, 20];\n",[],[657,1043],"d48c3806-d332-49ea-af48-0f7e969c6f77","kaggriculture_livestock_portfolio.ts","0136cb6e-aa41-11f1-9721-1607ee4eb77e",70,["D",1788733499893],"export type AnimalName='COW'|'SHEEP'|'GOOSE';\nexport type ProductName='MILK'|'WOOL'|'EGG'|'WHEAT';\n\nexport const ANIMAL_ECONOMICS:Record}>={\n GOOSE:{cost:300,first:4,interval:1,product:'EGG'},\n COW:{cost:400,first:8,interval:2,product:'MILK'},\n SHEEP:{cost:500,first:6,interval:3,product:'WOOL'},\n};\n\nconst MARKET:any={\n WHEAT:{base:25,I0:10000,T:400,below_func:'sqrt',below_target:.80,above_func:'log',above_target:.20},\n EGG:{base:50,I0:10000,T:332,below_func:'hinge',below_target:.40,above_func:'log',above_target:.20},\n MILK:{base:160,I0:10000,T:122,below_func:'sqrt',below_target:.60,above_func:'linear',above_target:1.60},\n WOOL:{base:200,I0:10000,T:105,below_func:'log',below_target:.20,above_func:'sq',above_target:3.20},\n};\nconst SHOPS:Record={\n BAKERY:['EGG','WHEAT'],PIZZA_SHOP:['MILK','TOMATO','WHEAT'],BRUNCH_SPOT:['EGG','WHEAT','STRAWBERRY'],YARN_STORE:['WOOL'],ICE_CREAM_SHOP:['STRAWBERRY','MILK','WHEAT'],PET_CAFE:['CARROT'],SMOOTHIE_SHOP:['STRAWBERRY','MILK'],FARMERS_MARKET:['WHEAT','CARROT','TOMATO','STRAWBERRY']\n};\nconst SHOP_NAMES=Object.keys(SHOPS).sort();\nconst hingeGain=8;\nfunction shape(fn:string,x:number,T:number){x=Math.max(0,x);if(fn==='linear')return x;if(fn==='sq')return x*x;if(fn==='sqrt')return Math.sqrt(x);if(fn==='log')return Math.log(1+x);if(fn==='hinge'){const u=x/T;return u+hingeGain*Math.max(0,u-1)**2;}return x;}\nexport function marketPrice(item:ProductName,inventory:number){const p=MARKET[item];const x=Math.abs(inventory-p.I0);const below=inventorys+shopMultiplier(sh,item),0)*shopTicks;\n // Town center consumes every product except fertilizer once per day.\n const centerTicks=Math.max(0,Math.floor((episodeSteps-1)/24)-Math.ceil(step/24)+1);\n demand += centerTicks;\n // Future shop slots unlock at end of days 3,6,...24. Expected contribution is uniform over 8 shop types.\n const avgMult=SHOP_NAMES.reduce((s,sh)=>s+shopMultiplier(sh,item),0)/SHOP_NAMES.length;\n for(const unlockDay of [3,6,9,12,15,18,21,24]){\n if(unlockDay<=day || known.length>=8)continue;\n const unlockStep=unlockDay*24;\n const ticks=Math.max(0,Math.floor((episodeSteps-1)/4)-Math.ceil(unlockStep/4)+1);\n demand += avgMult*ticks;\n }\n return demand;\n}\n\nexport function caredProductionUnits(animal:AnimalName,currentDay:number,horizonDay=30){\n const a=ANIMAL_ECONOMICS[animal];const first=currentDay+a.first;if(first>=horizonDay)return 0;\n const events=1+Math.floor((horizonDay-1-first)/a.interval);\n // With daily feed+care, pending care bonus makes productive refreshes approximately 2 units/event.\n return Math.max(0,2*events);\n}\n\nexport function visibleAnimalSupplyRemaining(farm:any,animal:AnimalName,currentDay:number,horizonDay=30){\n const a=ANIMAL_ECONOMICS[animal];let units=0;\n for(const row of farm?.tiles??[])for(const t of row??[]){if(!t||typeof t!=='object'||t.animal!==animal)continue;const placed=Number(t.placed_day??currentDay);const first=placed+a.first;let next=first;while(next=horizonDay)continue;units+=2*(1+Math.floor((horizonDay-1-next)/a.interval));}\n return units;\n}\n\nexport type AnimalScoreInput={\n obs:any; animal:AnimalName; cashBuffer?:number; horizonDay?:number; discountPerDay?:number; strategicWeight?:number;\n};\n\n/** Marginal NPV-like score for purchasing one more animal now. Designed for ranking, not accounting truth. */\nexport function scoreAnimalInvestment(x:AnimalScoreInput){\n const {obs,animal}=x;const a=ANIMAL_ECONOMICS[animal];const day=Number(obs?.day??0),h=x.horizonDay??30;\n const product=a.product;const inv=Number(obs?.market?.inventory?.[product]??10000);const wheatInv=Number(obs?.market?.inventory?.WHEAT??10000);\n const currentPrice=marketPrice(product,inv);const wheatPrice=marketPrice('WHEAT',wheatInv);\n const units=caredProductionUnits(animal,day,h);const feedDays=Math.max(0,h-day);\n const townDemand=expectedTownDemandRemaining(obs,product);\n const me=Number(obs?.player??0),farms=obs?.farms??[],mine=farms?.[me]??null,opp=farms.length===2?farms[1-me]:null;\n const ownCommittedSupply=visibleAnimalSupplyRemaining(mine,animal,day,h);\n const opponentSupply=visibleAnimalSupplyRemaining(opp,animal,day,h);\n // Cournot-like marginal accounting: compare the projected market before vs after the extra animal.\n // Extra supply changes the price received on OUR already-committed output and on the rival's output too.\n const baseProjectedInv=inv - 0.5*townDemand + 0.5*ownCommittedSupply + 0.5*opponentSupply;\n const priceBeforeMarginal=marketPrice(product,baseProjectedInv);\n const projectedInv=baseProjectedInv + 0.5*units;\n const projectedPrice=marketPrice(product,projectedInv);\n const avgPrice=(currentPrice+projectedPrice)/2;\n const disc=Math.pow(x.discountPerDay??0.997,Math.max(0,a.first));\n const newUnitsRevenue=units*avgPrice*disc;\n const ownPriceImpact=0.5*ownCommittedSupply*(projectedPrice-priceBeforeMarginal)*disc;\n const rivalPriceImpact=0.5*opponentSupply*(projectedPrice-priceBeforeMarginal)*disc;\n const relativeMarketContribution=newUnitsRevenue+ownPriceImpact-(x.strategicWeight??1.0)*rivalPriceImpact;\n const feedCost=feedDays*wheatPrice;\n const cash=Number(farms?.[me]?.money??0),buffer=x.cashBuffer??400;\n const postPurchaseCash=cash-a.cost;\n // Financial-feasibility gate mirrored from the reference scheduler: a positive-NPV animal is useless if the farm cannot fund its feed float and capital sequence.\n let flock=0;for(const row of mine?.tiles??[])for(const t of row??[])if(t&&typeof t==='object'&&t.animal)flock++;\n for(const k of ['COW','SHEEP','GOOSE'])flock+=Number(obs?.private?.shed?.[k]??0);\n const boughtLand=Math.max(0,(mine?.unlocked_quadrants??['NW']).length-1);\n const landPrices=[1000,2000,4000];\n const landReserve=(flock>=10 && boughtLand<2)?landPrices[boughtLand]:0;\n const feedFloatDays=16;\n const requiredLiquidity=a.cost+buffer+landReserve+(flock+1)*wheatPrice*feedFloatDays;\n const financeable=cash>=requiredLiquidity;\n const liquidityPenalty=financeable?0:1e6+(requiredLiquidity-cash)*1000;\n const net=relativeMarketContribution-a.cost-feedCost-liquidityPenalty;\n const timeToCash=a.first;\n return {animal,product,day,units,events:units/2,timeToCash,currentPrice,priceBeforeMarginal,projectedPrice,townDemand,ownCommittedSupply,opponentSupply,feedDays,wheatPrice,newUnitsRevenue,ownPriceImpact,rivalPriceImpact,relativeMarketContribution,animalCost:a.cost,feedCost,flock,boughtLand,landReserve,requiredLiquidity,financeable,liquidityPenalty,net,roi:net/Math.max(1,a.cost),postPurchaseCash};\n}\n\nexport function rankAnimalInvestments(obs:any,opts?:Omit){\n return (['COW','SHEEP','GOOSE'] as AnimalName[]).map(animal=>scoreAnimalInvestment({obs,animal,...opts})).sort((a,b)=>b.net-a.net);\n}\n\nexport function choosePastureAnimal(obs:any,opts?:Omit){\n const xs=(['COW','SHEEP'] as AnimalName[]).map(animal=>scoreAnimalInvestment({obs,animal,...opts})).sort((a,b)=>b.net-a.net);\n return {choice:xs[0].net>0?xs[0].animal:null,ranking:xs};\n}\n",[],[657,1051],"841bfd60-3bc8-4914-a54e-a0f010480893","kaggriculture_league.ts","476f455e-aa3f-11f1-8e55-1607ee4eb77e",48,["D",1788732418278],"export type MatchResult = \"WIN\" | \"LOSS\" | \"TIE\";\nexport type LeagueRole = \"MAIN\" | \"HISTORICAL\" | \"EXPLOITER\" | \"SPECIALIST\" | \"REFERENCE\";\n\nexport type LeagueMember = {\n id: string;\n role: LeagueRole;\n frozen?: boolean;\n lineage?: string;\n};\n\nexport type PairStats = { wins: number; losses: number; ties: number };\n\nexport class EmpiricalLeague {\n members = new Map();\n private pairs = new Map();\n\n add(member: LeagueMember) {\n this.members.set(member.id, { ...member });\n }\n\n private key(a: string, b: string) { return `${a}→${b}`; }\n\n record(a: string, b: string, result: MatchResult) {\n if (!this.members.has(a) || !this.members.has(b)) throw new Error(\"UNKNOWN_MEMBER\");\n const ab = this.pairs.get(this.key(a,b)) ?? { wins: 0, losses: 0, ties: 0 };\n const ba = this.pairs.get(this.key(b,a)) ?? { wins: 0, losses: 0, ties: 0 };\n if (result === \"WIN\") { ab.wins++; ba.losses++; }\n else if (result === \"LOSS\") { ab.losses++; ba.wins++; }\n else { ab.ties++; ba.ties++; }\n this.pairs.set(this.key(a,b), ab);\n this.pairs.set(this.key(b,a), ba);\n }\n\n stats(a: string, b: string): PairStats {\n return { ...(this.pairs.get(this.key(a,b)) ?? { wins: 0, losses: 0, ties: 0 }) };\n }\n\n /** Smoothed score in [0,1]. Ties count half; Beta(1,1)-style pseudocounts prevent zero-information extremes. */\n score(a: string, b: string): number {\n const s = this.stats(a,b);\n return (s.wins + 0.5*s.ties + 1) / (s.wins + s.losses + s.ties + 2);\n }\n\n /**\n * PFSP-like opponent weighting: prioritize opponents the focal policy does not reliably beat.\n * uncertaintyBonus keeps under-tested opponents alive so the pool does not collapse to one nemesis.\n */\n pfspWeights(focal: string, opponents: string[], alpha = 2, uncertaintyBonus = 0.25) {\n const raw = opponents.map(id => {\n const s = this.stats(focal,id);\n const n = s.wins+s.losses+s.ties;\n const p = this.score(focal,id);\n const difficulty = Math.pow(Math.max(1e-6, 1-p), alpha);\n const uncertainty = 1/Math.sqrt(n+1);\n return { id, weight: difficulty + uncertaintyBonus*uncertainty, n, p };\n });\n const total = raw.reduce((a,x)=>a+x.weight,0) || 1;\n return raw.map(x => ({ ...x, probability: x.weight/total }));\n }\n\n /** Weaknesses are opponents against which focal has lowest smoothed score. */\n weaknesses(focal: string, limit=5) {\n return [...this.members.keys()]\n .filter(id => id !== focal)\n .map(id => ({ id, score: this.score(focal,id), stats: this.stats(focal,id) }))\n .sort((a,b)=>a.score-b.score)\n .slice(0,limit);\n }\n\n /** Preserve frozen historical snapshots instead of overwriting them: catastrophic forgetting detector/control. */\n freezeSnapshot(sourceId: string, snapshotId: string) {\n const src = this.members.get(sourceId);\n if (!src) throw new Error(\"UNKNOWN_SOURCE\");\n this.add({ id: snapshotId, role: \"HISTORICAL\", frozen: true, lineage: src.lineage ?? sourceId });\n }\n\n payoffMatrix(ids: string[]) {\n return ids.map(a => ids.map(b => a===b ? 0 : 2*this.score(a,b)-1));\n }\n}\n\n/**\n * Regret-matching approximation of a symmetric zero-sum meta-strategy.\n * Useful as a low-cost PSRO meta-solver over an empirical payoff matrix.\n */\nexport function regretMatchingMix(payoff: number[][], iterations=20000) {\n const n = payoff.length;\n if (!n || payoff.some(r=>r.length!==n)) throw new Error(\"SQUARE_MATRIX_REQUIRED\");\n let regrets = Array(n).fill(0);\n let strategySum = Array(n).fill(0);\n let strategy = Array(n).fill(1/n);\n\n for (let t=0;tMath.max(0,r));\n const z = pos.reduce((a,b)=>a+b,0);\n strategy = z>1e-12 ? pos.map(x=>x/z) : Array(n).fill(1/n);\n for (let i=0;i row.reduce((s,v,j)=>s+v*strategy[j],0));\n const currentValue = strategy.reduce((s,p,i)=>s+p*actionValues[i],0);\n for (let i=0;ia+b,0) || 1;\n return strategySum.map(x=>x/z);\n}\n\nexport function mixEntropy(mix:number[]) {\n return -mix.filter(p=>p>0).reduce((s,p)=>s+p*Math.log(p),0);\n}\n",[],[657,1059],"336a164c-cacf-4eed-b42f-572da6afe34e","kaggriculture_farm_economics.ts","5a82cd1e-aa3f-11f1-8146-1607ee4eb77e",50,["D",1788732450327],"export function mean(xs:number[]) {\n return xs.length ? xs.reduce((a,b)=>a+b,0)/xs.length : NaN;\n}\n\n/** Lower-tail CVaR for profit distributions. alpha=0.1 means average of worst 10%. */\nexport function lowerTailCVaR(xs:number[], alpha=0.1) {\n if (!xs.length) return NaN;\n const a=Math.min(1,Math.max(1/xs.length,alpha));\n const sorted=[...xs].sort((x,y)=>x-y);\n const k=Math.max(1,Math.ceil(sorted.length*a));\n return mean(sorted.slice(0,k));\n}\n\nexport function riskAdjustedProfit(xs:number[], lambda=0.25, alpha=0.1) {\n const m=mean(xs), c=lowerTailCVaR(xs,alpha);\n return m - lambda*(m-c);\n}\n\n/** Finite-difference shadow value: extra net profit generated by one extra unit of a resource. */\nexport function shadowValue(baseProfit:number, expandedProfit:number, extraUnits:number, extraCost=0) {\n if (extraUnits<=0) throw new Error(\"POSITIVE_EXTRA_UNITS_REQUIRED\");\n return (expandedProfit-baseProfit-extraCost)/extraUnits;\n}\n\n/**\n * Generic sell-vs-hold decision. Holding preserves an option to sell later but has operating/opportunity cost.\n * strategicExternality is positive when withholding benefits the opponent or harms our win probability.\n */\nexport function sellHoldDecision(x:{\n spotPrice:number;\n expectedFuturePrice:number;\n holdingCost:number;\n spoilageProbability?:number;\n salvageIfSpoiled?:number;\n discountFactor?:number;\n strategicExternality?:number;\n optionFlexibilityValue?:number;\n}) {\n const spoil=Math.min(1,Math.max(0,x.spoilageProbability??0));\n const salvage=x.salvageIfSpoiled??0;\n const disc=x.discountFactor??1;\n const futureExpected=(1-spoil)*x.expectedFuturePrice + spoil*salvage;\n const holdValue=disc*futureExpected - x.holdingCost + (x.optionFlexibilityValue??0) - (x.strategicExternality??0);\n return {\n sellNowValue:x.spotPrice,\n holdValue,\n action:x.spotPrice>=holdValue ? \"SELL\" as const : \"HOLD\" as const,\n threshold:holdValue,\n advantage:x.spotPrice-holdValue,\n };\n}\n\n/** Reserve is economically valuable if it prevents an interruption whose expected damage exceeds carrying cost. */\nexport function reserveOptionValue(x:{\n interruptionProbability:number;\n lossIfInterrupted:number;\n reserveCarryingCost:number;\n reservePurchaseCost:number;\n recoveryValue?:number;\n}) {\n const p=Math.min(1,Math.max(0,x.interruptionProbability));\n const avoidedLoss=p*x.lossIfInterrupted;\n const benefit=avoidedLoss+(x.recoveryValue??0);\n const cost=x.reserveCarryingCost+x.reservePurchaseCost;\n return { benefit, cost, netOptionValue:benefit-cost, shouldHoldReserve:benefit>cost };\n}\n\nexport type ResourceBottleneck = {\n resource:string;\n shadowValue:number;\n utilization:number;\n};\n\n/** Prioritize binding resources with positive marginal value; negative shadow value means expansion destroys value. */\nexport function rankBottlenecks(xs:ResourceBottleneck[]) {\n return [...xs].sort((a,b)=>{\n const sa=a.shadowValue*Math.max(0,a.utilization);\n const sb=b.shadowValue*Math.max(0,b.utilization);\n return sb-sa;\n });\n}\n\n/** Finite-horizon liquidation pressure. 0 = no pressure; 1 = liquidate aggressively. */\nexport function liquidationPressure(turnsRemaining:number, leadTime:number, terminalSalvage:number, currentPrice:number) {\n if (turnsRemaining<=0) return 1;\n const horizonRisk=Math.max(0,Math.min(1,(leadTime+1)/turnsRemaining));\n const salvagePenalty=currentPrice<=0 ? 1 : Math.max(0,Math.min(1,1-terminalSalvage/currentPrice));\n return Math.max(0,Math.min(1,0.65*horizonRisk+0.35*salvagePenalty));\n}\n\n/**\n * Capital-efficiency metric: return generated per unit of scarce capital tied up.\n * Useful when two strategies have similar win rate but one requires much larger herd/land/feed commitments.\n */\nexport function returnOnCommittedCapital(netIncrementalProfit:number, committedCapital:number) {\n if (committedCapital<=0) return netIncrementalProfit>0 ? Infinity : 0;\n return netIncrementalProfit/committedCapital;\n}\n",[],[657,1067],"e2b3db4d-0adf-4758-9976-66328c59ed9d","kaggriculture_engine_loader.ts","6074d468-aa37-11f1-8d3f-1607ee4eb77e",20,["D",1788729024315],"const RAW_ROOT = \"https://raw.githubusercontent.com/Kaggle/kaggle-environments/master/kaggle_environments/envs/kaggriculture/\";\nconst ENGINE_BASE = `${RAW_ROOT}visualizer/playable/src/engine/`;\nconst SPEC_URL = `${RAW_ROOT}kaggriculture.json`;\nconst ENGINE_NAMES = [\"types\", \"constants\", \"market\", \"rng\", \"state\", \"interpreter\"] as const;\ntype EngineName = typeof ENGINE_NAMES[number];\n\nfunction toDataUrl(source: string): string {\n const bytes = new TextEncoder().encode(source);\n let binary = \"\";\n for (let i = 0; i < bytes.length; i += 0x8000) {\n binary += String.fromCharCode(...bytes.subarray(i, i + 0x8000));\n }\n return `data:application/typescript;base64,${btoa(binary)}`;\n}\n\nfunction stripTypeImports(src: string): string {\n return src.replace(/import\\s+type\\s+\\{[\\s\\S]*?\\}\\s+from\\s+['\"][^'\"]+['\"];?\\s*/g, \"\");\n}\n\nexport async function loadOfficialKaggricultureEngine() {\n const raw = new Map();\n for (const name of ENGINE_NAMES) {\n const res = await fetch(`${ENGINE_BASE}${name}.ts`);\n if (!res.ok) throw new Error(`fetch official ${name}.ts failed: ${res.status}`);\n raw.set(name, await res.text());\n }\n const specRes = await fetch(SPEC_URL);\n if (!specRes.ok) throw new Error(`fetch official kaggriculture.json failed: ${specRes.status}`);\n const specText = await specRes.text();\n JSON.parse(specText);\n\n const urls = new Map();\n for (const name of ENGINE_NAMES) {\n let src = stripTypeImports(raw.get(name)!);\n if (name === \"constants\") {\n src = src.replace(\n /import\\s+spec\\s+from\\s+['\"]\\.\\.\\/\\.\\.\\/\\.\\.\\/\\.\\.\\/kaggriculture\\.json['\"];?\\s*/,\n `const spec = ${specText};\\n`,\n );\n }\n src = src.replace(\n /import\\s+\\{([\\s\\S]*?)\\}\\s+from\\s+['\"]\\.\\/([A-Za-z0-9_-]+)['\"];?\\s*/g,\n (_all, symbols: string, dep: string) => {\n const depUrl = urls.get(dep as EngineName);\n if (!depUrl) throw new Error(`${name}: dependency ${dep} not compiled`);\n return `import {${symbols}} from ${JSON.stringify(depUrl)};\\n`;\n },\n );\n const unresolved = [...src.matchAll(/from\\s+['\"](\\.\\.?\\/[^'\"]+)['\"]/g)].map((m) => m[1]);\n if (unresolved.length) throw new Error(`${name}: unresolved imports ${unresolved.join(\", \")}`);\n urls.set(name, toDataUrl(src));\n }\n\n const [types, constants, market, rng, state, interpreter] = await Promise.all([\n import(urls.get(\"types\")!),\n import(urls.get(\"constants\")!),\n import(urls.get(\"market\")!),\n import(urls.get(\"rng\")!),\n import(urls.get(\"state\")!),\n import(urls.get(\"interpreter\")!),\n ]);\n\n return {\n types,\n constants,\n market,\n rng,\n state,\n interpreter,\n sourceMeta: Object.fromEntries(ENGINE_NAMES.map((name) => [name, { bytes: raw.get(name)!.length }])),\n };\n}\n\nexport function observationFor(state: any, player: number) {\n return {\n player,\n step: state.step,\n day: state.day,\n hour: state.hour,\n numAgents: state.numAgents,\n farms: state.farms,\n private: state.privates[player],\n market: state.market,\n town: state.town,\n };\n}\n",[],[657,1075],"6835ce70-1a2f-421b-bb9e-5a0f960202ef","kaggriculture_bayesian_router.ts","505ca7ba-aa3f-11f1-8cab-1607ee4eb77e",49,["D",1788732433289],"export type Hypothesis = { id: string; prior: number };\nexport type LikelihoodEvidence = { name: string; likelihood: Record };\n\nexport class BayesianRouter {\n private posterior = new Map();\n private evidenceCount = 0;\n\n constructor(hypotheses: Hypothesis[]) {\n if (!hypotheses.length) throw new Error(\"EMPTY_HYPOTHESES\");\n const sum = hypotheses.reduce((s,h)=>s+Math.max(0,h.prior),0);\n if (sum <= 0) throw new Error(\"NONPOSITIVE_PRIOR_SUM\");\n for (const h of hypotheses) this.posterior.set(h.id, Math.max(0,h.prior)/sum);\n }\n\n distribution() {\n return [...this.posterior.entries()].map(([id,p])=>({id,p})).sort((a,b)=>b.p-a.p);\n }\n\n update(ev: LikelihoodEvidence, floor=1e-6) {\n const before = new Map(this.posterior);\n let z = 0;\n for (const [id,p] of this.posterior) {\n const like = Math.max(floor, Math.min(1, ev.likelihood[id] ?? floor));\n const q = p * like;\n this.posterior.set(id,q);\n z += q;\n }\n if (z <= 0) throw new Error(\"ZERO_POSTERIOR_MASS\");\n for (const [id,q] of this.posterior) this.posterior.set(id,q/z);\n this.evidenceCount++;\n return {\n evidence: ev.name,\n before: [...before.entries()].map(([id,p])=>({id,p})),\n after: this.distribution(),\n kl: klDivergence(this.posterior,before),\n entropy: this.entropy(),\n };\n }\n\n entropy() {\n let h=0;\n for (const p of this.posterior.values()) if (p>0) h -= p*Math.log(p);\n return h;\n }\n\n confidence() { return this.distribution()[0]?.p ?? 0; }\n best() { return this.distribution()[0]; }\n count() { return this.evidenceCount; }\n}\n\nfunction klDivergence(p: Map, q: Map) {\n let out=0;\n for (const [id,pv] of p) {\n const qv=Math.max(1e-12,q.get(id)??1e-12);\n if (pv>0) out += pv*Math.log(pv/qv);\n }\n return out;\n}\n\nexport type MacroReplanInput = {\n previousBest?: string;\n currentBest: string;\n posteriorConfidence: number;\n informationGainKL: number;\n event: \"NEW_DAY\"|\"NEW_SHOP\"|\"PRICE_SHIFT\"|\"OPPONENT_SHIFT\"|\"HORIZON_PHASE\"|\"NO_EVENT\";\n};\n\n/** Event-driven control: avoid turn-by-turn thrashing. */\nexport function shouldReplanMacro(x: MacroReplanInput) {\n if (x.event === \"NO_EVENT\") return false;\n if (x.previousBest && x.previousBest !== x.currentBest && x.posteriorConfidence >= 0.60) return true;\n if (x.informationGainKL >= 0.08 && x.posteriorConfidence >= 0.55) return true;\n if (x.event === \"HORIZON_PHASE\") return true;\n return false;\n}\n\n/** Simple feature-to-likelihood adapter for opponent family classification. */\nexport function opponentFamilyLikelihood(features: {\n cropShare:number;\n livestockCount:number;\n recentSellIntensity:number;\n landUnlocked:number;\n}) {\n const clamp=(x:number)=>Math.max(0.02,Math.min(0.98,x));\n const crop = clamp(0.25 + 0.65*features.cropShare - 0.03*features.livestockCount);\n const livestock = clamp(0.15 + 0.055*features.livestockCount + 0.05*features.landUnlocked - 0.35*features.cropShare);\n const marketHeavy = clamp(0.15 + 0.75*features.recentSellIntensity);\n const mixed = clamp(1 - Math.max(crop,livestock,marketHeavy)*0.72);\n return { CROP: crop, LIVESTOCK: livestock, MARKET_HEAVY: marketHeavy, MIXED: mixed };\n}\n",[],[657,1083],"81eab083-914b-4c12-a6ee-eb5d9b8f9e0b","kaggriculture_agents_v1.ts","7605724c-aa37-11f1-aaa8-1607ee4eb77e",21,["D",1788729060447],"export type AgentFn = (obs: any) => any;\n\nconst CROPS: Record = {\n WHEAT: { seed: 10, first: 2, maxDay: 4, maxYield: 6, ongoing: false },\n CARROT: { seed: 20, first: 2, maxDay: 3, maxYield: 4, ongoing: false },\n TOMATO: { seed: 50, first: 8, maxDay: 8, maxYield: 4, ongoing: true },\n STRAWBERRY: { seed: 100, first: 10, maxDay: 10, maxYield: 4, ongoing: true },\n MELON: { seed: 80, first: 10, maxDay: 12, maxYield: 6, ongoing: false },\n};\n\nconst PASS = [\"PASS\"];\nconst MEM = new Map }>();\n\nfunction manhattan(a: [number, number], b: [number, number]) {\n return Math.abs(a[0] - b[0]) + Math.abs(a[1] - b[1]);\n}\n\nfunction stepToward(pos: [number, number], target: [number, number]) {\n const dx = target[0] - pos[0];\n const dy = target[1] - pos[1];\n if (Math.abs(dx) >= Math.abs(dy) && dx !== 0) return [dx > 0 ? \"EAST\" : \"WEST\"];\n if (dy !== 0) return [dy > 0 ? \"SOUTH\" : \"NORTH\"];\n return PASS;\n}\n\nfunction ownedCoords(farm: any): Array<[number, number]> {\n const out: Array<[number, number]> = [];\n for (let y = 0; y < farm.tiles.length; y++) {\n for (let x = 0; x < farm.tiles[y].length; x++) {\n if (farm.tiles[y][x] !== \"LOCKED\") out.push([x, y]);\n }\n }\n return out;\n}\n\nfunction tileTask(tile: any, day: number, hour: number, crop: string): [number, string] | null {\n if (tile === null) return hour < 23 ? [60, \"PLANT\"] : null;\n if (tile === \"LOCKED\" || typeof tile !== \"object\") return null;\n if (tile.kind === \"WEED\") return [50, \"DIG\"];\n if (tile.kind !== \"PLANT\" || tile.crop !== crop) return null;\n\n const age = day - Number(tile.planted_day ?? day);\n const cfg = CROPS[crop];\n const watered = Boolean(tile.watered_today);\n const streak = Number(tile.consecutive_unwatered ?? 0);\n const yieldUnits = Number(tile.yield_units ?? 0);\n\n if (!watered && (streak >= 1 || hour >= 18)) return [5, \"WATER\"];\n if (yieldUnits > 0 && age >= cfg.first) {\n if (!cfg.ongoing && age <= cfg.maxDay && !watered && hour < 22) return [8, \"WATER\"];\n if (age >= cfg.maxDay || hour >= 22) return [10, \"HARVEST\"];\n }\n if (!watered) return [20, \"WATER\"];\n if (yieldUnits > 0 && age >= cfg.first) return [25, \"HARVEST\"];\n return null;\n}\n\nfunction collectTasks(farm: any, day: number, hour: number, crop: string, maxTiles: number | null) {\n let coords = ownedCoords(farm);\n if (maxTiles !== null) {\n const h = Math.floor(farm.tiles.length / 2);\n const shedCorner: [number, number] = [h - 1, h - 1];\n coords = coords.sort((a, b) => manhattan(a, shedCorner) - manhattan(b, shedCorner) || a[1] - b[1] || a[0] - b[0]).slice(0, maxTiles);\n }\n const tasks: Array<{ pri: number; kind: string; target: [number, number] }> = [];\n for (const [x, y] of coords) {\n const t = tileTask(farm.tiles[y][x], day, hour, crop);\n if (t) tasks.push({ pri: t[0], kind: t[1], target: [x, y] });\n }\n tasks.sort((a, b) => a.pri - b.pri || a.target[1] - b.target[1] || a.target[0] - b.target[0]);\n return tasks;\n}\n\nfunction assignmentValid(farm: any, item: { kind: string; target: [number, number] }, day: number, hour: number, crop: string) {\n const [x, y] = item.target;\n if (y < 0 || y >= farm.tiles.length || x < 0 || x >= farm.tiles[y].length) return false;\n const t = tileTask(farm.tiles[y][x], day, hour, crop);\n return Boolean(t && t[1] === item.kind);\n}\n\nfunction chooseAssignments(player: number, farm: any, day: number, hour: number, crop: string, positions: Array<[number, number]>, tasks: any[], persistent: boolean) {\n const key = `${player}:${crop}`;\n if (day === 0 && hour === 0) MEM.delete(key);\n let state = MEM.get(key) ?? { day, assign: new Map() };\n if (state.day !== day) state = { day, assign: new Map() };\n MEM.set(key, state);\n\n const assigns = persistent ? state.assign : new Map();\n for (const [uid, item] of [...assigns.entries()]) {\n if (uid >= positions.length || !assignmentValid(farm, item, day, hour, crop)) assigns.delete(uid);\n }\n const claimed = new Set([...assigns.values()].map((v: any) => `${v.target[0]},${v.target[1]}`));\n const available = tasks.filter((t: any) => !claimed.has(`${t.target[0]},${t.target[1]}`));\n\n for (let uid = 0; uid < positions.length; uid++) {\n if (assigns.has(uid) || available.length === 0) continue;\n let best = 0;\n for (let i = 1; i < available.length; i++) {\n const a = available[i], b = available[best];\n const ka = [a.pri, manhattan(positions[uid], a.target), a.target[1], a.target[0]];\n const kb = [b.pri, manhattan(positions[uid], b.target), b.target[1], b.target[0]];\n if (ka[0] < kb[0] || (ka[0] === kb[0] && (ka[1] < kb[1] || (ka[1] === kb[1] && (ka[2] < kb[2] || (ka[2] === kb[2] && ka[3] < kb[3])))))) best = i;\n }\n const chosen = available.splice(best, 1)[0];\n assigns.set(uid, { kind: chosen.kind, target: chosen.target });\n }\n if (persistent) state.assign = assigns;\n return new Map(assigns);\n}\n\nfunction marketOrders(obs: any, farm: any, priv: any, crop: string, seedBuffer: number, targetHands: number) {\n const out: any[] = [];\n const hour = Number(obs.hour ?? 0);\n const currentHands = (farm.hands ?? []).length;\n const hires = Math.max(0, targetHands - currentHands);\n if (hour === 0 && hires > 0) {\n for (let i = 0; i < Math.min(hires, 10); i++) out.push([\"HIRE\"]);\n if (out.length >= 10) return out;\n }\n const qty = Number(priv.shed?.[crop] ?? 0);\n if (qty > 0 && out.length < 10) out.push([\"SELL\", crop, qty]);\n const seeds = Number(priv.seeds?.[crop] ?? 0);\n const missing = Math.max(0, seedBuffer - seeds);\n const affordable = Math.floor(Number(farm.money ?? 0) / CROPS[crop].seed);\n if (missing > 0 && affordable > 0 && out.length < 10) out.push([\"BUY_SEED\", crop, Math.min(missing, affordable)]);\n return out.slice(0, 10);\n}\n\nexport function buildAgent(opts: { crop: string; targetHands: number; maxTiles: number | null; persistent: boolean; seedBuffer: number }): AgentFn {\n return (obs: any) => {\n try {\n const player = Number(obs.player ?? 0);\n const farms = obs.farms ?? [];\n if (!farms[player]) return { farmer: PASS, hands: [], market: [] };\n const farm = farms[player];\n const priv = obs.private ?? {};\n const day = Number(obs.day ?? 0), hour = Number(obs.hour ?? 0);\n const positions: Array<[number, number]> = [farm.farmer, ...(farm.hands ?? [])].map((x: any) => [Number(x[0]), Number(x[1])]);\n const tasks = collectTasks(farm, day, hour, opts.crop, opts.maxTiles);\n const assignments = chooseAssignments(player, farm, day, hour, opts.crop, positions, tasks, opts.persistent);\n let seedBudget = Number(priv.seeds?.[opts.crop] ?? 0);\n const actions: any[] = [];\n for (let uid = 0; uid < positions.length; uid++) {\n const item = assignments.get(uid);\n if (!item) { actions.push(PASS); continue; }\n const target = item.target as [number, number];\n if (positions[uid][0] !== target[0] || positions[uid][1] !== target[1]) { actions.push(stepToward(positions[uid], target)); continue; }\n if (item.kind === \"PLANT\") {\n if (hour < 23 && seedBudget > 0) { actions.push([\"PLANT\", opts.crop]); seedBudget--; }\n else actions.push(PASS);\n } else if ([\"WATER\", \"HARVEST\", \"DIG\"].includes(item.kind)) actions.push([item.kind]);\n else actions.push(PASS);\n }\n return {\n farmer: actions[0] ?? PASS,\n hands: actions.slice(1, 1 + (farm.hands ?? []).length),\n market: marketOrders(obs, farm, priv, opts.crop, opts.seedBuffer, opts.targetHands),\n };\n } catch {\n return { farmer: PASS, hands: [], market: [] };\n }\n };\n}\n\nexport const K0 = buildAgent({ crop: \"CARROT\", targetHands: 0, maxTiles: 4, persistent: false, seedBuffer: 6 });\nexport const K1 = buildAgent({ crop: \"CARROT\", targetHands: 10, maxTiles: 25, persistent: true, seedBuffer: 30 });\n\nexport const STARTER: AgentFn = (obs: any) => {\n const farm = obs.farms?.[obs.player];\n if (!farm) return { farmer: PASS, hands: [], market: [] };\n const [x, y] = farm.farmer;\n const tile = farm.tiles[y][x];\n const seeds = obs.private?.seeds ?? {};\n const shed = obs.private?.shed ?? {};\n const market: any[] = [];\n const q = Number(shed.CARROT ?? 0);\n if (q > 0) market.push([\"SELL\", \"CARROT\", q]);\n if (Number(seeds.CARROT ?? 0) === 0 && Number(farm.money) >= 20) market.push([\"BUY_SEED\", \"CARROT\", 1]);\n let farmer: any = PASS;\n if (tile === null && Number(seeds.CARROT ?? 0) > 0) farmer = [\"PLANT\", \"CARROT\"];\n else if (tile && typeof tile === \"object\" && tile.kind === \"PLANT\" && tile.crop === \"CARROT\") {\n const age = Number(obs.day) - Number(tile.planted_day);\n if (age >= 3) farmer = [\"HARVEST\"];\n else if (!tile.watered_today) farmer = [\"WATER\"];\n }\n return { farmer, hands: [], market };\n};\n",[],[657,1091],"5a970014-78b8-486c-ad63-a0f09bc95d6f","kaggriculture_adaptive_racing.ts","6449343c-aa3f-11f1-a010-1607ee4eb77e",51,["D",1788732466721],"export type BernoulliRace = {\n wins:number;\n losses:number;\n p0?:number;\n p1?:number;\n alpha?:number;\n beta?:number;\n};\n\n/** Sequential Probability Ratio Test for H0:p=p0 vs H1:p=p1. Ties should be handled outside as paired margin diagnostics. */\nexport function sprt(x:BernoulliRace) {\n const p0=x.p0??0.50, p1=x.p1??0.60, alpha=x.alpha??0.05, beta=x.beta??0.10;\n if (!(0=upper ? \"PROMOTE_H1\" as const : llr<=lower ? \"REJECT_H1\" as const : \"CONTINUE\" as const,\n n:x.wins+x.losses,\n observed:x.wins/Math.max(1,x.wins+x.losses),\n };\n}\n\n/** Wilson score interval; descriptive CI for a fixed checkpoint, not claimed as an always-valid sequential confidence sequence. */\nexport function wilson(wins:number, losses:number, z=1.96) {\n const n=wins+losses;\n if (!n) return {low:0,high:1,center:0.5,n:0};\n const p=wins/n, z2=z*z;\n const den=1+z2/n;\n const center=(p+z2/(2*n))/den;\n const half=z*Math.sqrt((p*(1-p)+z2/(4*n))/n)/den;\n return {low:Math.max(0,center-half),high:Math.min(1,center+half),center,n};\n}\n\nexport type RaceCandidate = {\n id:string;\n wins:number;\n losses:number;\n avgMargin:number;\n runtimeErrorRate?:number;\n};\n\n/** Allocate future matches where information is most valuable: uncertain, close to decision boundary, and operationally stable. */\nexport function racePriority(c:RaceCandidate, target=0.55) {\n const ci=wilson(c.wins,c.losses);\n const width=ci.high-ci.low;\n const closeness=1-Math.min(1,Math.abs(ci.center-target)/0.5);\n const stability=1-Math.min(1,c.runtimeErrorRate??0);\n return width*(0.35+0.65*closeness)*stability;\n}\n\nexport function allocateBatch(candidates:RaceCandidate[], totalMatches:number) {\n const scores=candidates.map(c=>({id:c.id,score:racePriority(c)}));\n const z=scores.reduce((s,x)=>s+x.score,0);\n if (z<=0) return scores.map((x,i)=>({id:x.id,matches:i({id:x.id,q:totalMatches*x.score/z}));\n const base=raw.map(x=>({id:x.id,matches:Math.floor(x.q),frac:x.q-Math.floor(x.q)}));\n let left=totalMatches-base.reduce((s,x)=>s+x.matches,0);\n base.sort((a,b)=>b.frac-a.frac);\n for(let i=0;i0;i++,left--) base[i].matches++;\n return base.map(({id,matches})=>({id,matches}));\n}\n\nexport function dominanceDecision(a:RaceCandidate,b:RaceCandidate) {\n const A=wilson(a.wins,a.losses), B=wilson(b.wins,b.losses);\n if ((a.runtimeErrorRate??0)>0.02) return {decision:\"A_RUNTIME_BLOCKED\" as const,A,B};\n if ((b.runtimeErrorRate??0)>0.02) return {decision:\"B_RUNTIME_BLOCKED\" as const,A,B};\n if (A.low>B.high && a.avgMargin>=b.avgMargin) return {decision:\"A_DOMINATES\" as const,A,B};\n if (B.low>A.high && b.avgMargin>=a.avgMargin) return {decision:\"B_DOMINATES\" as const,A,B};\n return {decision:\"NEEDS_MORE_EVIDENCE\" as const,A,B};\n}\n",[],[657,1099],"bc8cbefe-eadd-4ab1-a695-c92931a29c9c","economic_policy.ts","4fb3747e-aa17-11f1-8e41-1607ee4eb77e",["D",1788715252312],"export type EconomicActionClass =\n | \"R0_OBSERVE\"\n | \"R1_PREPARE\"\n | \"R2_REVERSIBLE_WRITE\"\n | \"R3_COMMIT_SUBMIT\"\n | \"R4_ECONOMIC_SPEND\"\n | \"R5_IDENTITY_LEGAL\";\n\nexport type EconomicActionRequest = {\n actionClass: EconomicActionClass;\n approved?: boolean;\n amount?: number;\n maxBudget?: number;\n};\n\nexport type EconomicActionDecision = {\n allowed: boolean;\n humanGate: boolean;\n reason: string;\n};\n\nexport const ECONOMIC_POLICY = {\n version: \"0.6.0-candidate\",\n defaultBudget: 0,\n actionClasses: {\n R0_OBSERVE: \"Research/read/analyze only\",\n R1_PREPARE: \"Create local/draft artifacts without external commitment\",\n R2_REVERSIBLE_WRITE: \"Reversible external writes such as saving a draft\",\n R3_COMMIT_SUBMIT: \"External commitment such as submit/publish/PR\",\n R4_ECONOMIC_SPEND: \"Any action that spends money or credits\",\n R5_IDENTITY_LEGAL: \"KYC, banking, payout setup, legal or identity declarations\",\n },\n} as const;\n\nexport function evaluateEconomicAction(req: EconomicActionRequest): EconomicActionDecision {\n switch (req.actionClass) {\n case \"R0_OBSERVE\":\n case \"R1_PREPARE\":\n case \"R2_REVERSIBLE_WRITE\":\n return { allowed: true, humanGate: false, reason: \"AUTO_ALLOWED_BY_CLASS\" };\n case \"R3_COMMIT_SUBMIT\":\n return req.approved\n ? { allowed: true, humanGate: false, reason: \"CONTROLLED_WRITE_APPROVED\" }\n : { allowed: false, humanGate: true, reason: \"NEEDS_COMMIT_APPROVAL\" };\n case \"R4_ECONOMIC_SPEND\": {\n const amount = req.amount ?? 0;\n const budget = req.maxBudget ?? ECONOMIC_POLICY.defaultBudget;\n if (!req.approved) return { allowed: false, humanGate: true, reason: \"NEEDS_SPEND_APPROVAL\" };\n if (amount < 0) return { allowed: false, humanGate: true, reason: \"INVALID_NEGATIVE_AMOUNT\" };\n if (amount > budget) return { allowed: false, humanGate: true, reason: \"BUDGET_EXCEEDED\" };\n return { allowed: true, humanGate: false, reason: \"SPEND_WITHIN_APPROVED_BUDGET\" };\n }\n case \"R5_IDENTITY_LEGAL\":\n return { allowed: false, humanGate: true, reason: \"HUMAN_IDENTITY_OR_LEGAL_GATE\" };\n }\n}\n\nexport function netRevenue(input: {\n grossRevenue?: number;\n browserCost?: number;\n llmCost?: number;\n apiCost?: number;\n hostingCost?: number;\n platformFee?: number;\n transactionCost?: number;\n}) {\n const gross = input.grossRevenue ?? 0;\n const costs = (input.browserCost ?? 0) + (input.llmCost ?? 0) + (input.apiCost ?? 0) +\n (input.hostingCost ?? 0) + (input.platformFee ?? 0) + (input.transactionCost ?? 0);\n return gross - costs;\n}\n",[],[657,1107],"ebc09386-8d31-425e-a75d-ce3486658bf8","dsl.ts","01a077bc-2b99-740d-9881-2409b3ecffa5",["D",1788715215771],"import type { BrowserTask } from \"./types.ts\";\n\nconst ALLOWED_ACTIONS = new Set([\n \"goto\", \"wait_for\", \"click\", \"fill\", \"fill_secret\", \"type\", \"select\",\n \"extract_text\", \"extract_attribute\", \"expect_text\", \"expect_url\",\n]);\n\nexport function validateTask(task: BrowserTask): string[] {\n const errors: string[] = [];\n if (!task || typeof task !== \"object\") return [\"task must be an object\"];\n if (!task.runId || task.runId.length > 128) errors.push(\"invalid runId\");\n if (!task.purpose || task.purpose.length > 1000) errors.push(\"invalid purpose\");\n if (!Array.isArray(task.steps) || task.steps.length < 1 || task.steps.length > 30) errors.push(\"steps must contain 1..30 actions\");\n if (![\"read_only\", \"reversible_write\", \"consequential\"].includes(task.risk)) errors.push(\"invalid risk\");\n if (task.risk !== \"read_only\" && task.approved !== true) errors.push(\"NEEDS_APPROVAL\");\n if (task.preferredProvider && ![\"kernel\", \"browserless\"].includes(task.preferredProvider)) errors.push(\"invalid preferredProvider\");\n if (task.evidenceRetention && ![\"minimal\", \"full\"].includes(task.evidenceRetention)) errors.push(\"invalid evidenceRetention\");\n\n let target: URL | undefined;\n try {\n target = new URL(task.targetUrl);\n if (![\"http:\", \"https:\"].includes(target.protocol)) errors.push(\"target protocol blocked\");\n } catch {\n errors.push(\"invalid targetUrl\");\n }\n\n const targetHost = target?.hostname;\n const allowed = new Set([targetHost, ...(task.allowedHosts ?? [])].filter(Boolean) as string[]);\n for (const [i, step] of (task.steps ?? []).entries()) {\n if (!step || !ALLOWED_ACTIONS.has((step as any).action)) {\n errors.push(`step ${i}: unsupported action`);\n continue;\n }\n const maybe = step as any;\n if (typeof maybe.selector === \"string\" && maybe.selector.length > 1000) errors.push(`step ${i}: selector too long`);\n if (typeof maybe.text === \"string\" && maybe.text.length > 10000) errors.push(`step ${i}: text too long`);\n if (maybe.action === \"fill_secret\") {\n if (typeof maybe.envVar !== \"string\" || !/^[A-Za-z_][A-Za-z0-9_]*$/.test(maybe.envVar)) errors.push(`step ${i}: invalid secret env var`);\n if (task.approved !== true) errors.push(\"NEEDS_SECRET_APPROVAL\");\n }\n if (maybe.action === \"extract_attribute\" && String(maybe.attribute).toLowerCase() === \"value\") {\n errors.push(`step ${i}: extracting value attribute is blocked to reduce secret leakage risk`);\n }\n if (maybe.action === \"goto\" && maybe.url) {\n try {\n const u = new URL(maybe.url);\n if (![\"http:\", \"https:\"].includes(u.protocol) || !allowed.has(u.hostname)) errors.push(`step ${i}: navigation host blocked`);\n } catch {\n errors.push(`step ${i}: invalid goto url`);\n }\n }\n }\n return [...new Set(errors)];\n}\n\nexport function buildKernelPlaywrightCode(task: BrowserTask): string {\n const plan = JSON.stringify(task);\n return `\nconst plan = ${plan};\nconst outputs = {};\nconst checks = [];\nconst targetHost = new URL(plan.targetUrl).hostname;\nconst allowedHosts = new Set([targetHost, ...(plan.allowedHosts || [])]);\nconst allowedMethods = new Set([\"GET\", \"HEAD\", \"OPTIONS\"]);\n\nconst assertUrl = (value) => {\n const u = new URL(value);\n if (![\"http:\", \"https:\"].includes(u.protocol)) throw new Error(\"blocked protocol\");\n if (!allowedHosts.has(u.hostname)) throw new Error(\"blocked host: \" + u.hostname);\n};\n\nawait page.route(\"**/*\", async (route) => {\n const req = route.request();\n try {\n if (req.isNavigationRequest() && req.frame() === page.mainFrame()) assertUrl(req.url());\n if (plan.risk === \"read_only\" && !allowedMethods.has(req.method().toUpperCase())) return route.abort(\"blockedbyclient\");\n return route.continue();\n } catch {\n return route.abort(\"blockedbyclient\");\n }\n});\n\npage.on(\"popup\", async (popup) => { try { await popup.close(); } catch {} });\nassertUrl(plan.targetUrl);\nawait page.goto(plan.targetUrl, { waitUntil: \"domcontentloaded\" });\nassertUrl(page.url());\n\nfor (const step of plan.steps) {\n switch (step.action) {\n case \"goto\": {\n const url = step.url || plan.targetUrl;\n assertUrl(url);\n await page.goto(url, { waitUntil: \"domcontentloaded\" });\n break;\n }\n case \"wait_for\":\n await page.locator(step.selector).waitFor({ state: \"visible\", timeout: step.timeoutMs || 10000 });\n break;\n case \"click\":\n if (step.waitForNavigation) {\n await Promise.all([\n page.waitForLoadState(\"domcontentloaded\"),\n page.locator(step.selector).click(),\n ]);\n } else await page.locator(step.selector).click();\n break;\n case \"fill\":\n await page.locator(step.selector).fill(step.text);\n break;\n case \"type\":\n await page.locator(step.selector).pressSequentially(step.text, { delay: step.delayMs || 0 });\n break;\n case \"select\":\n await page.locator(step.selector).selectOption(step.value);\n break;\n case \"extract_text\":\n outputs[step.key] = await page.locator(step.selector).innerText();\n break;\n case \"extract_attribute\":\n outputs[step.key] = await page.locator(step.selector).getAttribute(step.attribute);\n break;\n case \"expect_text\": {\n const body = await page.locator(\"body\").innerText();\n checks.push({ type: \"text\", expected: step.text, ok: body.includes(step.text) });\n break;\n }\n case \"expect_url\": {\n const actual = page.url();\n checks.push({ type: \"url\", expected: step.contains, actual, ok: actual.includes(step.contains) });\n break;\n }\n }\n assertUrl(page.url());\n}\n\nreturn {\n finalUrl: page.url(),\n outputs,\n checks,\n verified: checks.length > 0 && checks.every((x) => x.ok),\n};\n`;\n}\n\nexport function resolveSecrets(task: BrowserTask): BrowserTask {\n const steps = task.steps.map((step) => {\n if (step.action !== \"fill_secret\") return step;\n const value = Deno.env.get(step.envVar);\n if (value === undefined) throw new Error(`secret env var missing: ${step.envVar}`);\n return { action: \"fill\" as const, selector: step.selector, text: value };\n });\n return { ...task, steps };\n}\n",[],[657,1114],"ffa9eab5-1611-4a35-91c1-b027af8f5f45","cost.ts","01a077bc-2b99-740d-9881-21df979511ad",["D",1788715215771],"import type { BrowserReceipt } from \"./types.ts\";\n\nexport function estimateProviderUnits(receipt: BrowserReceipt): number | null {\n if (receipt.status === \"BLOCKED\") return null;\n if (receipt.provider !== \"browserless\") return null;\n if (receipt.durationMs == null) return null;\n return Math.max(1, Math.ceil(receipt.durationMs / 30_000));\n}\n\nexport const COST_NOTES = {\n browserless: \"Estimated units cover browser-time only. Actual cost can be higher with CAPTCHA solving or built-in proxies.\",\n kernel: \"No local unit estimate: Kernel bills usage by GB-second; actual provider usage must be observed from the account.\",\n} as const;\n",[],[657,1121],["D",1788715215771],[696,697,698,699,700,701,702,703,704,705,706,707,708,709,710,711,712],[657],"9b11c5f5-b155-47a5-b4df-46bb3b72111d","TASK_SCHEMA.md","01a077bc-2b99-740d-9881-199895a0596b",["D",1788715215771],"# Browser Task Schema — V0.5\n\nTasks are inserted into the val-scoped SQLite database by the authenticated ChatGPT Val Town plugin. There is no public enqueue endpoint.\n\n## Required fields\n\n- `runId`: unique stable id, <=128 chars.\n- `targetUrl`: http/https URL.\n- `risk`: `read_only`, `reversible_write`, or `consequential`.\n- `purpose`: human-readable reason for the run.\n- `steps`: 1..30 DSL actions.\n\n## Optional fields\n\n- `approved`: must be `true` for `reversible_write`, `consequential`, and any `fill_secret` action.\n- `allowedHosts`: extra main-navigation hosts, explicit only.\n- `preferredProvider`: `kernel` or `browserless`.\n- `evidenceRetention`: `minimal` (default) or `full`.\n\n## DSL actions\n\n- `goto`\n- `wait_for`\n- `click`\n- `fill`\n- `fill_secret`\n- `type`\n- `select`\n- `extract_text`\n- `extract_attribute` (attribute `value` is blocked)\n- `expect_text`\n- `expect_url`\n\n## Secret rule\n\nNever put a password, cookie, API token, or OTP secret in `task_json`.\nUse `fill_secret` with an environment-variable name. The value is resolved in execution memory only after approval.\n\n## Evidence retention\n\n`minimal` persists status, URL, checks, errors, duration and fallback metadata but omits extracted outputs and provider session ids.\n`full` persists the full receipt and should be used only when the extracted data is intentionally safe to retain.\n\n## Retry policy\n\n- Only `read_only` + provider `FAIL` is retryable.\n- Maximum 2 task attempts.\n- Retry delay: 10 seconds.\n- `BLOCKED`, `PARTIAL`, writes and consequential tasks are never automatically retried.\n- No cron/automatic runner is enabled, so a retry becomes eligible but does not consume browser credits until ChatGPT explicitly runs `runner.ts` again.\n\n## Provider fallback\n\n- Kernel is primary.\n- Browserless is fallback only for `read_only` tasks.\n- No cross-provider retry for writes.\n\n## PASS rule\n\nA successful browser call without at least one positive expectation remains `PARTIAL`.\n`PASS` requires all explicit expectations to succeed.\n",[],[662,1131],"989fd312-57a2-4772-9d55-033ac00154a3","SMOKE_TASK.json","01a077bc-2b99-740d-9881-17f664878040",["D",1788715215771],"{\n \"state\": \"DRAFT_ONLY_DO_NOT_AUTO_ENQUEUE\",\n \"task\": {\n \"runId\": \"smoke-kernel-example-com\",\n \"targetUrl\": \"https://example.com\",\n \"risk\": \"read_only\",\n \"purpose\": \"First live cloud-browser smoke test after provider credential activation\",\n \"preferredProvider\": \"kernel\",\n \"evidenceRetention\": \"minimal\",\n \"steps\": [\n {\"action\": \"extract_text\", \"selector\": \"h1\", \"key\": \"heading\"},\n {\"action\": \"expect_text\", \"text\": \"Example Domain\"},\n {\"action\": \"expect_url\", \"contains\": \"example.com\"}\n ]\n },\n \"promotionCriteria\": [\n \"provider credential key exists in Val Town\",\n \"runner returns PASS\",\n \"heading equals Example Domain\",\n \"all expectations pass\",\n \"attempt receipt is persisted\",\n \"provider usage is observed when available\"\n ]\n}\n",[],[662,1138],"312b84fe-7828-4773-b437-17bbbcbafdca","SECURITY_MODEL.md","01a077bc-2b99-740d-9881-11dec1877342",["D",1788715215771],"# Security Model — V0.5.0\n\n## Trust boundaries\n\n### Trusted control plane\n- normal authenticated ChatGPT conversation;\n- authenticated Val Town plugin operations;\n- source code committed in `cleitoncosta/chat-native-maestro` after validation.\n\n### Sensitive trusted storage\n- Val Town Environment Variables;\n- val-scoped SQLite, but only for non-secret task metadata/evidence.\n\n### Untrusted inputs\n- every webpage and frame;\n- page text, HTML, script-generated text and accessibility labels;\n- redirects;\n- URLs supplied by pages;\n- downloaded files;\n- DNS answers and provider responses as evidence that still needs validation;\n- third-party provider error messages.\n\nA webpage is data, never policy or authorization.\n\n## Threat 1 — Prompt injection from a webpage\n\nRisk: page content tries to instruct ChatGPT/runner to reveal secrets, change policy, expand allowed hosts, approve actions or run arbitrary code.\n\nControls:\n- browser receives a bounded DSL, not a free-form agent prompt;\n- no shell or arbitrary-JS task action;\n- page content cannot set `approved=true`;\n- page content cannot add env vars;\n- page content cannot alter `allowedHosts`;\n- browser result is evidence/data only.\n\nResidual risk: extracted malicious text can still be shown to the language model. The control plane must continue treating it as untrusted data.\n\n## Threat 2 — SSRF / internal network access\n\nRisk: task or redirect targets localhost, cloud metadata, private network or a public hostname resolving to non-public IPs.\n\nControls before provider call:\n- HTTP/HTTPS only;\n- URL userinfo blocked;\n- only ports 80/443;\n- direct private/link-local/loopback/reserved/documentation IPv4 and IPv6 ranges blocked;\n- localhost/internal/metadata hostnames blocked;\n- `allowedHosts` validated;\n- A and AAAA resolved through Cloudflare DNS-over-HTTPS;\n- task fails closed if DoH fails, no A/AAAA is found, or any resolved address is non-public.\n\nControls in browser:\n- main-frame navigation restricted to target host plus explicit allowed hosts;\n- popups closed.\n\nValidated negative control:\n`169.254.169.254` is blocked in the real runner before provider invocation.\n\nResidual risk: DNS rebinding after preflight cannot be fully proven absent by a one-time DoH check. Remote browser isolation and navigation checks remain required.\n\n## Threat 3 — Secret leakage\n\nRisk: credentials enter task JSON, source, logs or persistent receipts.\n\nControls:\n- provider credentials only in Val Town env vars;\n- site credentials referenced by env-var name with `fill_secret`;\n- secret value resolved in memory immediately before execution;\n- `fill_secret` requires explicit approval;\n- `extract_attribute: value` blocked;\n- default `evidenceRetention=minimal` omits extracted outputs and provider session IDs;\n- snapshot/export must exclude env-var values and raw sensitive task payloads.\n\nResidual risk: a target site can reflect a submitted secret into ordinary DOM text. The orchestrator must not deliberately extract selectors expected to contain secrets, and `full` retention must not be used for sensitive workflows without a specific reason.\n\n## Threat 4 — Duplicate/replayed writes\n\nRisk: timeout or provider error occurs after a write happened, then another attempt repeats the effect.\n\nControls:\n- automatic retry only for `read_only + FAIL`;\n- no automatic retry for `reversible_write` or `consequential`;\n- no cross-provider fallback for writes;\n- unique `run_id` in SQLite;\n- write tasks require explicit approval.\n\nResidual risk: even a read-classified website can mutate state via GET. The read-only method firewall is strong but cannot prove zero side effects on a badly designed server.\n\n## Threat 5 — Read-only task causes state mutation\n\nControls:\n- browser request firewall allows only GET/HEAD/OPTIONS for `read_only`;\n- common POST/PUT/PATCH/DELETE side effects are blocked;\n- explicit expectations and post-action verification required.\n\nResidual risk:\n- GET endpoints may have side effects;\n- service-worker/browser behavior can be complex;\n- some legitimate read APIs use POST/GraphQL and will fail under strict mode. Do not weaken strict mode silently; use a connector/fetch route or explicitly reclassify the task.\n\n## Threat 6 — Provider degradation / repeated spend\n\nRisk: provider outage causes repeated browser sessions or runaway retries.\n\nControls:\n- max 2 task attempts;\n- 10-second retry eligibility delay;\n- no automatic scheduler;\n- provider circuit opens after 3 consecutive FAILs;\n- 15-minute cooldown;\n- BLOCKED config errors do not increment failure count;\n- PASS/PARTIAL resets provider failures;\n- browser timeouts;\n- Kernel cleanup in `finally`.\n\n## Threat 7 — Stuck RUNNING job\n\nRisk: Val Town/runtime interruption leaves queue permanently locked.\n\nControls:\n- 90-second lease;\n- stale lease recovery;\n- retry budget checked during recovery;\n- terminal failure when retry budget exhausted.\n\nValidated with a real stale-job fixture that was removed after testing.\n\n## Threat 8 — Cost surprise\n\n### Kernel\n- recurring free credits are finite;\n- no automatic runner;\n- short browser timeout;\n- cleanup in `finally`;\n- actual Kernel GB-second usage remains provider-authoritative.\n\n### Browserless\n- local estimate covers base browser-time units only;\n- CAPTCHA/proxy add-ons are not inferred as free;\n- before activation, provider overage spend limit must be set to `$0`;\n- no automatic browser cron;\n- compare local estimated units to provider accounting.\n\n## Threat 9 — False PASS\n\nControls:\n- `TOOL_SUCCESS_RESPONSE != BEHAVIOR_PROOF`;\n- no checks -> `PARTIAL`, not PASS;\n- PASS requires at least one positive expectation and all expectations true;\n- provider/module/pricing availability never promotes a tool to OPERATIONAL;\n- credential, browser creation, actual action, validation and usage evidence are separate states.\n\n## Threat 10 — Public Free-tier source exposure\n\nThe personal Val Town Free workspace requires public source visibility.\n\nControls:\n- no secrets in source;\n- public HTTP endpoint exposes liveness only;\n- detailed task/provider state stays behind authenticated plugin execution;\n- env-var values are never returned by normal Val Town listing tools;\n- source assumes it is publicly readable.\n\n## Evidence-state vocabulary\n\n- `AVAILABLE`: provider/service exists.\n- `ADAPTER_LOADED`: code imports in Val Town.\n- `CONFIGURED`: required env-var key exists.\n- `AUTHENTICATED`: credential proved usable.\n- `AUTHORIZED`: required action is permitted.\n- `EXECUTED`: real provider action occurred.\n- `VERIFIED`: postcondition proved.\n- `OPERATIONAL`: full required chain is repeatedly or sufficiently evidenced for intended scope.\n- `BLOCKED`: known prerequisite prevents execution.\n- `UNVERIFIED`: evidence is absent; not equivalent to failure.\n\nCurrent Kernel and Browserless live-browser state remains `UNVERIFIED` because no user-created provider env vars exist yet.\n",[],[662,1145],"43c57926-d688-45f9-bdd4-705fbd5186c1","PROVIDER_CENSUS.md","01a077bc-2b99-740d-9881-0e23597c5715",["D",1788715215771],"# Browser Provider Census — V0.5.0\n\nResearch snapshot: 2026-09-06.\n\nRanking target: normal ChatGPT mobile/web, no user PC, recurring free allowance, deterministic browser control, strong isolation, minimal browser-open time and zero-surprise-cost preference.\n\n## 1. Kernel — CHAMPION\n\nRuntime state: `ACCOUNT_KEY_REQUIRED` / live browser `UNVERIFIED`.\n\nCurrent official Free plan:\n- $0/month plus usage costs\n- $5/month free credits\n- 5 concurrent browsers\n- live view\n- stealth mode including CAPTCHA solver/proxy\n- managed auth (3 connections)\n- one-day session replays\n- uploads/downloads\n- no card required to get started\n- usage billed by GB-second\n\nTechnical fit:\n- official Val Town browser-automation guide/starter\n- `@onkernel/sdk`\n- server-side Playwright execution in the browser VM\n- on-demand `browsers.create()` is explicitly recommended for occasional/bursty/one-off work\n- browser is destroyed in `finally`\n\nAdapter: `providers/kernel.ts`.\nRequired env var: `KERNEL_API_KEY`.\n\nOfficial sources:\n- https://www.kernel.sh/pricing\n- https://www.kernel.sh/docs\n- https://docs.val.town/guides/browser-automation/kernel\n\n## 2. Browserless — RECURRING-FREE FALLBACK\n\nRuntime state: `ACCOUNT_TOKEN_REQUIRED` / live browser `UNVERIFIED`.\n\nCurrent official Free plan:\n- 1,000 units/month\n- 2 concurrent browsers\n- 2-minute max session\n- no card required\n- Chrome / WebKit / Firefox\n- automatic CAPTCHA solving available\n- persisted sessions/replays\n\nUnit model:\n- browser time: 1 unit per 30-second connection block\n- partial blocks round up\n- successful CAPTCHA solve: 10 additional units\n- residential proxy: 6 units/MB\n- datacenter proxy: 2 units/MB\n\nSeptember 2026 provider control:\n- account overage spend limit can be set to `$0`\n- this should be mandatory before promotion to fallback OPERATIONAL under this project's zero-surprise-cost policy\n\nAdapter: `providers/browserless.ts`.\nRequired env var: `BROWSERLESS_TOKEN`.\nOptional: `BROWSERLESS_BASE_URL`.\n\nOfficial sources:\n- https://www.browserless.io/pricing\n- https://docs.browserless.io/overview/unit-consumption\n- https://www.browserless.io/changelog/2026-09\n\n## 3. Browserbase — RESEARCHED FALLBACK\n\nState: researched, not implemented.\n\nVal Town has an official Browserbase integration guide and starter. It remains behind Kernel/Browserless because the current combination above better matches recurring-free allowance + CAPTCHA/anti-bot + cost control for this project.\n\nSource:\n- https://docs.val.town/guides/browser-automation/browserbase\n\n## 4. Steel — RESERVE / ONE-TIME-CREDIT PATH\n\nState: researched, not implemented.\n\nUseful properties:\n- open-source browser API\n- Puppeteer/Playwright\n- official Val Town integration guide\n\nLower priority because one-time starter credit is less aligned with recurring zero-cost steady state than Kernel/Browserless.\n\nSource:\n- https://docs.val.town/guides/browser-automation/steel\n\n## Routing rules V0.5\n\n1. Explicit configured `preferredProvider` is honored unless its circuit is OPEN.\n2. Otherwise Kernel is primary.\n3. Browserless fallback is allowed only for `read_only`.\n4. Provider `BLOCKED` for missing configuration does not increment health failures.\n5. Provider `FAIL` increments consecutive failures.\n6. Three consecutive FAILs open the provider circuit for 15 minutes.\n7. PASS/PARTIAL resets provider failure state.\n8. Never automatically retry a write on another provider.\n9. Keep reasoning outside the browser; send only a short deterministic DSL plan.\n10. No automatic cron runs browsers.\n\n## Promotion rule\n\nA provider cannot become `OPERATIONAL` from docs/pricing/module-load alone. Required evidence:\n- env-var key exists\n- credential authenticates\n- real browser is created\n- network preflight passes\n- read-only smoke plan executes\n- explicit expectations PASS\n- attempt is persisted\n- provider health remains CLOSED\n- actual account consumption is observed if available\n\nUntil all of these are true, state remains `UNVERIFIED` even if the SDK call returns successfully.\n",[],[662,1152],"875dc314-896d-458c-b402-0a0485726280","CURRENT_STATE.md","01a077bc-2b98-7186-8f2c-a206cdcc09fd",["D",1788715215771],"# CURRENT_STATE — V0.5.0\n\nUpdated: 2026-09-06\n\n## Canonical runtime\n\n`normal ChatGPT mobile/web -> authenticated Val Town plugin -> val-scoped SQLite -> runner.ts -> provider router -> cloud browser -> receipt`\n\nNo Codex and no user computer are required.\n\n## Val Town\n\n- Val: `cleitoncosta/chat-native-maestro`\n- Personal workspace tier: Free\n- Code visibility: public (Free-tier constraint)\n- Public HTTP: minimal liveness only\n- Detailed diagnostics: authenticated `status.ts`\n- Task execution: authenticated Val Town plugin only\n- Persistent state: val-scoped SQLite\n- Schema/app version: 0.5.0\n- Automatic runner/cron: disabled\n\n## Implemented files\n\n### Entrypoints\n- `main.ts` — minimal public GET-only liveness endpoint.\n- `status.ts` — authenticated provider/task/cost/security diagnostics.\n- `runner.ts` — queue lease, validation, network preflight, routed execution, retry decision, receipt persistence.\n- `selftest.ts` — stateless DSL/config regression tests.\n- `stateful_selftest.ts` — circuit breaker, timeout and retry-state regression tests with state restoration.\n- `url_selftest.ts` — URL/DNS/SSRF regression tests.\n\n### Libraries\n- `lib/types.ts` — typed task/receipt/evidence schema.\n- `lib/dsl.ts` — DSL validation, browser program generation, in-memory secret resolution.\n- `lib/policy.ts` — retry/lease/timeout/circuit constants and pure disposition logic.\n- `lib/provider_health.ts` — circuit breaker state machine.\n- `lib/cost.ts` — provider cost-estimation rules.\n- `lib/url_security.ts` — fail-closed URL/DNS-over-HTTPS preflight.\n\n### Providers\n- `providers/router.ts` — provider routing/fallback with health tracking.\n- `providers/kernel.ts` — primary browser adapter.\n- `providers/browserless.ts` — secondary browser adapter.\n\n### Documentation\n- `README.md`\n- `docs/CURRENT_STATE.md`\n- `docs/PROVIDER_CENSUS.md`\n- `docs/ACTIVATION_RUNBOOK.md`\n- `docs/TASK_SCHEMA.md`\n- `docs/SMOKE_TASK.json`\n\n## Database schema V0.5\n\n### `browser_tasks`\nDurable queue and terminal receipt state. New V0.5 fields:\n- `attempt_count`\n- `claimed_at`\n- `next_attempt_at`\n\n### `browser_attempts`\nOne row per provider attempt/fallback with:\n- attempt number\n- provider\n- timestamps\n- status/error\n- duration\n- sanitized receipt\n- estimated Browserless units\n\n### `provider_health`\nCircuit state per provider:\n- `CLOSED` / `HALF_OPEN` / `OPEN`\n- consecutive failures\n- cooldown timestamp\n- last success/failure/error\n\n### `provider_census`\nProvider ranking and current free-tier facts.\n\n### `schema_meta`\n`schema_version=0.5.0`, `app_version=0.5.0`.\n\n## Operational policy V0.5\n\n- max attempts per task: 2\n- read-only FAIL retry delay: 10 s\n- RUNNING lease: 90 s\n- browser execution timeout: 25 s\n- provider circuit opens at 3 consecutive FAILs\n- circuit cooldown: 15 min\n- automatic cross-provider fallback: read-only only\n- automatic scheduled execution: disabled\n\nA retry can become `PENDING`, but it cannot consume browser credits until ChatGPT explicitly invokes the runner again.\n\n## Network security\n\nBefore any provider execution:\n- only HTTP/HTTPS\n- URL credentials/userinfo blocked\n- nonstandard ports blocked\n- private/link-local/loopback/reserved/documentation IPv4/IPv6 blocked\n- localhost/internal/metadata hostnames blocked\n- allowed hosts validated\n- A/AAAA resolved through Cloudflare DNS-over-HTTPS\n- any resolved non-public IP blocks the task\n- DNS/preflight failure fails closed\n\nRunner-level negative-control proof:\n`ssrf-runner-v05 -> BLOCKED / NETWORK_PREFLIGHT_BLOCKED: blocked hostname: 169.254.169.254`\n\nThe fixture was deleted after verification.\n\n## Secret policy\n\nTask JSON never stores secret values.\n`fill_secret` stores only an env-var name and requires explicit approval.\nThe value is resolved in memory immediately before provider execution.\n\n`extract_attribute` of `value` is blocked to reduce accidental credential leakage.\n\nCurrent user-created Val Town env-var count: **0**.\n\n## Evidence retention\n\nDefault: `minimal`.\nPersisted by default:\n- run/provider/status\n- final URL\n- checks\n- errors\n- duration\n- fallback evidence\n- network preflight evidence\n\nNot persisted by default:\n- extracted outputs\n- provider session ID\n\n`full` must be intentionally requested.\n\n## Cost policy\n\n### Kernel\nOfficial current Free plan verified 2026-09-06:\n- $0/month plus usage\n- $5 monthly free credits\n- 5 concurrent browsers\n- no card required to start\n- billed by GB-second\n\nLocal Kernel cost estimate remains unsupported; actual account usage must be observed.\n\n### Browserless\nOfficial current Free plan verified 2026-09-06:\n- 1,000 units/month\n- 2 concurrent browsers\n- max session 2 min\n- no card\n- browser time 1 unit/30 s\n- CAPTCHA/proxy additional\n- overage cap should be set to $0 if Browserless is activated\n\nThe runtime estimates base browser-time units only; actual provider accounting remains authoritative.\n\n## Evidence states\n\n### PASS\n\n- ChatGPT Val Town plugin authentication.\n- Free workspace enumerated.\n- create/edit/run/deploy.\n- public liveness HTTP 200.\n- authenticated diagnostics.\n- SQLite schema/migrations/versioning.\n- atomic queue claim.\n- empty queue behavior.\n- stale RUNNING lease recovery.\n- task attempt persistence.\n- retry policy pure test.\n- timeout test.\n- provider circuit OPEN after three synthetic FAILs and restoration to CLOSED.\n- consequential action approval gate.\n- secret approval gate.\n- invalid provider rejection.\n- `value` attribute extraction block.\n- Kernel SDK adapter module load.\n- Browserless adapter module load.\n- missing provider credential -> BLOCKED.\n- DoH availability through normal Val Town HTTPS egress.\n- public-domain DNS preflight.\n- local/private/metadata/userinfo/nonstandard-port URL blocks.\n- runner-level SSRF block before provider invocation.\n- automatic schedule disabled.\n\n### UNVERIFIED\n\n- Kernel API authentication for this account.\n- live Kernel browser creation.\n- live Kernel server-side Playwright execution.\n- Kernel real credit consumption.\n- Browserless API authentication for this account.\n- live Browserless `/function` execution.\n- Browserless real unit consumption.\n\n## Persistent historical negative controls\n\nThese three V0.4 records intentionally remain in `browser_tasks` as historical evidence:\n1. `neg-control-no-kernel-key` -> BLOCKED / `KERNEL_API_KEY missing`.\n2. `neg-control-no-browserless-token` -> BLOCKED / `BROWSERLESS_TOKEN missing`.\n3. `neg-control-secret-not-approved` -> BLOCKED / `NEEDS_SECRET_APPROVAL`.\n\nV0.5 synthetic lease/circuit/SSRF fixtures were removed after tests so production metrics are not polluted.\n\n## Next incomplete milestone\n\nExactly one external action remains necessary: configure a recurring-free browser credential, preferably `KERNEL_API_KEY`, directly in Val Town env vars. Do not paste it into chat.\n\nAfter the key exists:\n1. confirm only the env-var **name** exists;\n2. enqueue `docs/SMOKE_TASK.json` explicitly;\n3. execute `runner.ts` once;\n4. inspect task + attempt receipt;\n5. verify `heading = Example Domain` and all checks PASS;\n6. inspect provider usage;\n7. only then promote Kernel from `ACCOUNT_KEY_REQUIRED/UNVERIFIED` to `OPERATIONAL`.\n",[],[662,1159],"59787f7c-1e09-4175-b579-f752ee64d035","ACTIVATION_RUNBOOK.md","01a077bc-2b98-7186-8f2c-9ca4b3fc4a0e",["D",1788715215771],"# Activation Runbook — V0.5.0\n\n## Objetivo\n\nAtivar exatamente um browser cloud sem depender de Codex ou computador do usuário e sem criar execução automática que possa consumir franquia sozinha.\n\nO provider preferido para a primeira ativação é **Kernel**.\n\n## 1. Kernel — ativação preferencial\n\n### Conta e chave\n\n1. Criar ou entrar em uma conta Kernel Free.\n2. Gerar uma API key no dashboard Kernel.\n3. Abrir diretamente o editor de Environment Variables do Val Town.\n4. Criar `KERNEL_API_KEY` com o valor da chave.\n5. Não colar a chave no ChatGPT, README, código, SQLite, issue, log ou task JSON.\n\nVal Town env editor:\nhttps://www.val.town/x/cleitoncosta/chat-native-maestro/environment-variables?key=KERNEL_API_KEY\n\nKernel API key dashboard:\nhttps://dashboard.onkernel.com/api-keys\n\n### Após gravar a chave\n\nNão executar browser imediatamente.\n\n1. ChatGPT consulta `list_env_vars` e confirma apenas que o **nome** `KERNEL_API_KEY` existe. O valor não deve ser retornado.\n2. Executar `selftest.ts` e `status.ts`.\n3. Confirmar:\n - Kernel `configured=true`;\n - circuit `CLOSED`;\n - nenhum job `PENDING` inesperado;\n - `automaticSchedule=disabled`.\n4. Ler `docs/SMOKE_TASK.json`.\n5. Inserir explicitamente a task draft no SQLite como `PENDING` somente nesse momento.\n6. Executar `runner.ts` exatamente uma vez.\n7. Ler o registro de `browser_tasks` e `browser_attempts` do smoke.\n8. Exigir:\n - receipt `PASS`;\n - `finalUrl` contém `example.com`;\n - `expect_text` passou;\n - `expect_url` passou;\n - output corrente `heading` é `Example Domain`;\n - attempt persistido;\n - circuit continua `CLOSED`.\n9. Consultar uso/créditos no Kernel, quando disponível.\n10. Somente depois atualizar o estado do Kernel para `OPERATIONAL`.\n\n### Promoção rejeitada se\n\n- SDK retorna sucesso mas expectations falham;\n- receipt é `PARTIAL`;\n- browser cria mas não navega;\n- network preflight falha;\n- circuit abre;\n- consumo não pode ser observado quando isso é material à decisão;\n- qualquer etapa é apenas inferida, não executada.\n\n## 2. Browserless — fallback\n\nAtivar somente se Kernel onboarding estiver bloqueado ou para validar redundância.\n\n### Antes da chave\n\nNo dashboard Browserless, configurar o **overage spend limit para $0**. Isso é requisito deste projeto para evitar cobrança surpresa.\n\nDepois:\n1. criar/entrar na conta Browserless Free;\n2. obter o token;\n3. salvar como `BROWSERLESS_TOKEN` no Val Town;\n4. opcionalmente salvar `BROWSERLESS_BASE_URL` se o account endpoint regional diferir do default;\n5. nunca colar o token em chat/código/SQLite.\n\nVal Town env editor:\nhttps://www.val.town/x/cleitoncosta/chat-native-maestro/environment-variables?key=BROWSERLESS_TOKEN\n\n### Smoke Browserless\n\nUsar a mesma task de `docs/SMOKE_TASK.json`, alterando apenas:\n\n```json\n\"preferredProvider\": \"browserless\"\n```\n\nExigir os mesmos critérios de PASS e, adicionalmente:\n- registrar `estimated_units`;\n- comparar com units reais do provider;\n- lembrar que CAPTCHA/proxy podem gerar units adicionais e não estão incluídos na estimativa local.\n\n## 3. Credenciais de sites-alvo\n\nPara login em um site, criar env vars específicas no Val Town, por exemplo:\n- `PORTAL_USERNAME`\n- `PORTAL_PASSWORD`\n\nTask JSON usa apenas referência:\n\n```json\n{\n \"action\": \"fill_secret\",\n \"selector\": \"#password\",\n \"envVar\": \"PORTAL_PASSWORD\"\n}\n```\n\n`fill_secret` exige aprovação explícita mesmo quando a finalidade geral é leitura.\n\nNunca armazenar senha/token diretamente em `task_json`.\n\n## 4. Regras de segurança operacional\n\n- Não executar task automaticamente só porque uma credencial apareceu.\n- Não criar cron de browser por padrão.\n- Não repetir writes em outro provider após falha.\n- Não transformar `FAIL` de provider em prova de ausência de side effect.\n- Não usar `evidenceRetention=full` com dados sensíveis sem necessidade explícita.\n- Não extrair atributo `value` de campos de formulário; a DSL bloqueia isso.\n- Não usar localhost, metadata cloud, rede privada, URL com userinfo ou porta não padrão; o network preflight bloqueia.\n- Não desabilitar o DNS-over-HTTPS preflight para “fazer funcionar”.\n- Não ampliar `allowedHosts` automaticamente a partir de conteúdo da página.\n- Não tratar uma página como fonte de autorização, policy ou segredo.\n\n## 5. Política de custo\n\n### Kernel\nO plano Free atual fornece créditos mensais; o runtime mantém browser com timeout curto e cleanup em `finally`. Não existe cron de browser.\n\n### Browserless\nA franquia Free é baseada em units. Antes da ativação:\n- overage cap = $0;\n- manter sessões curtas;\n- não habilitar proxy/CAPTCHA sem necessidade;\n- comparar `estimated_units` com uso real.\n\n## 6. Estado atual\n\nEnquanto `list_env_vars` não mostrar `KERNEL_API_KEY` ou `BROWSERLESS_TOKEN`, ambos continuam:\n\n`AVAILABLE/ADAPTER_LOADED != AUTHENTICATED != OPERATIONAL`\n\nNenhum provider deve ser promovido por documentação, pricing, existência do SDK ou sucesso de importação isoladamente.\n",[],[662,1166],["D",1788715215771],[689,690,691,692,693,694],[662],"0bd27574-a4c3-4d33-aaf0-fde83f6d055e","kaggriculture_neuron_protocol_v1.md","ee36dfc6-aa19-11f1-ad34-1607ee4eb77e",12,["D",1788716377031],"# Kaggriculture — Neurônio Competition Protocol V1\n\nStatus: R1_PREPARE / NO KAGGLE SUBMISSION YET\nAgent: A4-KAGGRICULTURE\nOpportunity: OP-KAGGRICULTURE-202609\nPrepared: 2026-09-06\n\n## Primary contract\n\n- Start: 2026-07-29\n- Entry / team-merger deadline: 2026-09-23 23:59 UTC\n- Final submission deadline: 2026-09-30 23:59 UTC\n- Final convergence/tournament continues into ~2026-10-15\n- Prize pool: USD 50,000\n- 10 prize positions × USD 5,000\n- No purchase necessary\n- 5 submissions/team/day\n- Latest 2 submissions are the active/final-evaluation pair\n- Winner of an episode = higher bank cash after 720 turns; cash margin itself does not change rating magnitude\n- Validation episode runs a submission against itself before ladder admission\n\n## Grimório interpretation\n\nThis competition is unusually compatible with the Neurônio method because the external environment supplies:\n\n- repeated trials;\n- adversarial opponents;\n- observable fitness;\n- daily mutation budget;\n- public replay evidence;\n- a final tournament;\n- an explicit economic objective.\n\nDo NOT use Kaggle rating as the only truth. Public discussion documents meaningful rating noise and large rating differences between identical submissions. Use paired local matches + ladder as independent evidence.\n\n## Champion / challenger slot policy\n\nBecause only the latest 2 submissions are used for final evaluation:\n\n1. Slot C = CURRENT_PROVEN_CHAMPION.\n2. Slot X = CHALLENGER.\n3. Never replace both slots with unproven mutations in the same generation.\n4. If X beats C in controlled evaluation and survives ladder falsification, X becomes C.\n5. Re-submit/freeze the champion when necessary to keep one latest slot occupied by a known-good artifact.\n6. Preserve exact code hash, parameters, tests, seed set and evidence for every champion epoch.\n\nThis is the competition-level equivalent of `CURRENT_PROVEN_CHAMPION`.\n\n## What current public meta evidence says\n\nCommunity evidence is discovery/benchmark evidence, not authority:\n\n- A fixed-asset strategy has been reported around 81% win rate and became widely copied.\n- A recently observed highly adaptive #1 agent was reported 40-0 over a 40-game public x-ray window with median margin around +13k before being retired by its team.\n- Another public report reached ~80k terminal cash with PPO but hit a wall and moved toward a hybrid policy + deterministic executor.\n- Public analysis repeatedly identifies path/walking inefficiency as a major bottleneck; early work reported 83% of unit-turns moving, improved toward ~55% by avoiding target thrashing.\n- The first ~10 daily hires are inexpensive relative to farm economics; labor-action capacity is generally cheaper than bad routing.\n- Static replay/meta agents remain strong, so novelty alone is not fitness.\n\n## Official-engine facts that matter to strategy\n\n- 30 days × 24 turns = 720 turns.\n- Starting money default: 3000.\n- Farm starts with one unlocked 5×5 quadrant.\n- Additional land: 1000, 2000, 4000 in fixed order.\n- Hiring resets daily and follows Fibonacci cost × multiplier.\n- Opponent farm is visible; opponent shed/private inventory is hidden.\n- Market inventory/prices are shared and persistent.\n- Selling pushes a resource into the glut branch for both players.\n- Town demand removes products from shared market inventory and can create scarcity.\n- Melon has no specialty-shop demand; town center is its principal exogenous sink.\n- Animals can create fertilizer daily; uncollected fertilizer does not accumulate.\n- Shed capacity is finite; excess end-of-day inventory can be discarded.\n- End-state winner uses cash in bank, so unliquidated inventory/capital is dangerous near horizon.\n\n## Architecture hypothesis\n\nThe strongest zero/low-compute direction is not pure LLM, pure RL, or a fixed tape.\n\nUse:\n\n`ADAPTIVE MACRO PLANNER → DETERMINISTIC TASK GRAPH → PATH/ACTION EXECUTOR → MARKET EXECUTOR`\n\n### Macro planner\n\nRecomputes only when meaningful state changes occur:\n\n- new day;\n- town shop unlock;\n- material price movement;\n- opponent commits to a new production cluster;\n- land/animal/crop lifecycle event;\n- endgame horizon threshold.\n\nOutputs desired asset mix, harvest/sell timing, land/hire budget and target inventory.\n\n### Deterministic executor\n\nConverts macro intent into explicit work orders and avoids per-turn retargeting:\n\n1. finish all useful same-tile operations before moving;\n2. assign persistent tasks to units;\n3. minimize Manhattan movement / use clustered layouts;\n4. prioritize survival actions (water/feed) over yield optimization;\n5. preserve item/shed capacity;\n6. use hands only when marginal task value exceeds hire + walking cost.\n\n### Market executor\n\nPredicts near-future shared inventory from:\n\n- current market inventory;\n- known town demand;\n- our visible production pipeline;\n- opponent visible crops/animals;\n- our hidden inventory;\n- horizon.\n\nThen chooses `sell now`, `hold`, or `produce another resource` based on expected marginal sale price, not base price.\n\n## Initial Neurônio branches\n\nThese are research variants, NOT economic offspring. Economic offspring are created only after positive real net revenue.\n\n### K0 — Deterministic control\n\nPurpose: stable control and regression oracle.\n\n- compact 1–3 quadrant layout;\n- deterministic task completion;\n- simple horizon-aware liquidation;\n- no opponent adaptation except basic price observation.\n\nMust be reproducible across seeds.\n\n### K1 — Labor/route optimizer\n\nMutation: K0 + workload-derived hands + persistent routing.\n\nHypothesis: reducing walking/thrashing provides larger win gain than adding a more sophisticated crop-value model.\n\nAblation: same macro policy with fixed hands / naive nearest-target routing.\n\n### K2 — Livestock/fertilizer flywheel\n\nMutation: K1 + animal-centric asset allocation.\n\n- value named product + fertilizer stream jointly;\n- feed/care/collect as co-located task bundle;\n- use fertilizer where marginal crop gain beats fertilizer sale value;\n- adapt animal type to observed shop demand.\n\nFalsifier: seasons with weak product demand; action/walking cost; wheat feed opportunity cost.\n\n### K3 — Opponent-aware anti-glut\n\nMutation: K1 + forecast opponent future supply from public farm state.\n\n- front-run likely opponent dumps;\n- avoid entering a resource whose predicted shared glut destroys both margins;\n- exploit complementary demand holes;\n- maintain uncertainty because opponent shed is hidden.\n\nFalsifier: opponent visibility adds noise without enough predictive power.\n\n### K4 — Demand/horizon portfolio\n\nMutation: K1 + explicit NPV by remaining turns and town draw.\n\n- only start an asset if expected payback occurs before wind-down;\n- demand-sensitive product allocation;\n- controlled inventory holding under shed limit;\n- late-game liquidation schedule;\n- land expansion only when marginal NPV beats capital + route overhead.\n\nFalsifier: static meta beats adaptivity because replanning causes execution instability.\n\n### K5 — Hybrid champion candidate\n\nOnly created after K1–K4 evidence.\n\n`K1 executor + best macro mechanisms from K2/K3/K4`\n\nDo not fuse every feature. Each mechanism must survive ablation first.\n\n## Evaluation harness when Kaggle runtime becomes available\n\nFor every candidate:\n\n1. validation episode/self mirror;\n2. fixed seed suite;\n3. both player seats;\n4. built-ins: pass/random/starter;\n5. public reference agents used only as attributed controls;\n6. CURRENT_CHAMPION head-to-head;\n7. paired seeds so both candidates face identical stochastic worlds;\n8. report win/loss/tie, terminal bank, movement %, pass %, task completion, discarded inventory, deaths/weeds/escapes, realized price per product and land/hire utilization.\n\nUse Bradley-Terry or paired win rate for ranking; terminal bank is diagnostic, not the competition's sole ranking signal.\n\n## Promotion gate\n\nA challenger can replace Champion only when all are true:\n\n- zero validation/runtime errors;\n- deterministic invariants pass;\n- >50% paired win rate vs champion with enough episodes to avoid obvious noise;\n- preferably >=60% before online promotion in early generations;\n- no material regression against reference-agent basket;\n- improvement mechanism is explainable or survives ablation;\n- exact submission artifact hash preserved.\n\n## Daily online use of 5 submission budget\n\nDo not spend 5 slots blindly.\n\nSuggested cadence after local harness exists:\n\n1. champion/canary if needed;\n2. strongest challenger;\n3. orthogonal challenger with high information gain;\n4–5 only when earlier evidence justifies them.\n\nBecause only the latest 2 are final-active, order matters. Preserve champion + one challenger at day end.\n\n## Negative-space questions\n\n- Are top agents intentionally retired to reduce replay harvesting?\n- Does a fixed-route meta dominate only because common opponents are copies of it?\n- Can opponent-aware adaptation exploit this monoculture?\n- Is 4th quadrant ever NPV-positive after walking + labor + delayed production?\n- Is fertilizer sale or use better under each current demand state?\n- Can shop draw be inferred early enough to materially reallocate assets?\n- Does expected-value demand planning lose to robust/worst-case planning?\n- Is market timing more valuable than production optimization?\n- Which features improve terminal bank but reduce head-to-head win rate?\n\n## Required next external gate\n\nKaggle account must accept the competition rules before 2026-09-23. This is an R3/terms/account gate and cannot be truthfully fabricated by the agent.\n\nAfter that, use the official `kaggle_environments` runtime as the oracle. Do not promote a hand-written substitute simulator as proof of game performance.\n",[],[667,1176],"00a862ef-d86a-4945-a833-760ba8728205","kaggriculture_joined_research_plan_v1.md","4178cfe2-aa32-11f1-9903-1607ee4eb77e",16,["D",1788726824853],"# Kaggriculture — Joined Research Plan V1\n\nStatus: JOINED_RESEARCHING\nAgent: A4-KAGGRICULTURE\nHuman gate: completed by user (competition joined; identity verification completed)\nDate: 2026-09-06\n\n## Official mechanics confirmed\n\n- 30 days × 24 turns = 720 turns.\n- One farmer action per turn; market orders can also be submitted, up to the configured per-turn limit.\n- Winning is determined by final bank balance; rating movement uses win/loss/tie rather than coin margin.\n- Up to 5 submissions/day; latest 2 submissions are tracked for active/final evaluation.\n- A validation episode runs the submission against a copy of itself before ladder entry.\n- Final evaluation continues after submission lock and culminates in a Bradley–Terry tournament.\n- Observation exposes both farms publicly, shared market state and town state; own shed/seeds/inventories are private.\n- Market inventory and prices are shared; player production can therefore alter the price environment faced by both agents.\n- Submission contract: root `main.py` with top-level `agent(obs)`.\n- No ingress/egress during episode evaluation.\n\n## Current strategic thesis\n\nDo not use an LLM per turn. Treat the problem as a deterministic control system with an adaptive macro layer.\n\nControl stack:\n\n1. macro allocation policy — crop/animal/land/labor/market regime;\n2. persistent task graph — avoid turn-by-turn retargeting;\n3. deterministic path/action executor — minimize walking/thrashing;\n4. market executor — exploit shared inventory/price dynamics;\n5. opponent model — infer likely supply pressure from public farm state;\n6. horizon controller — alter investment/liquidation as remaining turns shrink.\n\n## Neurônio variants\n\nK0 — Deterministic Control\n- stable regression oracle;\n- correct action schema;\n- no unnecessary complexity.\n\nK1 — Labor/Route Optimizer\n- hypothesis: reducing travel and retargeting improves win rate more than adding valuation complexity.\n\nK2 — Livestock/Fertilizer Flywheel\n- hypothesis: animal ROI is understated if product + fertilizer streams are not jointly valued.\n\nK3 — Opponent-Aware Anti-Glut\n- hypothesis: public opponent farm state predicts future shared-market supply enough to change profitable production/sale timing.\n\nK4 — Demand/Horizon Portfolio\n- hypothesis: explicit remaining-horizon value improves investment, allocation and liquidation timing.\n\nK5 — Hybrid Champion Candidate\n- blocked until K2/K3/K4 mechanisms individually survive ablation and regression testing.\n\n## Evidence discipline\n\nPublic replay data is useful for calibration, controls and matchup simulation, but copied action tapes are not a valid competitive strategy. Every external code/data source must satisfy competition licensing and accessibility rules. Public leaderboard/replay performance is historical evidence, not proof that a copied strategy will remain competitive.\n\n## Evaluation protocol\n\nFor every variant:\n\n1. validation/self-play smoke;\n2. deterministic seed set;\n3. mirrored seats where possible;\n4. fixed baseline opponents;\n5. replay-derived sparring opponents only as controls/reference;\n6. record wins/losses/ties, terminal bank, movement rate, pass rate, runtime errors;\n7. mutation/ablation against parent;\n8. promote only when the improvement survives repeated seed/opponent sets.\n\nPrimary selection metric: win rate / Bradley–Terry-relevant outcomes.\nSecondary diagnostics: terminal bank, movement efficiency, runtime stability and opponent-specific failure modes.\n\n## Immediate build order\n\n1. K0 exact-contract baseline.\n2. K1 persistent task graph + nearest/route-aware executor.\n3. Harness that runs paired/mirrored matches across seeds.\n4. Mechanic/reference calibration from official engine/reference data.\n5. K2/K3/K4 independently.\n6. K5 only after evidence-gated fusion.\n7. First Kaggle submission only after local/official-env smoke is clean.\n\n## Economic state\n\nGross revenue: 0\nNet revenue: 0\nTrial terminal: false\nSelection state: INCUBATION\nNo offspring allowed yet.\n",[],[667,1184],"0e19555c-7e69-4662-ba5f-cae3f13cdc4e","calle_feedback_candidate_v1.md","51f5ad64-aa18-11f1-a53a-1607ee4eb77e",7,["D",1788715685600],"# CALL-E Feedback Candidate V1\n\nStatus: R1_PREPARE / NOT SUBMITTED\nAgent: A2-CALLE\nOpportunity: OP-CALL-E-20260914\nPrepared: 2026-09-06\n\n## Why this candidate exists\n\nThe CALL-E rules allow one feedback submission per entrant and explicitly value actionable bug reports, UI improvements, documentation improvements, and suggested integrations. This artifact contains only findings supported by public documentation/repository evidence. It does **not** claim an authenticated CALL-E runtime test or a real phone call.\n\n## Finding 1 — Supported-region documentation can become stale relative to the maintained region backlog\n\n### Evidence\n\n- The current repository README lists Kenya (`KE`, +254, English, International) in the public “Supported Regions and Languages” table.\n- The current regional/language backlog in GitHub issue #102 records Kenya (`KE`, +254, Swahili) as `Requested`, added 2026-09-01, not `Enabled`.\n- The latest README commit returned for `README.md` was 2026-08-27, while the backlog contains later state changes through 2026-09-03.\n\n### User/agent impact\n\nAn agent that trusts the README as a capability contract can select a recipient/locale combination that the live service may reject. For autonomous callers this is more serious than a normal documentation typo: unsupported-route failures happen near a consequential action boundary and can break planning, retry logic, cost estimation, and user expectations.\n\n### Suggested improvement\n\nCreate one canonical machine-readable capability source and derive public documentation from it. For example:\n\n1. expose a read-only API/MCP capability such as `list_supported_regions` / `get_call_capabilities`;\n2. return region, calling code, supported locales/languages, line type/region, availability state, and effective date;\n3. generate the README table from that source in CI;\n4. fail CI when the generated table and committed documentation diverge;\n5. include a `last_updated`/capability-version value so agent clients can reason about staleness.\n\nThis avoids manually synchronized capability claims across README, issues, Discord and backend behavior.\n\n## Finding 2 — Capability discovery is missing from the 3-tool MCP workflow\n\nThe public MCP contract exposes only:\n\n- `plan_call`\n- `run_call`\n- `get_call_run`\n\nFor an agent, supported-region/language discovery therefore appears to happen only indirectly when `plan_call` rejects or clarifies a request. A read-only capability-discovery tool would let an agent validate a plan before generating a call workflow and would make the system friendlier for unattended automation.\n\n### Suggested tool\n\n`get_call_capabilities({ destination_country?, locale?, channel? })`\n\nPossible output:\n\n```json\n{\n \"capability_version\": \"...\",\n \"destination_country\": \"BR\",\n \"calling_code\": \"+55\",\n \"supported\": true,\n \"languages\": [\"Portuguese\", \"English\"],\n \"locales\": [\"pt-BR\", \"en-...\"],\n \"line_region\": \"Local\",\n \"effective_at\": \"...\"\n}\n```\n\nThis is especially useful for agents that need to choose among regions or languages before `plan_call`.\n\n## Finding 3 — Documentation currentness should be treated as a runtime contract\n\nThe repository is evolving quickly: recent public issues include Windows shell incompatibility (#111), SSE parsing loss (#110), CLI binary collision (#109), missing recovery guidance (#108), and an API-key placeholder mismatch (#107). These are already reported, so they should **not** be duplicated in the feedback survey as new bugs. However, together they show that integration documentation is a fast-moving operational surface.\n\n### Suggested improvement\n\nPublish a small generated compatibility manifest alongside the install guide, for example:\n\n```json\n{\n \"cli_version\": \"...\",\n \"mcp_protocol\": \"...\",\n \"supported_shells\": [\"bash\", \"pwsh\", \"cmd\"],\n \"mcp_tools\": [\"plan_call\", \"run_call\", \"get_call_run\"],\n \"capability_version\": \"...\",\n \"docs_commit\": \"...\"\n}\n```\n\nAgent integrations could verify this before using cached instructions. This would reduce the chance of an agent following stale command syntax or capability assumptions.\n\n## Recommended survey wording\n\n> I found a currentness problem in the supported-region documentation that is particularly important for autonomous agents. The current README lists Kenya (+254) as a supported English/International destination, while the maintained regional backlog in issue #102 records Kenya as Requested (added Sep 1, not Enabled). The README’s latest returned commit is Aug 27, so the two public capability surfaces can disagree as support changes weekly. I recommend making the region/language matrix machine-readable and generating the README from the same source, with a capability version/effective date. It would also be useful to expose a read-only MCP/API capability such as `get_call_capabilities` so agents can validate destination + locale before `plan_call` rather than learning support only through a failed/clarification path. A CI check could fail when generated docs diverge from the canonical capability source. I did not place a real call for this finding; this is a public docs/repository consistency audit.\n\n## Falsification / remaining work before submission\n\n- Re-check the live README immediately before submission.\n- Re-check issue #102 immediately before submission.\n- If a documented capability API/tool already exists elsewhere, revise Finding 2 from “missing” to “hard to discover in the public integration path”.\n- If authenticated CALL-E access is created, run a **plan-only** Brazil/Portuguese capability check first. Do not call `run_call` as a connectivity test.\n- Do not claim a phone call was attempted unless it actually was.\n\n## Evidence state\n\nFinding 1: STRONG / public contradiction observed\nFinding 2: PARTIAL / absence confirmed in public 3-tool MCP contract, backend-wide absence not proven\nFinding 3: INFERENCE / synthesis from multiple already-reported integration issues\n\n## Economic state\n\nGross revenue: 0\nCost recorded by this agent: 0\nNet revenue: 0\nStatus: PREPARED_NOT_SUBMITTED\n",[],[667,1192],"69d33785-05f9-4837-943b-cda43a5b3ea1","KAGGRICULTURE_REAL_WORLD_CURRICULUM_V1.md","385d7470-aa3d-11f1-8d8a-1607ee4eb77e",47,["D",1788731534043],"# Kaggriculture Real-World Curriculum V1\n\nStatus: ACTIVE RESEARCH DOCTRINE\nDate: 2026-09-06\nPurpose: turn Kaggriculture agents into domain experts rather than blind parameter searchers.\n\n## Principle\n\nResearch first, test second. External knowledge should generate mechanisms, priors, strategy families and falsifiable hypotheses. Simulation remains the validation laboratory because transferable theory can fail under Kaggriculture's exact rules.\n\n## Track A — Autonomous Competitive Agents\n\nCore disciplines:\n- Multi-agent reinforcement learning (MARL)\n- Stochastic / Markov games\n- Opponent modeling / Theory of Mind\n- Competitive coevolution\n- Population-based training (PBT)\n- Policy Space Response Oracles (PSRO)\n- League training / PFSP matchmaking\n- Self-play and historical snapshot pools\n- Evolutionary strategies / CMA-ES / genetic algorithms\n- Curriculum learning\n- Meta-learning / transfer learning\n- Imitation learning / behavioral cloning\n- Hierarchical reinforcement learning\n- Model-based RL and planning\n- Monte Carlo Tree Search\n- Counterfactual regret minimization / regret learning\n- Online learning / no-regret dynamics\n- Exploitability / Nash / best response / empirical game-theoretic analysis\n- Robust RL / distributionally robust Markov games\n- Operations research for task allocation and routing\n- Multi-agent path finding / scheduling\n- Hybrid learned-policy + deterministic executor architectures\n- Active learning / experiment design / Bayesian optimization\n- Ablation / causal attribution / mutation testing\n\nQuestions every agent-research branch must answer:\n1. What is the opponent set used for training and why?\n2. Does the method overfit one opponent or strategy family?\n3. Is fitness absolute or relative to an evolving population?\n4. Does the population preserve diversity?\n5. What triggers branch, mutation, reset and pruning?\n6. Can the agent infer opponent type online?\n7. What is the best response to each opponent family?\n8. How is robustness measured under unseen shops/seeds/seats/opponents?\n9. Which decisions should be learned/adaptive and which deterministic?\n10. What would falsify the claimed mechanism?\n\nHigh-value implementation families:\n- PSRO-like strategy population\n- AlphaStar-style league training\n- Historical champion pool\n- Exploiter agents specialized in finding champion weaknesses\n- Opponent classifier + conditional policy router\n- Hierarchical macro policy + deterministic operations executor\n- Population-based parameter evolution\n- Curriculum from weak reference agents to meta-line opponents\n- Robust selection on quantiles/CVaR/win probability, not average bank alone\n\n## Track B — Real-World Farm / Economics / Business Strategy\n\nCore disciplines:\n- Agricultural economics\n- Whole-farm planning\n- Farm management\n- Agribusiness\n- Production economics / theory of the firm\n- Operations management\n- Resource allocation / linear and mixed-integer programming\n- Dynamic programming / approximate DP\n- Stochastic optimization\n- Inventory theory / storage economics\n- Working capital / liquidity management\n- Cash conversion cycle\n- Marginal productivity of labor / land / capital\n- Diminishing returns\n- Opportunity cost / shadow price / bottleneck value\n- Commodity market microstructure\n- Supply and demand\n- Price elasticity\n- Scarcity / glut / endogenous price impact\n- Intertemporal selling / hold-vs-sell thresholds\n- Convenience yield / real options of inventory\n- Dynamic pricing under competition\n- Industrial organization / duopoly / oligopoly\n- Game theory / repeated games / differential games\n- Competitor response / strategic substitutes and complements\n- Capacity planning\n- Perishability / terminal salvage / liquidation\n- Portfolio allocation / diversification\n- Mean-variance / downside risk / CVaR\n- Risk management\n- Hedging concepts (transfer only where environment has analogous mechanism)\n- Interest / inflation / cost of capital (knowledge layer; not directly represented in current game)\n- Investment timing / NPV / real options\n- Supply chain / logistics / storage capacity / transport\n- Demand forecasting / Bayesian updating\n- Price discrimination / reservation price / market timing\n- Competitive strategy / positioning / resource-based view\n- OODA loop / wargaming / red teaming / adversarial planning\n\n## Kaggriculture ↔ Real World Mapping\n\n- farm money -> working capital / liquidity\n- workers -> labor capacity and marginal productivity\n- land -> capacity investment / capital expenditure\n- crop mix -> production portfolio\n- livestock -> capital-intensive productive assets with delayed payback\n- feed reserve -> operating liquidity / safety stock\n- shed -> inventory/storage capacity\n- crop/animal lifecycle -> lead time / biological production cycle\n- market inventory -> aggregate supply state\n- market price curve -> endogenous price elasticity\n- shops -> stochastic demand regimes / local demand shocks\n- market order sequence -> execution ordering + intraperiod financing\n- shared market -> duopoly / strategic price impact\n- opponent farm visibility -> competitor intelligence\n- unknown private inventory -> partial information / belief state\n- weeds -> operational shocks\n- 720-turn horizon -> finite planning horizon\n- final unsold stock -> zero terminal salvage / liquidation risk\n- buy land / animals -> irreversible investment / real option\n- choice to sell now or hold -> inventory real option / threshold policy\n\n## Things NOT directly represented — avoid fake realism\n\n- debt / loans / leverage\n- interest expense\n- inflation\n- taxation\n- insurance\n- futures/options contracts\n- regulation\n- weather and climate shocks beyond weeds\n- supplier defaults\n- reputation / relationships / contract enforcement\n- product quality grades\n- transportation distance/cost\n- multiple buyers with negotiated contracts\n- macroeconomic policy\n\nStudy these as transferable concepts, but never pretend the simulator already models them.\n\n## Research-to-Action Pipeline\n\nSOURCE -> CLAIM -> TRANSFERABLE MECHANISM -> KAGGRICULTURE ANALOGY -> HYPOTHESIS -> MINIMAL IMPLEMENTATION -> CONTROL -> SIMULATION -> FALSIFICATION -> PROMOTE/REJECT -> LESSON\n\nBlind parameter sweeps are prohibited when a researchable mechanism exists. Parameter search is allowed only after mechanism definition and should estimate thresholds/robust regions rather than replace reasoning.\n\n## Recommended Source Router\n\n- TinyFish research_paper: papers/theses/dissertations and targeted recent academic search\n- Exa: semantic discovery of theses, projects, labs, case studies, technical blogs, repositories and unusual adjacent fields\n- Firecrawl developer_search: GitHub README/issues/PRs/docs and implementation patterns\n- Firecrawl research_search_papers: broad paper discovery / alternate formulations\n- GitHub connector: full code/provenance/commit history once a relevant implementation is found\n- Reddit via TinyFish/Exa: practitioner failures, hidden assumptions, implementation pain, community consensus; never authority by itself\n- Consensus/Elicit/Scite: evidence synthesis, paper tables, supporting/contrasting citations\n- Wolfram when operational: symbolic/numeric optimization, sensitivity, probability, robust decision models, independent calculation oracle\n\n## Priority Research Waves\n\nWave A1: PSRO + league training + exploiters + opponent population management\nWave A2: opponent modeling + Bayesian strategy classification + best-response routing\nWave A3: hierarchical macro policy + deterministic task executor + routing/scheduling OR\nWave A4: competitive coevolution + diversity preservation + curriculum + transfer\nWave A5: robust selection / uncertainty / win-probability optimization\n\nWave B1: whole-farm optimization / MIP / dynamic programming\nWave B2: inventory/storage/hold-sell threshold policies and real options\nWave B3: working capital/liquidity/feed reserve/capital allocation\nWave B4: industrial organization / dynamic pricing / endogenous supply / competitor response\nWave B5: farm production economics / marginal returns / capacity bottlenecks\nWave B6: risk, CVaR, portfolio diversification and finite-horizon liquidation\n\n## Immediate research-derived hypotheses\n\nH-A1: opponent sequence and population composition materially affect learned policy quality; train against a curated evolving league, not one baseline.\nH-A2: preserve old champions as frozen opponents to prevent forgetting and cyclic collapse.\nH-A3: specialized exploiters should search for champion weaknesses and feed discovered failure modes back into the champion lineage.\nH-A4: online opponent classification should route among strategy families rather than force one universal policy.\nH-A5: macro adaptation should occur only at information-changing events; low-level logistics should remain deterministic/persistent.\n\nH-B1: optimal production is a joint production+inventory+liquidity decision, not yield maximization.\nH-B2: feed reserve has option value because it preserves the ability to operate through adverse price/supply states.\nH-B3: sell/hold decisions should use state-dependent thresholds rather than fixed reservation prices.\nH-B4: extra land/labor has a shadow value that becomes zero or negative after downstream demand/storage/logistics bottlenecks bind.\nH-B5: strategy should optimize probability of defeating the opponent, not expected own bank in isolation.\nH-B6: shop-world classification should alter the crop/livestock portfolio and liquidation timing.\n\n## Promotion rule\n\nNo concept becomes canonical merely because it appears in a paper, thesis, GitHub repo or successful public agent. Promotion requires a clear mechanism, compatible assumptions, current game mapping, an explicit counterfactual/ablation, and local evidence against a suitable control.\n",[],[667,1200],"05af4f80-7c0e-4dba-9cc2-f5000cae2a0d","HUMAN_GATE_KAGGRICULTURE_20260906.md","0e5a86d4-aa30-11f1-a6db-1607ee4eb77e",15,["D",1788725880082],"# HUMAN GATE — Kaggriculture\n\nStatus: READY_FOR_USER_ACTION\nChecked: 2026-09-06\nOpportunity: OP-KAGGRICULTURE-202609\nAgent: A4-KAGGRICULTURE\n\n## Proven current primary-source facts\n\n- Official competition: https://www.kaggle.com/competitions/kaggriculture\n- Official rules: https://www.kaggle.com/competitions/kaggriculture/rules\n- Sponsor: Google LLC\n- Total prizes: USD 50,000\n- 10 prizes of USD 5,000 each\n- Entry Deadline: 2026-09-23\n- Team Merger Deadline: 2026-09-23\n- Final Submission Deadline: 2026-09-30\n- Maximum submissions: 5/day\n- Up to 2 final submissions may be selected for judging\n- Rules explicitly permit AMLT/automated machine learning tools subject to licensing/rule compliance.\n- General eligibility is worldwide except listed sanctioned/restricted territories; Brazil is not among the listed exclusions in the current rules.\n- A Kaggle account and acceptance of the competition rules are required before the Entry Deadline.\n\n## Human action required\n\n1. Sign in to the user's real Kaggle account.\n2. Open the Kaggriculture competition page.\n3. Click `Join Competition`.\n4. Read and accept the official competition rules using the user's own identity/account.\n5. Do not create multiple Kaggle accounts; the rules prohibit multiple accounts.\n6. Stop after the competition shows the account as joined. Do not submit an agent yet.\n\n## Why this is a human gate\n\nAccepting binding competition rules is an identity/legal action (R5/HUMAN_GATE). The agent may prepare strategies, code, tests, ablations and submissions, but must not impersonate the user or accept binding terms on the user's behalf.\n\n## After the gate\n\nExpected next lifecycle state: `JOINED_RESEARCHING`.\nThe autonomous work resumes with K0→K5 strategy experiments, simulation/replay analysis, deterministic executor optimization, anti-glut/opponent-aware branches, falsification and champion selection.\n\n## Important correction from previous plan\n\nCALL-E/Devpost must NOT be used for this user's paid-entry experiment: the current official CALL-E rules explicitly list Brazil among excluded resident territories. That opportunity is now `INELIGIBLE` and the prior recommendation to register was withdrawn and recorded as negative knowledge.\n",[],[667,1208],["D",1788715656185],[683,684,685,686,687],[667],["D",1788707065045],["D",1789575110896],{"_102":101,"_110":106},{"_102":101,"_103":104,"_105":106,"_18":55,"_107":108,"_109":25},{"_13":89,"_32":90,"_43":42,"_91":44,"_92":93,"_94":95,"_96":50,"_97":44,"_98":65,"_99":45,"_100":101},"ctx",{"_82":-5,"_131":1256,"_1257":1258,"_1259":1260,"_1261":25,"_1262":25,"_1263":25,"_1264":59,"_1265":-5,"_1266":-7,"_1267":-7,"_1268":63,"_1269":25,"_1270":25,"_1271":-5,"_1272":25,"_1273":25,"_1274":25,"_1275":-5},"ENV",{"_1227":1228,"_1229":1230,"_1231":137,"_1232":1233,"_1234":1235,"_1236":1237,"_1238":1239,"_1240":1241,"_1242":1243,"_1244":1245,"_1246":1247,"_1248":1249,"_1250":1251,"_1252":1253,"_1254":1255},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","811aa22498c9b0b5a47e8d778de579cdb990f332","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

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