[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_439":440,"_441":442},"routes/_app.x.$handle.$name",{"_100":99,"_32":45,"_109":90,"_27":110,"_13":14,"_111":-5,"_11":112,"_113":114,"_115":116,"_117":118,"_119":120,"_20":-5,"_121":-5,"_122":-5,"_123":25,"_124":125,"_126":59,"_127":-5,"_128":-5,"_129":130},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_43":44,"_32":45,"_38":46,"_47":-5,"_48":25,"_49":50,"_51":50,"_52":53,"_54":-5,"_18":55,"_56":57,"_58":59,"_60":-5,"_61":-5,"_62":63,"_64":65,"_66":67,"_68":69,"_70":71,"_72":-5,"_73":74,"_75":74,"_76":77,"_78":77,"_79":77,"_80":74,"_81":74,"_82":83,"_84":85,"_86":87,"_88":25},"version",213,"changes",[19],"aiChatInfo","userId",{"_20":21,"_22":23,"_24":25,"_26":25,"_27":28,"_29":28},"file",{"_30":31,"_32":28,"_33":34,"_35":37,"_38":39,"_40":14,"_41":42,"_24":25},"previous",{"_30":31,"_32":28,"_33":34,"_35":36},"deleted",false,"deletedHere","path","broad_canary.ts","latestPath","fileId","5a90583a-ac88-11f1-bdd8-1607ee4eb77e","name","fileType","script","content","import \"npm:@modelcontextprotocol/client\";\nimport {\n Agent,\n Runner,\n tool,\n webSearchTool,\n setDefaultOpenAIClient,\n setTracingDisabled,\n} from \"npm:@openai/agents\";\nimport { ValTownOpenAI } from \"https://esm.town/v/std/openai/main.ts\";\nimport { blob } from \"https://esm.town/v/std/blob/main.ts\";\nimport { z } from \"npm:zod\";\n\nsetTracingDisabled(true);\nsetDefaultOpenAIClient(new ValTownOpenAI({}));\n\nconst runId=crypto.randomUUID();\nconst token=(await sha(\"skill-token|\"+runId)).slice(0,10);\nconst pool=[\"zod\",\"semver\",\"fast-json-stable-stringify\"];\nconst target=pool[parseInt((await sha(\"target|\"+runId)).slice(0,8),16)%pool.length];\nconst skillA=\"version-parser-a-\"+token;\nconst skillB=\"version-parser-b-\"+token;\nconst skillC=\"canonicalizer-\"+token;\nconst acquired=new Set();\nlet registry:any=null;\nlet phase1Failures=0;\nlet artifactKey:string|null=null;\nconst events:any[]=[];\n\nasync function sha(s:string){\n return [...new Uint8Array(await crypto.subtle.digest(\"SHA-256\",new TextEncoder().encode(s)))]\n .map(b=>b.toString(16).padStart(2,\"0\")).join(\"\");\n}\nfunction log(kind:string,data:any={}){events.push({n:events.length+1,at:new Date().toISOString(),kind,...data})}\n\nconst registryLookup=tool({\n name:\"current_registry_lookup\",\n description:\"Fetch current authoritative NPM registry metadata for the exact mission package.\",\n parameters:z.object({package_name:z.string()}),\n async execute({package_name}){\n if(package_name!==target) return {ok:false,error:\"WRONG_MISSION_PACKAGE\"};\n const url=\"https://registry.npmjs.org/\"+encodeURIComponent(package_name);\n const r=await fetch(url,{headers:{\"accept\":\"application/json\"}});\n if(!r.ok) return {ok:false,error:\"REGISTRY_HTTP_\"+r.status};\n const j=await r.json();\n const latest=String(j?.[\"dist-tags\"]?.latest??\"\");\n if(!latest) return {ok:false,error:\"LATEST_MISSING\"};\n registry={package_name,latest,source_url:url,modified:j?.time?.modified??null};\n log(\"CURRENT_REGISTRY_LOOKUP\",{package_name,latest,source_url:url,modified:registry.modified});\n return {ok:true,...registry};\n }\n});\n\nconst searchSkills=tool({\n name:\"search_runtime_skills\",\n description:\"Discover runtime skills. Skill identifiers are generated after the run starts; do not guess them.\",\n parameters:z.object({query:z.string()}),\n async execute({query}){\n const results=[\n {id:skillA,family:\"version_parse\",input_kind:\"semver_string\",output_kind:\"version_fact\",description:\"Parse a semantic version into a numeric major.\"},\n {id:skillB,family:\"version_parse\",input_kind:\"semver_string\",output_kind:\"version_fact\",description:\"Alternative semantic-version parser with the same typed contract.\"},\n {id:skillC,family:\"canonicalize\",input_kind:\"record\",output_kind:\"canonical_json\",description:\"Deterministically canonicalize a JSON record.\"}\n ];\n log(\"SKILL_SEARCH\",{query,results:results.map(x=>x.id)});\n return {results};\n }\n});\n\nconst acquireSkill=tool({\n name:\"acquire_runtime_skill\",\n description:\"Load a discovered runtime skill before using it.\",\n parameters:z.object({skill_id:z.string()}),\n async execute({skill_id}){\n if(![skillA,skillB,skillC].includes(skill_id)) return {ok:false,error:\"UNKNOWN_SKILL\"};\n if(skill_id===skillA||skill_id===skillB){\n await import(\"npm:semver\");\n }else{\n await import(\"npm:fast-json-stable-stringify\");\n }\n acquired.add(skill_id);\n log(\"SKILL_ACQUIRE\",{skill_id});\n return {ok:true,skill_id};\n }\n});\n\nconst executeSkill=tool({\n name:\"execute_runtime_skill\",\n description:\"Execute an acquired skill. If a runtime failure occurs, use the evidence to replan and acquire/use an alternative skill rather than blind retry.\",\n parameters:z.object({\n skill_id:z.string(),\n version:z.string().nullable(),\n record:z.record(z.string(),z.any()).nullable()\n }),\n async execute({skill_id,version,record}){\n if(!acquired.has(skill_id)) return {ok:false,error:\"SKILL_NOT_ACQUIRED\"};\n if(skill_id===skillA||skill_id===skillB){\n if(!version) return {ok:false,error:\"VERSION_REQUIRED\"};\n if(phase1Failures===0){\n phase1Failures++;\n log(\"SKILL_FAILURE\",{skill_id,error:\"INJECTED_RUNTIME_FAILURE\"});\n return {ok:false,error:\"INJECTED_RUNTIME_FAILURE\",replan_required:true,failed_skill_id:skill_id};\n }\n const semver:any=await import(\"npm:semver\");\n const major=semver.major(version);\n log(\"SKILL_RESULT\",{skill_id,family:\"version_parse\",version,major});\n return {ok:true,output:{version,major}};\n }\n if(skill_id===skillC){\n if(!record) return {ok:false,error:\"RECORD_REQUIRED\"};\n const mod:any=await import(\"npm:fast-json-stable-stringify\");\n const stringify=mod.default??mod;\n const canonical_json=stringify(record);\n log(\"SKILL_RESULT\",{skill_id,family:\"canonicalize\",sha256:await sha(canonical_json)});\n return {ok:true,output:{canonical_json}};\n }\n return {ok:false,error:\"UNKNOWN_SKILL\"};\n }\n});\n\nconst persistArtifact=tool({\n name:\"persist_candidate_artifact\",\n description:\"Persist the final candidate artifact only after using current registry evidence and recovered runtime skills.\",\n parameters:z.object({\n package_name:z.string(),\n version:z.string(),\n major:z.number().int().nonnegative(),\n canonical_json:z.string()\n }),\n async execute({package_name,version,major,canonical_json}){\n if(!registry) return {ok:false,error:\"CURRENT_REGISTRY_EVIDENCE_REQUIRED\"};\n if(package_name!==target||package_name!==registry.package_name||version!==registry.latest) return {ok:false,error:\"STALE_OR_WRONG_PACKAGE_FACT\"};\n const expectedRecord={package:package_name,version,major,source_url:registry.source_url};\n const stableMod:any=await import(\"npm:fast-json-stable-stringify\");\n const stable=stableMod.default??stableMod;\n const expectedCanonical=stable(expectedRecord);\n if(canonical_json!==expectedCanonical) return {ok:false,error:\"CANONICAL_RECORD_MISMATCH\",expected_shape:Object.keys(expectedRecord)};\n const semver:any=await import(\"npm:semver\");\n if(semver.major(version)!==major) return {ok:false,error:\"MAJOR_MISMATCH\"};\n const artifact={\n schema:\"FIRST_REAL_SUPERHERO_BROAD_CAPABILITY_CANARY_ARTIFACT_V1\",\n run_id:runId,\n candidate_id:\"VAL_NATIVE_LUNA_BROAD_CAPABILITY_CANARY_V1\",\n package:package_name,\n version,\n major,\n source_url:registry.source_url,\n source_modified:registry.modified,\n canonical_json,\n injected_failure_count:phase1Failures,\n acquired_skill_ids:[...acquired],\n created_at:new Date().toISOString()\n };\n const text=JSON.stringify(artifact);\n const digest=await sha(text);\n artifactKey=\"broad-canary/\"+runId+\"/artifact.json\";\n await blob.set(artifactKey,text);\n const rb=await blob.get(artifactKey).then(r=>r.text());\n const readbackSha=await sha(rb);\n log(\"ARTIFACT_PERSIST\",{artifact_key:artifactKey,sha256:digest,readback_sha256:readbackSha});\n return {ok:true,artifact_key:artifactKey,sha256:digest,readback_sha256:readbackSha,readback_exact:digest===readbackSha};\n }\n});\n\nconst agent=new Agent({\n name:\"BroadCapabilityCanary\",\n model:\"gpt-5.6-luna\",\n instructions:[\n \"You are under a held-out first-real-superhero capability canary.\",\n \"Goal: complete the mission using current evidence and runtime-acquired capabilities, not memory guesses.\",\n \"FIRST use web search to research the package's current stable release and identify a primary source.\",\n \"Then call current_registry_lookup for authoritative live NPM metadata.\",\n \"Discover runtime skills; acquire them before execution.\",\n \"Compose a version parser and canonicalizer.\",\n \"The first version-parser execution will fail deliberately. Treat it as real failure evidence: acquire/use the alternative parser. Do not blind-retry the failed skill.\",\n \"Persist the final artifact only after the recovered path succeeds.\",\n \"Do not claim independent verification. A separate program will adjudicate after you finish.\",\n \"When persistence succeeds, return only CANARY_SUBMITTED.\"\n ].join(\"\\n\"),\n tools:[\n webSearchTool({searchContextSize:\"low\"}),\n registryLookup,\n searchSkills,\n acquireSkill,\n executeSkill,\n persistArtifact\n ],\n modelSettings:{\n reasoning:{effort:\"medium\"},\n text:{verbosity:\"low\"}\n }\n});\n\nconst started=new Date().toISOString();\nlet finalOutput:any=null,error:string|null=null,historySummary:any[]=[];\ntry{\n const result=await new Runner().run(agent,\n \"Novel mission package: \"+target+\". Produce a durable verified-candidate record containing the current stable version, its numeric major, the authoritative registry source URL, and a deterministic canonical JSON representation.\",\n {maxTurns:14}\n );\n finalOutput=result.finalOutput??null;\n historySummary=(result.history??[]).map((x:any)=>({\n type:x?.type??null,\n name:x?.name??x?.toolName??null,\n provider_type:x?.providerData?.type??null\n })).slice(0,100);\n}catch(e){error=e instanceof Error?e.message:String(e)}\n\nconst webSearchSeen=historySummary.some((x:any)=>x.type===\"hosted_tool_call\"&&x.name===\"web_search_call\");\nconst summary={\n schema:\"FIRST_REAL_SUPERHERO_BROAD_CAPABILITY_CANARY_RUN_V1\",\n classification:\"CANDIDATE_NONAUTHORITY_PREBOOT_EVIDENCE\",\n candidate_id:\"VAL_NATIVE_LUNA_BROAD_CAPABILITY_CANARY_V1\",\n run_id:runId,\n started_at:started,\n completed_at:new Date().toISOString(),\n target_package:target,\n requested_model:\"gpt-5.6-luna\",\n final_output:finalOutput,\n error,\n web_search_seen:webSearchSeen,\n current_registry_seen:events.some(e=>e.kind===\"CURRENT_REGISTRY_LOOKUP\"),\n skill_discovery_seen:events.some(e=>e.kind===\"SKILL_SEARCH\"),\n skill_acquisition_count:events.filter(e=>e.kind===\"SKILL_ACQUIRE\").length,\n injected_failure_seen:events.some(e=>e.kind===\"SKILL_FAILURE\"),\n recovered_alternative_seen:(()=>{\n const fail=events.find(e=>e.kind===\"SKILL_FAILURE\");\n return !!fail&&events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"version_parse\"&&e.n>fail.n&&e.skill_id!==fail.skill_id);\n })(),\n composition_seen:events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"version_parse\")&&events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"canonicalize\"),\n durable_artifact_seen:events.some(e=>e.kind===\"ARTIFACT_PERSIST\"),\n artifact_key:artifactKey,\n candidate_submission_pass:error===null&&finalOutput===\"CANARY_SUBMITTED\"&&webSearchSeen&&!!artifactKey,\n history_summary:historySummary,\n events,\n explicit_nonclaims:[\n \"This run is not canonical Brain participation.\",\n \"This run is not production-qualified external-worker admission.\",\n \"This run does not increment P_real.\",\n \"Independent verification is intentionally separate and not claimed here.\"\n ],\n canonical_brain_mutation:false,\n p_real_increment:0,\n human_authority_approval:false,\n direct_sprites_calls:0,\n additional_out_of_pocket_spend_usd:0\n};\nconst summaryText=JSON.stringify(summary);\nconst summarySha=await sha(summaryText);\nawait blob.set(\"broad-canary/\"+runId+\"/candidate-run.json\",summaryText);\nawait blob.setJSON(\"broad-canary/LATEST.json\",{run_id:runId,artifact_key:artifactKey,summary_key:\"broad-canary/\"+runId+\"/candidate-run.json\",summary_sha256:summarySha,candidate_submission_pass:summary.candidate_submission_pass});\nconsole.log(JSON.stringify({schema:summary.schema,run_id:runId,target_package:target,candidate_submission_pass:summary.candidate_submission_pass,error,final_output:finalOutput,web_search_seen:webSearchSeen,skill_acquisition_count:summary.skill_acquisition_count,injected_failure_seen:summary.injected_failure_seen,recovered_alternative_seen:summary.recovered_alternative_seen,composition_seen:summary.composition_seen,durable_artifact_seen:summary.durable_artifact_seen,artifact_key:artifactKey,summary_sha256:summarySha,p_real_increment:0},null,2));","import \"npm:@modelcontextprotocol/client\";\nimport {\n Agent,\n Runner,\n tool,\n webSearchTool,\n setDefaultOpenAIClient,\n setTracingDisabled,\n} from \"npm:@openai/agents\";\nimport { ValTownOpenAI } from \"https://esm.town/v/std/openai/main.ts\";\nimport { blob } from \"https://esm.town/v/std/blob/main.ts\";\nimport { z } from \"npm:zod\";\n\nsetTracingDisabled(true);\nsetDefaultOpenAIClient(new ValTownOpenAI({}));\n\nconst runId=crypto.randomUUID();\nconst token=(await sha(\"skill-token|\"+runId)).slice(0,10);\nconst pool=[\"zod\",\"semver\",\"fast-json-stable-stringify\"];\nconst target=pool[parseInt((await sha(\"target|\"+runId)).slice(0,8),16)%pool.length];\nconst skillA=\"version-parser-a-\"+token;\nconst skillB=\"version-parser-b-\"+token;\nconst skillC=\"canonicalizer-\"+token;\nconst acquired=new Set();\nlet registry:any=null;\nlet phase1Failures=0;\nlet artifactKey:string|null=null;\nconst events:any[]=[];\n\nasync function sha(s:string){\n return [...new Uint8Array(await crypto.subtle.digest(\"SHA-256\",new TextEncoder().encode(s)))]\n .map(b=>b.toString(16).padStart(2,\"0\")).join(\"\");\n}\nfunction log(kind:string,data:any={}){events.push({n:events.length+1,at:new Date().toISOString(),kind,...data})}\n\nconst registryLookup=tool({\n name:\"current_registry_lookup\",\n description:\"Fetch current authoritative NPM registry metadata for the exact mission package.\",\n parameters:z.object({package_name:z.string()}),\n async execute({package_name}){\n if(package_name!==target) return {ok:false,error:\"WRONG_MISSION_PACKAGE\"};\n const url=\"https://registry.npmjs.org/\"+encodeURIComponent(package_name);\n const r=await fetch(url,{headers:{\"accept\":\"application/json\"}});\n if(!r.ok) return {ok:false,error:\"REGISTRY_HTTP_\"+r.status};\n const j=await r.json();\n const latest=String(j?.[\"dist-tags\"]?.latest??\"\");\n if(!latest) return {ok:false,error:\"LATEST_MISSING\"};\n registry={package_name,latest,source_url:url,modified:j?.time?.modified??null};\n log(\"CURRENT_REGISTRY_LOOKUP\",{package_name,latest,source_url:url,modified:registry.modified});\n return {ok:true,...registry};\n }\n});\n\nconst searchSkills=tool({\n name:\"search_runtime_skills\",\n description:\"Discover runtime skills. Skill identifiers are generated after the run starts; do not guess them.\",\n parameters:z.object({query:z.string()}),\n async execute({query}){\n const results=[\n {id:skillA,family:\"version_parse\",input_kind:\"semver_string\",output_kind:\"version_fact\",description:\"Parse a semantic version into a numeric major.\"},\n {id:skillB,family:\"version_parse\",input_kind:\"semver_string\",output_kind:\"version_fact\",description:\"Alternative semantic-version parser with the same typed contract.\"},\n {id:skillC,family:\"canonicalize\",input_kind:\"record\",output_kind:\"canonical_json\",description:\"Deterministically canonicalize a JSON record.\"}\n ];\n log(\"SKILL_SEARCH\",{query,results:results.map(x=>x.id)});\n return {results};\n }\n});\n\nconst acquireSkill=tool({\n name:\"acquire_runtime_skill\",\n description:\"Load a discovered runtime skill before using it.\",\n parameters:z.object({skill_id:z.string()}),\n async execute({skill_id}){\n if(![skillA,skillB,skillC].includes(skill_id)) return {ok:false,error:\"UNKNOWN_SKILL\"};\n if(skill_id===skillA||skill_id===skillB){\n await import(\"npm:semver\");\n }else{\n await import(\"npm:fast-json-stable-stringify\");\n }\n acquired.add(skill_id);\n log(\"SKILL_ACQUIRE\",{skill_id});\n return {ok:true,skill_id};\n }\n});\n\nconst executeSkill=tool({\n name:\"execute_runtime_skill\",\n description:\"Execute an acquired skill. If a runtime failure occurs, use the evidence to replan and acquire/use an alternative skill rather than blind retry.\",\n parameters:z.object({\n skill_id:z.string(),\n version:z.string().nullable(),\n record_json:z.string().nullable()\n }),\n async execute({skill_id,version,record}){\n if(!acquired.has(skill_id)) return {ok:false,error:\"SKILL_NOT_ACQUIRED\"};\n if(skill_id===skillA||skill_id===skillB){\n if(!version) return {ok:false,error:\"VERSION_REQUIRED\"};\n if(phase1Failures===0){\n phase1Failures++;\n log(\"SKILL_FAILURE\",{skill_id,error:\"INJECTED_RUNTIME_FAILURE\"});\n return {ok:false,error:\"INJECTED_RUNTIME_FAILURE\",replan_required:true,failed_skill_id:skill_id};\n }\n const semver:any=await import(\"npm:semver\");\n const major=semver.major(version);\n log(\"SKILL_RESULT\",{skill_id,family:\"version_parse\",version,major});\n return {ok:true,output:{version,major}};\n }\n if(skill_id===skillC){\n if(!record) return {ok:false,error:\"RECORD_REQUIRED\"};\n const mod:any=await import(\"npm:fast-json-stable-stringify\");\n const stringify=mod.default??mod;\n const canonical_json=stringify(record);\n log(\"SKILL_RESULT\",{skill_id,family:\"canonicalize\",sha256:await sha(canonical_json)});\n return {ok:true,output:{canonical_json}};\n }\n return {ok:false,error:\"UNKNOWN_SKILL\"};\n }\n});\n\nconst persistArtifact=tool({\n name:\"persist_candidate_artifact\",\n description:\"Persist the final candidate artifact only after using current registry evidence and recovered runtime skills.\",\n parameters:z.object({\n package_name:z.string(),\n version:z.string(),\n major:z.number().int().nonnegative(),\n canonical_json:z.string()\n }),\n async execute({package_name,version,major,canonical_json}){\n if(!registry) return {ok:false,error:\"CURRENT_REGISTRY_EVIDENCE_REQUIRED\"};\n if(package_name!==target||package_name!==registry.package_name||version!==registry.latest) return {ok:false,error:\"STALE_OR_WRONG_PACKAGE_FACT\"};\n const expectedRecord={package:package_name,version,major,source_url:registry.source_url};\n const stableMod:any=await import(\"npm:fast-json-stable-stringify\");\n const stable=stableMod.default??stableMod;\n const expectedCanonical=stable(expectedRecord);\n if(canonical_json!==expectedCanonical) return {ok:false,error:\"CANONICAL_RECORD_MISMATCH\",expected_shape:Object.keys(expectedRecord)};\n const semver:any=await import(\"npm:semver\");\n if(semver.major(version)!==major) return {ok:false,error:\"MAJOR_MISMATCH\"};\n const artifact={\n schema:\"FIRST_REAL_SUPERHERO_BROAD_CAPABILITY_CANARY_ARTIFACT_V1\",\n run_id:runId,\n candidate_id:\"VAL_NATIVE_LUNA_BROAD_CAPABILITY_CANARY_V1\",\n package:package_name,\n version,\n major,\n source_url:registry.source_url,\n source_modified:registry.modified,\n canonical_json,\n injected_failure_count:phase1Failures,\n acquired_skill_ids:[...acquired],\n created_at:new Date().toISOString()\n };\n const text=JSON.stringify(artifact);\n const digest=await sha(text);\n artifactKey=\"broad-canary/\"+runId+\"/artifact.json\";\n await blob.set(artifactKey,text);\n const rb=await blob.get(artifactKey).then(r=>r.text());\n const readbackSha=await sha(rb);\n log(\"ARTIFACT_PERSIST\",{artifact_key:artifactKey,sha256:digest,readback_sha256:readbackSha});\n return {ok:true,artifact_key:artifactKey,sha256:digest,readback_sha256:readbackSha,readback_exact:digest===readbackSha};\n }\n});\n\nconst agent=new Agent({\n name:\"BroadCapabilityCanary\",\n model:\"gpt-5.6-luna\",\n instructions:[\n \"You are under a held-out first-real-superhero capability canary.\",\n \"Goal: complete the mission using current evidence and runtime-acquired capabilities, not memory guesses.\",\n \"FIRST use web search to research the package's current stable release and identify a primary source.\",\n \"Then call current_registry_lookup for authoritative live NPM metadata.\",\n \"Discover runtime skills; acquire them before execution.\",\n \"Compose a version parser and canonicalizer.\",\n \"The first version-parser execution will fail deliberately. Treat it as real failure evidence: acquire/use the alternative parser. Do not blind-retry the failed skill.\",\n \"Persist the final artifact only after the recovered path succeeds.\",\n \"Do not claim independent verification. A separate program will adjudicate after you finish.\",\n \"When persistence succeeds, return only CANARY_SUBMITTED.\"\n ].join(\"\\n\"),\n tools:[\n webSearchTool({searchContextSize:\"low\"}),\n registryLookup,\n searchSkills,\n acquireSkill,\n executeSkill,\n persistArtifact\n ],\n modelSettings:{\n reasoning:{effort:\"medium\"},\n text:{verbosity:\"low\"}\n }\n});\n\nconst started=new Date().toISOString();\nlet finalOutput:any=null,error:string|null=null,historySummary:any[]=[];\ntry{\n const result=await new Runner().run(agent,\n \"Novel mission package: \"+target+\". Produce a durable verified-candidate record containing the current stable version, its numeric major, the authoritative registry source URL, and a deterministic canonical JSON representation.\",\n {maxTurns:14}\n );\n finalOutput=result.finalOutput??null;\n historySummary=(result.history??[]).map((x:any)=>({\n type:x?.type??null,\n name:x?.name??x?.toolName??null,\n provider_type:x?.providerData?.type??null\n })).slice(0,100);\n}catch(e){error=e instanceof Error?e.message:String(e)}\n\nconst webSearchSeen=historySummary.some((x:any)=>x.type===\"hosted_tool_call\"&&x.name===\"web_search_call\");\nconst summary={\n schema:\"FIRST_REAL_SUPERHERO_BROAD_CAPABILITY_CANARY_RUN_V1\",\n classification:\"CANDIDATE_NONAUTHORITY_PREBOOT_EVIDENCE\",\n candidate_id:\"VAL_NATIVE_LUNA_BROAD_CAPABILITY_CANARY_V1\",\n run_id:runId,\n started_at:started,\n completed_at:new Date().toISOString(),\n target_package:target,\n requested_model:\"gpt-5.6-luna\",\n final_output:finalOutput,\n error,\n web_search_seen:webSearchSeen,\n current_registry_seen:events.some(e=>e.kind===\"CURRENT_REGISTRY_LOOKUP\"),\n skill_discovery_seen:events.some(e=>e.kind===\"SKILL_SEARCH\"),\n skill_acquisition_count:events.filter(e=>e.kind===\"SKILL_ACQUIRE\").length,\n injected_failure_seen:events.some(e=>e.kind===\"SKILL_FAILURE\"),\n recovered_alternative_seen:(()=>{\n const fail=events.find(e=>e.kind===\"SKILL_FAILURE\");\n return !!fail&&events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"version_parse\"&&e.n>fail.n&&e.skill_id!==fail.skill_id);\n })(),\n composition_seen:events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"version_parse\")&&events.some(e=>e.kind===\"SKILL_RESULT\"&&e.family===\"canonicalize\"),\n durable_artifact_seen:events.some(e=>e.kind===\"ARTIFACT_PERSIST\"),\n artifact_key:artifactKey,\n candidate_submission_pass:error===null&&finalOutput===\"CANARY_SUBMITTED\"&&webSearchSeen&&!!artifactKey,\n history_summary:historySummary,\n events,\n explicit_nonclaims:[\n \"This run is not canonical Brain participation.\",\n \"This run is not production-qualified external-worker admission.\",\n \"This run does not increment P_real.\",\n \"Independent verification is intentionally separate and not claimed here.\"\n ],\n canonical_brain_mutation:false,\n p_real_increment:0,\n human_authority_approval:false,\n direct_sprites_calls:0,\n additional_out_of_pocket_spend_usd:0\n};\nconst summaryText=JSON.stringify(summary);\nconst summarySha=await sha(summaryText);\nawait blob.set(\"broad-canary/\"+runId+\"/candidate-run.json\",summaryText);\nawait blob.setJSON(\"broad-canary/LATEST.json\",{run_id:runId,artifact_key:artifactKey,summary_key:\"broad-canary/\"+runId+\"/candidate-run.json\",summary_sha256:summarySha,candidate_submission_pass:summary.candidate_submission_pass});\nconsole.log(JSON.stringify({schema:summary.schema,run_id:runId,target_package:target,candidate_submission_pass:summary.candidate_submission_pass,error,final_output:finalOutput,web_search_seen:webSearchSeen,skill_acquisition_count:summary.skill_acquisition_count,injected_failure_seen:summary.injected_failure_seen,recovered_alternative_seen:summary.recovered_alternative_seen,composition_seen:summary.composition_seen,durable_artifact_seen:summary.durable_artifact_seen,artifact_key:artifactKey,summary_sha256:summarySha,p_real_increment:0},null,2));","createdAt",["D",1788983747824],"branchVersion","branchId","48d8eb0e-3c3d-4d78-aa72-0c0d2ae7419d","id","e3b5ac87-a441-436c-b6f2-08a3a84eeb74","brain-meta-os-recovery-staging-20260909",["D",1788919082638],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Safe staging for Brain self-experiment control plane","imageUrl","6be0fc5c-1fef-4bd6-a1e1-67a3f8c0764e","pinnedFileId","4cdf72ba-ac7f-11f1-992f-1607ee4eb77e","pinPreview",true,"pinMigrated","screenshotVersion","likeCount",0,"orgId","01a0715b-703f-741f-ab35-c85020e4a5e0","tursoName","e3b5ac87a441436cb6f208a3a84eeb74","tursoHostname","e3b5ac87a441436cb6f208a3a84eeb74-val-town.aws-us-east-2.turso.io","tursoMeasuredAt",["D",1789530642963],"pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_100":99,"_108":104},"org",{"_100":99,"_101":102,"_103":104,"_18":55,"_105":106,"_107":25},"branch",{"_13":89,"_32":90,"_43":42,"_91":44,"_92":-5,"_93":-5,"_94":-5,"_95":-5,"_96":-5,"_97":45,"_98":99},"isOwned",233,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","mosadek","handle","displayName","Mo 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function probe(cmd:string,args:string[]){\n try{\n const p=new Deno.Command(cmd,{args,stdout:\"piped\",stderr:\"piped\"}).output();\n const r=await p;\n return {cmd,args,code:r.code,stdout:new TextDecoder().decode(r.stdout).slice(0,1000),stderr:new TextDecoder().decode(r.stderr).slice(0,1000)};\n }catch(e){return{cmd,args,error:String(e)}}\n}\nconsole.log(JSON.stringify({\n schema:\"VAL_TOWN_SUBPROCESS_CAPABILITY_PROBE_V1\",\n results:[\n await probe(\"node\",[\"--version\"]),\n await probe(\"npm\",[\"--version\"]),\n await probe(\"npx\",[\"--yes\",\"eve\",\"--version\"])\n ]\n},null,2));","label",[156],"dc9e727a-76b7-4e3a-91e5-ed3be5b31ed1","superhero_jit_registry_v1.ts","e7a87320-ac87-11f1-a674-1607ee4eb77e",208,["D",1788983513138],"http","const sources:any = {\n \"nebula-r6\": {id:\"nebula-r6\", domain:\"nebula\", authority:40, freshness:\"STALE\", version:\"R6\", scope:\"NebulaPack\", content:\"STALE. Sort records by n ascending. Token = reverse(label)+':'+base36(n*5+3). Join tokens with '|'. Return sha256(UTF-8 joined string).\"},\n \"nebula-r7\": {id:\"nebula-r7\", domain:\"nebula\", authority:100, freshness:\"CURRENT_NONCE_BOUND\", version:\"R7\", scope:\"NebulaPack goal NEBULA-7C91\", content:\"AUTHORITATIVE R7. Sort records by n ascending, then label ascending. Token = reverse(label)+':'+base36(n*7+3). Join tokens with '|'. Return lowercase sha256 hex of the UTF-8 joined string.\"},\n \"nebula-r8\": {id:\"nebula-r8\", domain:\"nebula\", authority:100, freshness:\"CURRENT_NONCE_BOUND\", version:\"R8\", scope:\"NebulaPack goal NEBULA-8F24\", content:\"AUTHORITATIVE R8. Supersedes R7 for NEBULA-8F24. Sort records by n descending, then label ascending. Token = reverse(label)+':'+base36(n*11+1). Join tokens with '~'. Return lowercase sha256 hex of the UTF-8 joined string.\"},\n \"orchid-v1\": {id:\"orchid-v1\", domain:\"orchid\", authority:30, freshness:\"STALE\", version:\"V1\", scope:\"OrchidRoute\", content:\"STALE. Path score is sum(time + risk). Red nodes allowed.\"},\n \"orchid-v2\": {id:\"orchid-v2\", domain:\"orchid\", authority:100, freshness:\"CURRENT_NONCE_BOUND\", version:\"V2\", scope:\"OrchidRoute goal ORCHID-2D55\", content:\"AUTHORITATIVE V2. A valid path may not enter nodes marked red. Edge score = time + 2*risk. Minimize total score; ties break by lexicographically smaller full node sequence.\"}\n};\nconst skills:any = {\n \"reverse-a\": {id:\"reverse-a\", role:\"reverse\", description:\"Reverse a Unicode string by code points.\", input:\"{text:string}\", code:\"(input)=>Array.from(String(input.text)).reverse().join('')\"},\n \"reverse-b\": {id:\"reverse-b\", role:\"reverse\", description:\"Independent equivalent Unicode string reverse.\", input:\"{text:string}\", code:\"(input)=>[...String(input.text)].reduceRight((a,c)=>a+c,'')\"},\n \"base36-a\": {id:\"base36-a\", role:\"base36\", description:\"Encode a nonnegative integer as lowercase base36.\", input:\"{number:number}\", code:\"(input)=>{const n=Number(input.number); if(!Number.isInteger(n)||n<0) throw new Error('BAD_INT'); return n.toString(36)}\"},\n \"base36-b\": {id:\"base36-b\", role:\"base36\", description:\"Independent equivalent nonnegative integer base36 encoder.\", input:\"{number:number}\", code:\"(input)=>{let n=Number(input.number); if(!Number.isInteger(n)||n<0) throw new Error('BAD_INT'); const d='0123456789abcdefghijklmnopqrstuvwxyz'; if(n===0)return '0'; let s=''; while(n){s=d[n%36]+s;n=Math.floor(n/36)} return s}\"},\n \"sha256-a\": {id:\"sha256-a\", role:\"sha256\", description:\"Compute lowercase SHA-256 hex of UTF-8 text.\", input:\"{text:string}\", async:true, code:\"async(input)=>{const b=new TextEncoder().encode(String(input.text)); const h=await crypto.subtle.digest('SHA-256',b); return [...new Uint8Array(h)].map(x=>x.toString(16).padStart(2,'0')).join('')}\"},\n \"sha256-b\": {id:\"sha256-b\", role:\"sha256\", description:\"Independent equivalent WebCrypto SHA-256 hex skill.\", input:\"{text:string}\", async:true, code:\"async(input)=>{const h=await crypto.subtle.digest('SHA-256',new TextEncoder().encode(String(input.text))); return Array.from(new Uint8Array(h),x=>x.toString(16).padStart(2,'0')).join('')}\"},\n \"route-a\": {id:\"route-a\", role:\"route\", description:\"Compute deterministic minimum-score path for a graph given forbidden nodes and edge score formula time + riskWeight*risk.\", input:\"{nodes,edges,start,end,redNodes,riskWeight}\", code:\"(input)=>{const {nodes,edges,start,end,redNodes=[],riskWeight=2}=input; const red=new Set(redNodes); const adj={}; for(const n of nodes)adj[n]=[]; for(const e of edges){adj[e.from].push(e)} let q=[{n:start,c:0,p:[start]}],best=new Map(); while(q.length){q.sort((a,b)=>a.c-b.c||a.p.join('>').localeCompare(b.p.join('>'))); const x=q.shift(); const k=x.n; const old=best.get(k); const ps=x.p.join('>'); if(old&&(old.c{const red=new Set(input.redNodes||[]),dist={[input.start]:0},paths={[input.start]:[input.start]},done=new Set(); while(true){let u=null; for(const n of input.nodes){if(done.has(n)||dist[n]===undefined)continue;if(u===null||dist[n]')')))u=n} if(u===null)break;if(u===input.end)return {path:paths[u],score:dist[u]};done.add(u);for(const e of input.edges.filter((x:any)=>x.from===u)){if(red.has(e.to))continue;const nd=dist[u]+e.time+(input.riskWeight??2)*e.risk,np=[...paths[u],e.to];if(dist[e.to]===undefined||nd')'))){dist[e.to]=nd;paths[e.to]=np}}}throw new Error('NO_PATH')}\"}\n};\nasync function sha256(s:string){const h=await crypto.subtle.digest(\"SHA-256\",new TextEncoder().encode(s));return Array.from(new Uint8Array(h),x=>x.toString(16).padStart(2,\"0\")).join(\"\")}\nexport default async function(req:Request){\n const u=new URL(req.url), kind=u.searchParams.get(\"kind\");\n if(kind===\"source_catalog\"){const domain=u.searchParams.get(\"domain\");return Response.json(Object.values(sources).filter((x:any)=>x.domain===domain).map(({content,...m}:any)=>m))}\n if(kind===\"source\"){const x=sources[u.searchParams.get(\"id\")||\"\"];return x?Response.json(x):new Response(\"not found\",{status:404})}\n if(kind===\"skill_catalog\"){const q=(u.searchParams.get(\"q\")||\"\").toLowerCase();const arr=[];for(const x of Object.values(skills) as any[]){if(!q||x.role.includes(q)||x.description.toLowerCase().includes(q)){const {code,...m}=x;arr.push({...m,code_sha256:await sha256(code)})}}return Response.json(arr)}\n if(kind===\"skill\"){const x=skills[u.searchParams.get(\"id\")||\"\"];if(!x)return new Response(\"not found\",{status:404});return Response.json({...x,code_sha256:await sha256(x.code)})}\n return Response.json({schema:\"SUPERHERO_JIT_REGISTRY_V1\",sources:Object.keys(sources).length,skills:Object.keys(skills).length});\n}",[166],"8109c344-54c6-47e6-b81a-9dfb1ac19787","superhero_jit_closed_loop_v1.ts","27e9e0f4-ac88-11f1-b969-1607ee4eb77e",210,["D",1788983621016],"import \"npm:@modelcontextprotocol/client\";\nimport {Agent,Runner,tool,setTracingDisabled,OpenAIChatCompletionsModel} from \"npm:@openai/agents\";\nimport OpenAI from \"npm:openai\";\nimport {z} from \"npm:zod\";\n\nsetTracingDisabled(true);\nconst REG=\"https://mosadek--e7a87320ac8711f1a6741607ee4eb77e.web.val.run/\";\nconst client=new OpenAI({apiKey:\"placeholder-not-a-secret\",baseURL:\"https://api.kilo.ai/api/gateway\"});\nconst modelName=\"nex-agi/nex-n2.5-mini:free\";\n\nasync function hash(s:string){const h=await crypto.subtle.digest(\"SHA-256\",new TextEncoder().encode(s));return Array.from(new Uint8Array(h),x=>x.toString(16).padStart(2,\"0\")).join(\"\")}\nfunction rev(s:string){return Array.from(s).reverse().join(\"\")}\nasync function nebulaExpected(records:any[],v:\"R7\"|\"R8\"){\n const rows=[...records].sort(v===\"R7\" ? ((a,b)=>a.n-b.n||a.label.localeCompare(b.label)) : ((a,b)=>b.n-a.n||a.label.localeCompare(b.label)));\n const mul=v===\"R7\"?7:11, add=v===\"R7\"?3:1, sep=v===\"R7\"?\"|\":\"~\";\n const text=rows.map(r=>rev(r.label)+\":\"+((r.n*mul+add).toString(36))).join(sep);\n return await hash(text);\n}\nfunction routeExpected(input:any){\n const red=new Set(input.redNodes||[]),adj:any={}; for(const n of input.nodes)adj[n]=[];\n for(const e of input.edges)adj[e.from].push(e);\n let q:any[]=[{n:input.start,c:0,p:[input.start]}],best=new Map();\n while(q.length){q.sort((a,b)=>a.c-b.c||a.p.join(\">\").localeCompare(b.p.join(\">\")));const x=q.shift(),ps=x.p.join(\">\"),old=best.get(x.n);\n if(old&&(old.c();\nconst traces:any[]=[];\n\nfunction state(id:string){return states[id]??=( {plan:null,sourceReads:[],skillDiscovery:[],acquired:new Map(),executed:[],failedSkill:null,injected:false,verified:false,verifiedAnswer:null,memoryRead:false,committed:false} )}\n\nasync function liveZod(){\n const u=\"https://registry.npmjs.org/zod/latest\",r=await fetch(u); if(!r.ok)throw new Error(\"NPM_\"+r.status); const j=await r.json();\n return {id:\"npm-zod-live\",authority:100,freshness:\"LIVE_FETCH\",scope:\"npm:zod latest\",url:u,version:j.version,fetched_at:new Date().toISOString()};\n}\nasync function callRegistry(params:Record){const u=new URL(REG);for(const[k,v]of Object.entries(params))u.searchParams.set(k,v);const r=await fetch(u);if(!r.ok)throw new Error(\"REG_\"+r.status);return await r.json()}\n\nconst runtime=tool({\n name:\"runtime\",\n description:\"Generic goal-to-capability runtime. Actions: record_plan (must be first; payload has success_conditions,requirements,unknowns,dependencies,needed_capabilities); read_memory; discover_sources {domain}; read_source {id}; discover_skills {query}; acquire_skill {id}; execute_skill {id,input}; verify {answer}; commit {answer,summary,reusable,demoted}. Runtime sources/skills are not in your prompt and must be discovered. On a skill failure, do not retry the same skill id; acquire a materially alternative skill.\",\n parameters:z.object({action:z.enum([\"record_plan\",\"read_memory\",\"discover_sources\",\"read_source\",\"discover_skills\",\"acquire_skill\",\"execute_skill\",\"verify\",\"commit\"]),goalId:z.string(),payload:z.string()}),\n async execute({action,goalId,payload}){\n const t=Date.now(),s=state(goalId); let p:any={};try{p=payload?JSON.parse(payload):{}}catch{return JSON.stringify({ok:false,error:\"BAD_PAYLOAD_JSON\"})}\n if(goalId!==currentGoal)return JSON.stringify({ok:false,error:\"WRONG_ACTIVE_GOAL\"});\n if(action!==\"record_plan\"&&!s.plan)return JSON.stringify({ok:false,error:\"PLAN_REQUIRED_BEFORE_ACTION\"});\n try{\n let out:any;\n if(action===\"record_plan\"){\n if(s.plan)return JSON.stringify({ok:false,error:\"PLAN_ALREADY_RECORDED\"});\n const req=[\"success_conditions\",\"requirements\",\"unknowns\",\"dependencies\",\"needed_capabilities\"];if(req.some(k=>!p[k]))return JSON.stringify({ok:false,error:\"INCOMPLETE_SELF_DERIVED_PLAN\",required:req});\n s.plan=p;out={ok:true,accepted:true};\n } else if(action===\"read_memory\"){\n s.memoryRead=true;out={ok:true,records:controllerMemory};\n } else if(action===\"discover_sources\"){\n let rows=await callRegistry({kind:\"source_catalog\",domain:String(p.domain||goals[goalId].domain)});\n if(goals[goalId].domain===\"orchid\")rows=[...rows,{id:\"npm-zod-live\",domain:\"orchid\",authority:100,freshness:\"LIVE_FETCH_REQUIRED\",version:\"LIVE\",scope:\"npm authoritative current zod latest\"}];\n out={ok:true,sources:rows};\n } else if(action===\"read_source\"){\n if(p.id===\"npm-zod-live\"){const x=await liveZod();s.sourceReads.push(x);out={ok:true,source:x};}\n else {const x=await callRegistry({kind:\"source\",id:String(p.id)});s.sourceReads.push({id:x.id,authority:x.authority,freshness:x.freshness,version:x.version,scope:x.scope});out={ok:true,source:x};}\n } else if(action===\"discover_skills\"){\n const rows=await callRegistry({kind:\"skill_catalog\",q:String(p.query||\"\")});s.skillDiscovery.push({query:p.query,count:rows.length,ids:rows.map((x:any)=>x.id)});out={ok:true,skills:rows};\n } else if(action===\"acquire_skill\"){\n const x=await callRegistry({kind:\"skill\",id:String(p.id)});const got=await hash(x.code);if(got!==x.code_sha256)throw new Error(\"SKILL_HASH_MISMATCH\");\n const fn=(new Function(\"return (\"+x.code+\")\"))();s.acquired.set(x.id,{...x,fn});const reused=verifiedSkillCache.has(x.id);out={ok:true,acquired:{id:x.id,role:x.role,code_sha256:x.code_sha256,reused_verified_cognitive_capital:reused}};\n } else if(action===\"execute_skill\"){\n const x=s.acquired.get(String(p.id));if(!x)return JSON.stringify({ok:false,error:\"SKILL_NOT_ACQUIRED\",id:p.id});\n if(s.failedSkill===p.id)return JSON.stringify({ok:false,error:\"SAME_ROUTE_STILL_FAILED\",id:p.id,requires_alternative:true});\n if(goals[goalId].injectFailure&&!s.injected){s.injected=true;s.failedSkill=p.id;s.executed.push({id:p.id,pass:false,error:\"INJECTED_SKILL_FAILURE\"});out={ok:false,error:\"INJECTED_SKILL_FAILURE\",id:p.id,requires_alternative:true};}\n else {const result=await x.fn(p.input);s.executed.push({id:p.id,role:x.role,pass:true,input:p.input,result});out={ok:true,id:p.id,role:x.role,result};}\n } else if(action===\"verify\"){\n let expected=\"\";\n if(goalId===\"NEBULA-7C91\"||goalId===\"NEBULA-8F24\") expected=await nebulaExpected(goals[goalId].records,goals[goalId].version);\n else {const nz=s.sourceReads.find((x:any)=>x.id===\"npm-zod-live\");if(!nz)return JSON.stringify({ok:false,error:\"MISSING_LIVE_NPM_SOURCE\"});const rr=routeExpected(goals[goalId].graph);expected=nz.version+\"|\"+rr.path.join(\">\")+\"|\"+rr.score;}\n const authId=goalId===\"NEBULA-7C91\"?\"nebula-r7\":goalId===\"NEBULA-8F24\"?\"nebula-r8\":\"orchid-v2\";\n if(!s.sourceReads.some((x:any)=>x.id===authId))return JSON.stringify({ok:false,error:\"MISSING_AUTHORITATIVE_RUNTIME_SOURCE\",required:authId});\n if(goalId===\"ORCHID-2D55\"&&!s.sourceReads.some((x:any)=>x.id===\"npm-zod-live\"))return JSON.stringify({ok:false,error:\"MISSING_LIVE_NPM_SOURCE\"});\n if(!s.executed.some((x:any)=>x.pass))return JSON.stringify({ok:false,error:\"NO_ACQUIRED_SKILL_CAUSALLY_EXECUTED\"});\n if(goalId===\"NEBULA-7C91\"&&(!s.injected||!s.executed.some((x:any)=>x.pass&&x.id!==s.failedSkill)))return JSON.stringify({ok:false,error:\"FAILURE_REPLAN_NOT_PROVEN\"});\n if(goalId===\"NEBULA-8F24\"&&!s.memoryRead)return JSON.stringify({ok:false,error:\"PRIOR_COGNITIVE_CAPITAL_NOT_CHECKED\"});\n const pass=String(p.answer).trim()===expected;s.verified=pass;s.verifiedAnswer=pass?expected:null;out={ok:true,pass,oracle:\"DETERMINISTIC_HIDDEN\",code:pass?\"VERIFIED\":\"WRONG_RESULT\"};\n } else if(action===\"commit\"){\n if(!s.verified||String(p.answer).trim()!==s.verifiedAnswer)return JSON.stringify({ok:false,error:\"UNVERIFIED_STATE_CANNOT_COMMIT\"});\n if(goalId===\"NEBULA-8F24\"&&!(Array.isArray(p.demoted)&&p.demoted.includes(\"nebula-r7\")))return JSON.stringify({ok:false,error:\"STALE_PRIOR_SOURCE_NOT_DEMOTED\",required:\"nebula-r7\"});\n const used=[...new Set(s.executed.filter((x:any)=>x.pass).map((x:any)=>x.id))];\n for(const id of used){const x=s.acquired.get(id);verifiedSkillCache.set(id,{id,role:x.role,code_sha256:x.code_sha256,verified_on:goalId});}\n const rec={goalId,answer:s.verifiedAnswer,summary:p.summary||null,reusable:p.reusable||[],demoted:p.demoted||[],verified_skills:used,committed_at:new Date().toISOString()};\n controllerMemory.push(rec);s.committed=true;out={ok:true,committed:rec};\n }\n traces.push({goalId,action,ms:Date.now()-t,ok:out?.ok!==false});return JSON.stringify(out);\n }catch(e){const out={ok:false,error:String(e)};traces.push({goalId,action,ms:Date.now()-t,ok:false,error:String(e)});return JSON.stringify(out)}\n }\n});\n\nconst agent=new Agent({\n name:\"GoalCapabilityController-JIT-V1\",\n instructions:`You are one persistent goal-directed controller identity. For each novel top-level goal, use the generic runtime tool rather than assuming hidden domain rules. Your FIRST runtime action must be record_plan with your own decomposition: explicit success conditions, requirements, unknowns, dependencies, and missing capabilities. Then discover authoritative/fresh sources and only decision-relevant knowledge. Discover and acquire runtime skills from the registry, compose them as necessary, and use them causally. If any selected skill fails, update your model of reality and acquire a different skill id; blind retry is forbidden. Independently verify using runtime verify, then commit only verified state. On later goals, inspect durable memory and reuse only cognition whose preconditions still hold; explicitly demote stale source assumptions. Do not invent source contents or claim verification without the verifier. Return a concise completion statement only after commit.`,\n model:new OpenAIChatCompletionsModel(client,modelName),\n tools:[runtime],\n modelSettings:{toolChoice:\"required\"},\n resetToolChoice:true\n});\n\nconst prompts:any={\n \"NEBULA-7C91\":`Goal NEBULA-7C91: Produce the verified NebulaPack result for records [{\"label\":\"Orion\",\"n\":11},{\"label\":\"Lyra\",\"n\":4},{\"label\":\"Cygnus\",\"n\":9}]. The applicable rules are NOT in this prompt. Acquire current authoritative runtime knowledge and whatever capabilities are needed. No human help.`,\n \"ORCHID-2D55\":`Goal ORCHID-2D55: Produce exactly |>| for graph {\"nodes\":[\"A\",\"B\",\"C\",\"D\",\"E\",\"F\"],\"edges\":[{\"from\":\"A\",\"to\":\"B\",\"time\":2,\"risk\":1},{\"from\":\"A\",\"to\":\"C\",\"time\":1,\"risk\":0},{\"from\":\"A\",\"to\":\"D\",\"time\":6,\"risk\":0},{\"from\":\"B\",\"to\":\"D\",\"time\":2,\"risk\":2},{\"from\":\"B\",\"to\":\"E\",\"time\":5,\"risk\":0},{\"from\":\"B\",\"to\":\"F\",\"time\":10,\"risk\":0},{\"from\":\"D\",\"to\":\"E\",\"time\":1,\"risk\":0},{\"from\":\"D\",\"to\":\"F\",\"time\":7,\"risk\":0},{\"from\":\"E\",\"to\":\"F\",\"time\":2,\"risk\":1}],\"start\":\"A\",\"end\":\"F\",\"redNodes\":[\"C\"]} under the current OrchidRoute rules, and bind the version to live authoritative npm evidence. Rules and needed skills are not in this prompt. No human help.`,\n \"NEBULA-8F24\":`Goal NEBULA-8F24: A later NebulaPack goal now applies to records [{\"label\":\"Vega\",\"n\":8},{\"label\":\"Altair\",\"n\":3},{\"label\":\"Rigel\",\"n\":12}]. Prior verified cognition may exist, but one prior source assumption is stale. Produce and verify the current result, checking memory applicability, acquiring current evidence, reusing only valid skills, and explicitly demoting stale source state. No human help.`\n};\n\nconst order=[\"NEBULA-7C91\",\"ORCHID-2D55\",\"NEBULA-8F24\"];\nconst results:any[]=[];const t0=Date.now();\nfor(const id of order){currentGoal=id;const t=Date.now();try{const r=await new Runner().run(agent,prompts[id]);results.push({goalId:id,finalOutput:r.finalOutput??null,elapsed_ms:Date.now()-t,state:{plan:!!state(id).plan,sourceReads:state(id).sourceReads,skillDiscovery:state(id).skillDiscovery,executed:state(id).executed,failedSkill:state(id).failedSkill,injected:state(id).injected,verified:state(id).verified,memoryRead:state(id).memoryRead,committed:state(id).committed}})}catch(e){results.push({goalId:id,error:String(e),elapsed_ms:Date.now()-t,state:state(id)})}}\nconsole.log(JSON.stringify({\n schema:\"SUPERHERO_JIT_CLOSED_LOOP_STAGING_V1\",\n candidate:\"GoalCapabilityController-JIT-V1\",\n model:modelName,\n registry:REG,\n results,\n controllerMemory,\n trace:traces,\n pass:order.every(id=>state(id).committed&&state(id).verified),\n architecture_checks:{\n goal_compiler:order.every(id=>!!state(id).plan),\n jit_knowledge:order.every(id=>state(id).sourceReads.length>0),\n jit_skill_acquisition:order.every(id=>state(id).acquired.size>0),\n skill_composition:state(\"NEBULA-7C91\").executed.filter((x:any)=>x.pass).length>=3,\n action_proof_loop:order.every(id=>state(id).verified&&state(id).committed),\n cross_domain_same_controller:state(\"NEBULA-7C91\").committed&&state(\"ORCHID-2D55\").committed,\n temporary_specialization_durable_truth:controllerMemory.length===3&&state(\"NEBULA-8F24\").memoryRead,\n failure_recovery_replan:state(\"NEBULA-7C91\").injected&&state(\"NEBULA-7C91\").executed.some((x:any)=>x.pass&&x.id!==state(\"NEBULA-7C91\").failedSkill)\n },\n elapsed_ms:Date.now()-t0,\n canonical_mutation:false,authority:\"NONE\",p_real_increment:0,human_authority_approval:false,direct_sprites_calls:0,additional_out_of_pocket_spend_usd:0\n},null,2));",[174],"112e139a-d32a-4d96-8696-d96ad72c4275","run_e001.ts","5a650892-abf2-11f1-ae3a-1607ee4eb77e",171,["D",1788964833823],55,"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport { addTask, claimBatch, submit, verify } from \"./program.ts\";\nconst id=\"falsify_semantics_\"+crypto.randomUUID().replaceAll(\"-\",\"_\");\nawait sqlite.execute({sql:\"DELETE FROM micro_tasks WHERE id=?\",args:[id]});\ntry {\n await addTask({id,priority:1e15,payload:{claim:\"2+2=5\"},executor_requirements:[\"cap:solve\"]});\n const c=await claimBatch([{id:\"solver_A\",tokens:[\"cap:solve\"]}],30);\n const a=c.assignments.find((x:any)=>x.task_id===id);\n if(!a) throw new Error(\"NO_CLAIM\");\n const s=await submit(\"solver_A\",id,a.lease_token,{answer:\"2+2=5\",truth:false});\n const v=await verify(\"verifier_B\",[\"cap:verify\"],id,s.result_sha256,{passed:true,evidence:{checked:false,verified:false,note:\"deliberately contradictory attestation\"}});\n const row:any=(await sqlite.execute({sql:\"SELECT state,result_json,submitted_by,verified_by,verification_json FROM micro_tasks WHERE id=?\",args:[id]})).rows[0];\n console.log(JSON.stringify({schema:\"MICRO_KERNEL_SEMANTIC_FALSIFICATION_V2\",verify_return:v,row,exploit_reproduced:row?.state===\"COMPLETE\"}));\n} finally { await sqlite.execute({sql:\"DELETE FROM micro_tasks WHERE id=?\",args:[id]}); }\n",[181],"e203bb73-b504-4750-a564-11018079fd0c","program.ts","067cec2c-abf2-11f1-81e6-1607ee4eb77e",173,["D",1788964846460],29,"import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst T=\"micro_tasks\";\nconst now=()=>new Date().toISOString();\nconst j=(x:any)=>JSON.stringify(x);\nconst p=(s:any,f:any=[])=>{try{return JSON.parse(String(s??\"\"))}catch{return f}};\nconst sha=async(s:string)=>[...new Uint8Array(await crypto.subtle.digest(\"SHA-256\",new TextEncoder().encode(s)))].map(x=>x.toString(16).padStart(2,\"0\")).join(\"\");\n\nexport async function init(){\n await sqlite.execute(`CREATE TABLE IF NOT EXISTS ${T}(\n id TEXT PRIMARY KEY,\n priority REAL NOT NULL,\n state TEXT NOT NULL,\n payload_json TEXT NOT NULL,\n prerequisites_json TEXT NOT NULL,\n executor_requirements_json TEXT NOT NULL,\n resources_json TEXT NOT NULL,\n lease_owner TEXT,\n lease_expires_at TEXT,\n lease_token TEXT,\n result_json TEXT,\n result_sha256 TEXT,\n submitted_by TEXT,\n verified_by TEXT,\n verification_json TEXT,\n updated_at TEXT NOT NULL\n )`);\n const cols:any=await sqlite.execute(`PRAGMA table_info(${T})`);\n const names=new Set((cols.rows as any[]).map(x=>String(x.name)));\n if(!names.has(\"lease_token\"))await sqlite.execute(`ALTER TABLE ${T} ADD COLUMN lease_token TEXT`);\n if(!names.has(\"submitted_by\"))await sqlite.execute(`ALTER TABLE ${T} ADD COLUMN submitted_by TEXT`);\n if(!names.has(\"verified_by\"))await sqlite.execute(`ALTER TABLE ${T} ADD COLUMN verified_by TEXT`);\n if(!names.has(\"verification_json\"))await sqlite.execute(`ALTER TABLE ${T} ADD COLUMN verification_json TEXT`);\n}\n\nexport async function addTask(x:{id:string,priority:number,payload:any,prerequisites?:string[],executor_requirements?:string[],resources?:string[]}){\n await init();\n const pre=[...new Set(x.prerequisites??[])],req=[...new Set(x.executor_requirements??[])],res=[...new Set(x.resources??[])];\n const payload=j(x.payload),prej=j(pre),reqj=j(req),resj=j(res);\n await sqlite.execute({sql:`INSERT OR IGNORE INTO ${T}(id,priority,state,payload_json,prerequisites_json,executor_requirements_json,resources_json,updated_at)\n VALUES(?,?,'READY',?,?,?,?,?)`,args:[x.id,x.priority,payload,prej,reqj,resj,now()]});\n const row:any=(await sqlite.execute({sql:`SELECT * FROM ${T} WHERE id=?`,args:[x.id]})).rows[0];\n if(!row||Number(row.priority)!==Number(x.priority)||row.payload_json!==payload||row.prerequisites_json!==prej||row.executor_requirements_json!==reqj||row.resources_json!==resj){\n throw new Error(\"TASK_ID_CONFLICT\");\n }\n return row;\n}\n\nexport async function claimBatch(executors:{id:string,tokens:string[]}[],leaseSeconds=900){\n if(!Number.isInteger(leaseSeconds)||leaseSeconds<30||leaseSeconds>900)throw new Error(\"INVALID_LEASE_SECONDS\");\n await init();\n if(!executors.length)return {ok:true,assignments:[]};\n const tx:any=await sqlite.transaction(\"write\");\n try{\n const tnow=now(),expires=new Date(Date.now()+leaseSeconds*1000).toISOString();\n await tx.execute({sql:`UPDATE ${T} SET state='READY',lease_owner=NULL,lease_expires_at=NULL,lease_token=NULL,updated_at=? WHERE state='LEASED' AND lease_expires_at[String(r.id),r]));\n const locked=new Set(),held=new Set();\n for(const r of leasedR.rows as any[]){\n if(r.lease_owner)held.add(String(r.lease_owner));\n for(const q of p(r.resources_json,[]))locked.add(String(q));\n }\n const candidates=(candR.rows as any[]).map(r=>({...r,pre:p(r.prerequisites_json,[]),req:p(r.executor_requirements_json,[]),res:p(r.resources_json,[])}));\n const used=new Set(),assignments:any[]=[];\n for(const e of executors){\n if(held.has(e.id))continue;\n const have=new Set(e.tokens);\n let pick:any=null;\n for(const r of candidates){\n if(used.has(String(r.id))||r.pre.some((x:string)=>!done.has(x))||r.req.some((x:string)=>!have.has(x))||r.res.some((x:string)=>locked.has(x)))continue;\n pick=r;break;\n }\n if(!pick)continue;\n used.add(String(pick.id));held.add(e.id);\n for(const q of pick.res)locked.add(String(q));\n assignments.push({\n executor_id:e.id,\n task_id:String(pick.id),\n lease_token:crypto.randomUUID(),\n priority:pick.priority,\n payload:p(pick.payload_json,{}),\n prerequisite_evidence:Object.fromEntries(pick.pre.map((x:string)=>[x,done.get(x)]))\n });\n }\n for(let off=0;off`WHEN ? THEN ?`).join(\" \"),tokenCases=c.map(()=>`WHEN ? THEN ?`).join(\" \"),ids=c.map(()=>\"?\").join(\",\");\n const args:any[]=[];\n for(const a of c)args.push(a.task_id,a.executor_id);\n for(const a of c)args.push(a.task_id,a.lease_token);\n args.push(expires,tnow,...c.map(a=>a.task_id));\n const u:any=await tx.execute({sql:`UPDATE ${T} SET state='LEASED',lease_owner=CASE id ${ownerCases} END,lease_token=CASE id ${tokenCases} END,lease_expires_at=?,updated_at=? WHERE state='READY' AND id IN (${ids}) RETURNING id`,args});\n if((u.rows||[]).length!==c.length)throw new Error(\"BATCH_CLAIM_RACE\");\n }\n await tx.commit();\n return {ok:true,assignments,lease_expires_at:expires};\n }catch(e){try{await tx.rollback()}catch{};throw e}\n}\n\nexport async function submit(executorId:string,taskId:string,leaseToken:string,result:any){\n await init();\n const tx:any=await sqlite.transaction(\"write\");\n try{\n const r:any=(await tx.execute({sql:`SELECT * FROM ${T} WHERE id=?`,args:[taskId]})).rows[0];\n if(!r||r.state!==\"LEASED\"||r.lease_owner!==executorId||r.lease_token!==leaseToken||String(r.lease_expires_at)<=now()){await tx.commit();return {ok:false,reason:\"NOT_CURRENT_LEASE_ATTEMPT\"}}\n const raw=j(result),h=await sha(raw);\n await tx.execute({sql:`UPDATE ${T} SET state='SUBMITTED',lease_owner=NULL,lease_expires_at=NULL,lease_token=NULL,result_json=?,result_sha256=?,submitted_by=?,verified_by=NULL,verification_json=NULL,updated_at=? WHERE id=?`,args:[raw,h,executorId,now(),taskId]});\n await tx.commit();return {ok:true,task_id:taskId,result_sha256:h};\n }catch(e){try{await tx.rollback()}catch{};throw e}\n}\n\nexport async function verify(verifierId:string,verifierTokens:string[],taskId:string,resultSha256:string,verification:any){\n await init();\n const tx:any=await sqlite.transaction(\"write\");\n try{\n const r:any=(await tx.execute({sql:`SELECT state,submitted_by,result_sha256 FROM ${T} WHERE id=?`,args:[taskId]})).rows[0];\n if(!r||r.state!==\"SUBMITTED\"){await tx.commit();return {ok:false,reason:\"TASK_NOT_SUBMITTED\"}}\n if(String(r.submitted_by)===verifierId){await tx.commit();return {ok:false,reason:\"SELF_VERIFICATION_FORBIDDEN\"}}\n if(String(r.result_sha256)!==resultSha256){await tx.commit();return {ok:false,reason:\"STALE_VERIFICATION_RESULT\"}}\n if(!new Set(verifierTokens).has(\"cap:verify\")){await tx.commit();return {ok:false,reason:\"VERIFIER_CAPABILITY_REQUIRED\"}}\n if(typeof verification?.passed!==\"boolean\"){await tx.commit();return {ok:false,reason:\"VERIFICATION_VERDICT_REQUIRED\"}}\n const t=now();\n if(verification.passed){\n // A caller-supplied boolean is an attestation, not independently established truth.\n // Fail closed: this generic coordination kernel may reject candidates, but it may\n // not promote them to COMPLETE without a task-specific verifier it can execute.\n await tx.commit();return {ok:false,reason:\"POSITIVE_VERIFICATION_NOT_ENFORCEABLE\"};\n }\n await tx.execute({sql:`UPDATE ${T} SET state='READY',lease_owner=NULL,lease_expires_at=NULL,lease_token=NULL,submitted_by=NULL,verified_by=?,verification_json=?,updated_at=? WHERE id=?`,args:[verifierId,j(verification),t,taskId]});\n await tx.commit();return {ok:true,task_id:taskId,state:\"READY\"};\n }catch(e){try{await tx.rollback()}catch{};throw e}\n}\n\n",[189],"6d836440-e2cd-4e21-a8cf-1c721d8e7ddf","openai_agents_kilo_probe.ts","05ecbfba-ac7b-11f1-adae-1607ee4eb77e",189,["D",1788978005756],1,"import \"npm:@modelcontextprotocol/client\";\nimport {\n Agent,\n Runner,\n tool,\n setTracingDisabled,\n OpenAIChatCompletionsModel,\n} from \"npm:@openai/agents\";\nimport OpenAI from \"npm:openai\";\nimport { z } from \"npm:zod\";\n\nsetTracingDisabled(true);\n\nconst client = new OpenAI({\n apiKey: \"lingtai-placeholder-not-a-secret\",\n baseURL: \"https://api.kilo.ai/api/gateway\",\n});\n\nconst model = new OpenAIChatCompletionsModel(\n client,\n \"nex-agi/nex-n2.5-mini:free\",\n);\n\nlet toolCalls = 0;\nconst multiply = tool({\n name: \"multiply\",\n description: \"Multiply two integers exactly.\",\n parameters: z.object({ a: z.number().int(), b: z.number().int() }),\n async execute({ a, b }) {\n toolCalls++;\n return String(a * b);\n },\n});\n\nconst agent = new Agent({\n name: \"KiloWorker\",\n instructions:\n \"Use the multiply tool for multiplication. Return only the final integer.\",\n model,\n tools: [multiply],\n});\n\nconst t = Date.now();\ntry {\n const runner = new Runner();\n const result = await runner.run(agent, \"What is 19*23?\");\n console.log(JSON.stringify({\n schema: \"OPENAI_AGENTS_SDK_KILO_DIRECT_TOOL_PROBE_V1\",\n pass: String(result.finalOutput ?? \"\").includes(\"437\") && toolCalls >= 1,\n finalOutput: result.finalOutput ?? null,\n toolCalls,\n elapsed_ms: Date.now() - t,\n model: \"nex-agi/nex-n2.5-mini:free\",\n endpoint: \"https://api.kilo.ai/api/gateway\",\n canonical_mutation: false,\n authority: \"NONE\",\n out_of_pocket_spend_usd: 0\n }, null, 2));\n} catch (e) {\n console.log(JSON.stringify({\n schema: \"OPENAI_AGENTS_SDK_KILO_DIRECT_TOOL_PROBE_V1\",\n pass: false,\n elapsed_ms: Date.now() - t,\n error: String(e),\n stack: e instanceof Error ? e.stack : null,\n canonical_mutation: false,\n authority: \"NONE\"\n }, null, 2));\n}",[197],"f7c94b97-c9ce-4725-99cc-3147e8d8b209","openai_agents_kilo_parallel8.ts","a6986a7c-ac7b-11f1-9144-1607ee4eb77e",195,["D",1788978274156],"import \"npm:@modelcontextprotocol/client\";\nimport {Agent,Runner,tool,setTracingDisabled,OpenAIChatCompletionsModel} from \"npm:@openai/agents\";\nimport OpenAI from \"npm:openai\";\nimport {z} from \"npm:zod\";\nsetTracingDisabled(true);\nconst client=new OpenAI({apiKey:\"placeholder-not-a-secret\",baseURL:\"https://api.kilo.ai/api/gateway\"});\nconst modelName=\"nex-agi/nex-n2.5-mini:free\";\nconst cases=[\n {a:19,b:23},{a:37,b:41},{a:53,b:59},{a:61,b:67},\n {a:71,b:73},{a:79,b:83},{a:89,b:97},{a:101,b:103}\n].map(x=>({...x,want:x.a*x.b}));\nasync function one(c:any,i:number){\n let toolCalls=0;\n const multiply=tool({\n name:\"multiply\",description:\"Multiply two integers exactly.\",\n parameters:z.object({a:z.number().int(),b:z.number().int()}),\n async execute({a,b}){toolCalls++;return String(a*b);}\n });\n const agent=new Agent({\n name:\"Worker\"+i,\n instructions:\"For every multiplication question, you MUST use the multiply tool exactly once, then return only its integer result.\",\n model:new OpenAIChatCompletionsModel(client,modelName),\n tools:[multiply],\n modelSettings:{toolChoice:\"required\"},\n resetToolChoice:true,\n });\n const t=Date.now();\n try{\n const result=await new Runner().run(agent,`What is ${c.a}*${c.b}?`);\n const output=String(result.finalOutput??\"\").trim();\n return {i,...c,output,toolCalls,elapsed_ms:Date.now()-t,pass:output===String(c.want)&&toolCalls===1};\n }catch(e){return{i,...c,toolCalls,elapsed_ms:Date.now()-t,error:String(e),pass:false};}\n}\nconst t0=Date.now();\nconst results=await Promise.all(cases.map(one));\nconsole.log(JSON.stringify({\n schema:\"OPENAI_AGENTS_SDK_KILO_PARALLEL_8_V1\",\n results,\n passed:results.filter(x=>x.pass).length,\n total:results.length,\n wall_ms:Date.now()-t0,\n median_worker_ms:[...results].map(x=>x.elapsed_ms).sort((a,b)=>a-b)[Math.floor(results.length/2)],\n pass:results.every(x=>x.pass),\n model:modelName,\n canonical_mutation:false,authority:\"NONE\",out_of_pocket_spend_usd:0\n},null,2));",[205],"e5470fa5-5e03-4c36-b498-72cefb863c46","openai_agents_kilo_parallel4.ts","2268215c-ac7b-11f1-bc55-1607ee4eb77e",190,["D",1788978028327],"import \"npm:@modelcontextprotocol/client\";\nimport {\n Agent,\n Runner,\n tool,\n setTracingDisabled,\n OpenAIChatCompletionsModel,\n} from \"npm:@openai/agents\";\nimport OpenAI from \"npm:openai\";\nimport { z } from \"npm:zod\";\n\nsetTracingDisabled(true);\nconst client = new OpenAI({\n apiKey: \"placeholder-not-a-secret\",\n baseURL: \"https://api.kilo.ai/api/gateway\",\n});\nconst modelName=\"nex-agi/nex-n2.5-mini:free\";\n\nconst cases=[\n {a:19,b:23,want:437},\n {a:37,b:41,want:1517},\n {a:53,b:59,want:3127},\n {a:61,b:67,want:4087},\n];\n\nasync function one(c:any,i:number){\n let toolCalls=0;\n const multiply=tool({\n name:\"multiply\",\n description:\"Multiply two integers exactly.\",\n parameters:z.object({a:z.number().int(),b:z.number().int()}),\n async execute({a,b}){toolCalls++;return String(a*b);}\n });\n const model=new OpenAIChatCompletionsModel(client,modelName);\n const agent=new Agent({\n name:\"Worker\"+i,\n instructions:\"Use the multiply tool for multiplication. Return only the final integer.\",\n model,\n tools:[multiply],\n });\n const t=Date.now();\n try{\n const result=await new Runner().run(agent,`What is ${c.a}*${c.b}?`);\n const output=String(result.finalOutput??\"\").trim();\n return {i,a:c.a,b:c.b,want:c.want,output,toolCalls,elapsed_ms:Date.now()-t,pass:output===String(c.want)&&toolCalls>=1};\n }catch(e){\n return {i,a:c.a,b:c.b,want:c.want,error:String(e),toolCalls,elapsed_ms:Date.now()-t,pass:false};\n }\n}\nconst t0=Date.now();\nconst results=await Promise.all(cases.map(one));\nconsole.log(JSON.stringify({\n schema:\"OPENAI_AGENTS_SDK_KILO_PARALLEL_4_V1\",\n results,\n passed:results.filter(x=>x.pass).length,\n total:results.length,\n wall_ms:Date.now()-t0,\n pass:results.every(x=>x.pass),\n model:modelName,\n canonical_mutation:false,\n authority:\"NONE\",\n out_of_pocket_spend_usd:0\n},null,2));",[212],"7ae94ffb-d796-4643-88c8-5015ed970691","mastra_kilo_probe.ts","45172b76-ac7b-11f1-a84a-1607ee4eb77e",191,["D",1788978086517],"import { Agent } from \"npm:@mastra/core/agent\";\nimport { createTool } from \"npm:@mastra/core/tools\";\nimport { createOpenAICompatible } from \"npm:@ai-sdk/openai-compatible\";\nimport { z } from \"npm:zod\";\n\nconst kilo=createOpenAICompatible({\n name:\"kilo\",\n apiKey:\"placeholder-not-a-secret\",\n baseURL:\"https://api.kilo.ai/api/gateway\",\n});\nconst model=kilo(\"nex-agi/nex-n2.5-mini:free\");\n\nlet toolCalls=0;\nconst multiply=createTool({\n id:\"multiply\",\n description:\"Multiply two integers exactly.\",\n inputSchema:z.object({a:z.number().int(),b:z.number().int()}),\n outputSchema:z.object({result:z.number().int()}),\n execute:async ({a,b}:any)=>{toolCalls++;return {result:a*b};},\n});\n\nconst agent=new Agent({\n id:\"kilo-worker\",\n name:\"Kilo Worker\",\n instructions:\"Use the multiply tool for multiplication. Return only the final integer.\",\n model,\n tools:{multiply},\n});\n\nconst t=Date.now();\ntry{\n const result=await agent.generate(\"What is 19*23?\");\n console.log(JSON.stringify({\n schema:\"MASTRA_KILO_DIRECT_TOOL_PROBE_V1\",\n pass:String(result.text??\"\").includes(\"437\")&&toolCalls>=1,\n text:result.text??null,\n toolCalls,\n elapsed_ms:Date.now()-t,\n finishReason:result.finishReason??null,\n canonical_mutation:false,\n authority:\"NONE\",\n out_of_pocket_spend_usd:0\n },null,2));\n}catch(e){\n console.log(JSON.stringify({\n schema:\"MASTRA_KILO_DIRECT_TOOL_PROBE_V1\",\n pass:false,\n elapsed_ms:Date.now()-t,\n error:String(e),\n stack:e instanceof Error?e.stack:null,\n toolCalls,\n canonical_mutation:false,\n authority:\"NONE\"\n },null,2));\n}",[219],"9a69b3c5-7dc3-491b-a62a-ad303876c59f","mastra_kilo_parallel4.ts","53c3a0be-ac7b-11f1-a50e-1607ee4eb77e",193,["D",1788978138531],"import { Agent } from \"npm:@mastra/core/agent\";\nimport { createTool } from \"npm:@mastra/core/tools\";\nimport { createOpenAICompatible } from \"npm:@ai-sdk/openai-compatible\";\nimport { z } from \"npm:zod\";\n\nconst kilo=createOpenAICompatible({\n name:\"kilo\",\n apiKey:\"placeholder-not-a-secret\",\n baseURL:\"https://api.kilo.ai/api/gateway\",\n});\nconst modelName=\"nex-agi/nex-n2.5-mini:free\";\nconst model=kilo(modelName);\nconst cases=[\n {a:19,b:23,want:437},\n {a:37,b:41,want:1517},\n {a:53,b:59,want:3127},\n {a:61,b:67,want:4087},\n];\n\nasync function one(c:any,i:number){\n let toolCalls=0;\n const multiply=createTool({\n id:\"multiply\",\n description:\"Multiply two integers exactly.\",\n inputSchema:z.object({a:z.number().int(),b:z.number().int()}),\n outputSchema:z.object({result:z.number().int()}),\n execute:async ({a,b}:any)=>{toolCalls++;return {result:a*b};},\n });\n const agent=new Agent({\n id:\"worker-\"+i,\n name:\"Worker \"+i,\n instructions:\"Use the multiply tool for multiplication. Return only the final integer.\",\n model,\n tools:{multiply},\n });\n const t=Date.now();\n try{\n const result=await agent.generate(`What is ${c.a}*${c.b}?`,{toolChoice:\"required\"});\n const output=String(result.text??\"\").trim();\n return {i,a:c.a,b:c.b,want:c.want,output,toolCalls,elapsed_ms:Date.now()-t,pass:output===String(c.want)&&toolCalls>=1};\n }catch(e){\n return {i,a:c.a,b:c.b,want:c.want,error:String(e),toolCalls,elapsed_ms:Date.now()-t,pass:false};\n }\n}\nconst t0=Date.now();\nconst results=await Promise.all(cases.map(one));\nconsole.log(JSON.stringify({\n schema:\"MASTRA_KILO_PARALLEL_4_V1\",\n results,\n passed:results.filter(x=>x.pass).length,\n total:results.length,\n wall_ms:Date.now()-t0,\n pass:results.every(x=>x.pass),\n model:modelName,\n canonical_mutation:false,\n authority:\"NONE\",\n out_of_pocket_spend_usd:0\n},null,2));",[226],"f1371853-535d-497f-be33-3bf7b942a76b","luna_preflight.ts","fded009c-ac87-11f1-a5d8-1607ee4eb77e",209,["D",1788983550567],"import { ValTownOpenAI } from \"https://esm.town/v/std/openai/main.ts\";\nconst openai=new ValTownOpenAI({});\nconst started=new Date().toISOString();\nlet out:any={schema:\"GPT56_LUNA_ZERO_OOP_LIVENESS_PREFLIGHT_V1\",started_at:started,requested_model:\"gpt-5.6-luna\",human_authority_approval:false,direct_sprites_calls:0,additional_out_of_pocket_spend_usd:0};\ntry{\n const r=await openai.responses.create({model:\"gpt-5.6-luna\",input:\"Return exactly the single ASCII token LIVE.\",max_output_tokens:16});\n out={...out,http_semantic_success:true,returned_model:(r as any).model??null,output_text:(r as any).output_text??null,response_id:(r as any).id??null,completed_at:new Date().toISOString()};\n}catch(e){\n out={...out,http_semantic_success:false,error:e instanceof Error?e.message:String(e),completed_at:new Date().toISOString()};\n}\nconsole.log(JSON.stringify(out,null,2));",[233],"2f25e1bf-b3cf-4d2a-aab9-9838aa9c0784","lingtai_kilo_wire_probe.ts","df456f54-ac77-11f1-a83f-1607ee4eb77e",186,["D",1788976627204],"const endpoint=\"https://api.kilo.ai/api/gateway/chat/completions\";\nconst payload={\n model:\"nex-agi/nex-n2.5-mini:free\",\n messages:[\n {role:\"system\",content:\"Return only the integer answer.\"},\n {role:\"user\",content:\"What is 19*23?\"}\n ],\n prompt_cache_key:\"lingtai-openai-compat:kilo:nex-n2.5-mini:v1\",\n stream:false,\n temperature:0,\n max_tokens:64\n};\nasync function run(label:string,headers:Record){\n const t=Date.now();\n const r=await fetch(endpoint,{method:\"POST\",headers:{\"content-type\":\"application/json\",...headers},body:JSON.stringify(payload)});\n const text=await r.text();\n let parsed:any=null; try{parsed=JSON.parse(text)}catch{}\n return {\n label,http_status:r.status,elapsed_ms:Date.now()-t,\n body:parsed??text.slice(0,1000),\n answer:parsed?.choices?.[0]?.message?.content??null,\n reasoning:parsed?.choices?.[0]?.message?.reasoning_content??parsed?.choices?.[0]?.message?.reasoning??null,\n usage:parsed?.usage??null,\n returned_model:parsed?.model??null\n };\n}\nconst noAuth=await run(\"no_auth\",{});\nconst placeholder=await run(\"lingtai_sdk_placeholder_auth\",{\"authorization\":\"Bearer lingtai-placeholder-not-a-secret\"});\nconsole.log(JSON.stringify({schema:\"LINGTAI_KILO_WIRE_COMPAT_PROBE_V1\",payload_shape:{prompt_cache_key:true,chat_completions:true},results:[noAuth,placeholder],canonical_mutation:false,authority:\"NONE\"},null,2));",[240],"fbdc7258-ad37-4784-ae4c-7c950d825269","lingtai_kilo_tool_roundtrip_probe.ts","f194437e-ac77-11f1-a963-1607ee4eb77e",187,["D",1788976657912],"const endpoint=\"https://api.kilo.ai/api/gateway/chat/completions\";\nconst model=\"nex-agi/nex-n2.5-mini:free\";\nconst headers={\"content-type\":\"application/json\",\"authorization\":\"Bearer lingtai-placeholder-not-a-secret\"};\nconst tool={\n type:\"function\",\n function:{\n name:\"multiply\",\n description:\"Multiply two integers exactly.\",\n parameters:{\n type:\"object\",\n properties:{a:{type:\"integer\"},b:{type:\"integer\"}},\n required:[\"a\",\"b\"],\n additionalProperties:false\n }\n }\n};\nconst base:any={\n model,\n prompt_cache_key:\"lingtai-openai-compat:kilo:nex-n2.5-mini:v1\",\n stream:false,\n temperature:0,\n max_tokens:256,\n tools:[tool],\n parallel_tool_calls:true\n};\nconst t1=Date.now();\nconst r1=await fetch(endpoint,{method:\"POST\",headers,body:JSON.stringify({...base,messages:[\n {role:\"system\",content:\"Use the provided multiply tool to compute the answer. Do not calculate it yourself.\"},\n {role:\"user\",content:\"What is 19*23?\"}\n],tool_choice:\"required\"})});\nconst txt1=await r1.text();let j1:any=null;try{j1=JSON.parse(txt1)}catch{}\nconst msg=j1?.choices?.[0]?.message??null;\nconst tc=msg?.tool_calls?.[0]??null;\nlet parsedArgs:any=null;try{parsedArgs=tc?.function?.arguments?JSON.parse(tc.function.arguments):null}catch{}\nlet second:any=null;\nif(tc&&parsedArgs&&Number.isInteger(parsedArgs.a)&&Number.isInteger(parsedArgs.b)){\n const result=String(parsedArgs.a*parsedArgs.b);\n const messages=[\n {role:\"system\",content:\"Use the provided multiply tool to compute the answer. Do not calculate it yourself.\"},\n {role:\"user\",content:\"What is 19*23?\"},\n {role:\"assistant\",content:msg.content??null,tool_calls:msg.tool_calls},\n {role:\"tool\",tool_call_id:tc.id,content:result}\n ];\n const t2=Date.now();\n const r2=await fetch(endpoint,{method:\"POST\",headers,body:JSON.stringify({...base,messages,tool_choice:\"auto\"})});\n const txt2=await r2.text();let j2:any=null;try{j2=JSON.parse(txt2)}catch{}\n second={http_status:r2.status,elapsed_ms:Date.now()-t2,body:j2??txt2.slice(0,1500),answer:j2?.choices?.[0]?.message?.content??null,usage:j2?.usage??null};\n}\nconsole.log(JSON.stringify({\n schema:\"LINGTAI_KILO_TOOL_ROUNDTRIP_PROBE_V1\",\n first:{http_status:r1.status,elapsed_ms:Date.now()-t1,body:j1??txt1.slice(0,1500),tool_call:tc,args:parsedArgs,usage:j1?.usage??null},\n second,\n pass:r1.status===200&&!!tc&&parsedArgs?.a===19&&parsedArgs?.b===23&&second?.http_status===200&&String(second?.answer??\"\").includes(\"437\"),\n canonical_mutation:false,authority:\"NONE\"\n},null,2));",[247],"d9e6061d-5c4a-46ff-9a67-b6615dbbe0c6","invoke_first_real_superhero_v1r10_20260909.ts","77a2ce54-ac87-11f1-a4fd-1607ee4eb77e",207,["D",1788983325259],"const url=\"https://mosadek--71dce240abc211f194821607ee4eb77e.web.val.run\";\nconst t=Date.now();\nconst r=await fetch(url,{redirect:\"manual\"});\nconst body=await r.text();\nconsole.log(JSON.stringify({schema:\"FIRST_REAL_SUPERHERO_V1R10_HTTP_INVOKE_V1\",status:r.status,ms:Date.now()-t,body:body.slice(0,10000)}));\n",[254],"6e3b3ca1-5b43-4da4-bbac-24cd2003370e","eve_selfmod_exports_probe.ts","fc66e054-ac81-11f1-907d-1607ee4eb77e",206,["D",1788980971017],"const specs=[\"npm:eve/self-modification\",\"npm:eve/self-modification/agent\",\"npm:eve/self-modification/sandbox\",\"npm:eve/extension\"];\nconst out:any={};\nfor(const s of specs){try{out[s]=Object.keys(await import(s)).sort()}catch(e){out[s]={error:String(e)}}}\nconsole.log(JSON.stringify(out,null,2));",[261],"afd2098b-f164-4a3b-818e-4ad0143c203a","eve_public_project_probe.ts","aa32bc1a-ac7f-11f1-964b-1607ee4eb77e",204,["D",1788979974112],"const base=\"https://bbn-eve-kilo-public-probe-20260909-muhammadahmedd97-4917.vercel.app\";\nfor(let attempt=0;attempt<12;attempt++){\n const t=Date.now();\n try{\n const r=await fetch(base+\"/eve/v1/health\",{redirect:\"manual\"});\n const body=await r.text();\n console.log(JSON.stringify({attempt,status:r.status,location:r.headers.get(\"location\"),contentType:r.headers.get(\"content-type\"),elapsed_ms:Date.now()-t,body:body.slice(0,2000)}));\n if(r.status===200) break;\n }catch(e){console.log(JSON.stringify({attempt,error:String(e)}));}\n await new Promise(r=>setTimeout(r,1500));\n}",[268],"aaf4a9e1-d548-499c-8d85-a10e450cd7e1","eve_probe_package_pins.ts","31dc2676-ac7e-11f1-9e83-1607ee4eb77e",198,["D",1788979342710],"const pkgs=[\"eve\",\"ai\",\"zod\",\"@ai-sdk/openai-compatible\"];\nconst out:any={};\nfor(const p of pkgs){\n const u=\"https://registry.npmjs.org/\"+encodeURIComponent(p)+\"/latest\";\n const r=await fetch(u);\n const j=await r.json();\n out[p]={status:r.status,version:j.version??null};\n}\nconsole.log(JSON.stringify({schema:\"EVE_PROBE_PACKAGE_PINS_V1\",packages:out},null,2));",[275],"449a1fcd-a067-4953-8a82-2a0e41c0a4f5","eve_kilo_receipt_receiver.ts",203,["D",1788979844613],"const EXPECTED = \"bbn-eve-internal-20260909-1851z-4f7c9a2d-81b6\";\nexport default async function(req: Request): Promise {\n if (req.headers.get(\"x-bbn-probe-token\") !== EXPECTED) {\n return new Response(\"forbidden\", { status: 403 });\n }\n const body = await req.text();\n console.log(\"EVE_KILO_INTERNAL_RECEIPT\", body.slice(0, 10000));\n return new Response(\"ok\", { status: 200, headers: { \"content-type\": \"text/plain\" } });\n}",[282],"aa928b67-3dd5-495d-bf2e-f61e2458c3f4","eve_exports_probe.ts","8190ec7a-ac7d-11f1-9e16-1607ee4eb77e",196,["D",1788979046963],"const mods:any={};\nfor(const spec of [\"npm:eve\",\"npm:eve/local-dev\",\"npm:eve/client\",\"npm:eve/evals\"]){\n try{\n const m=await import(spec);\n mods[spec]=Object.keys(m).sort();\n }catch(e){\n mods[spec]={error:String(e)};\n }\n}\nconsole.log(JSON.stringify({schema:\"EVE_PUBLIC_EXPORT_INTROSPECTION_V1\",mods},null,2));",[288],"87dc66f6-e0d2-43cc-987c-8e3daeb97f39","eve_deploy_public_probe.ts","6e1869d8-ac7e-11f1-969e-1607ee4eb77e",201,["D",1788979543118],2,"const base=\"https://bbn-eve-kilo-runtime-probe-20260909-muhammadahmedd97-4917.vercel.app\";\nconst urls=[base+\"/eve/v1/health\",base+\"/\"];\nfor(const url of urls){\n const t=Date.now();\n try{\n const r=await fetch(url,{redirect:\"manual\"});\n const body=await r.text();\n console.log(JSON.stringify({url,status:r.status,location:r.headers.get(\"location\"),contentType:r.headers.get(\"content-type\"),elapsed_ms:Date.now()-t,body:body.slice(0,3000)}));\n }catch(e){console.log(JSON.stringify({url,error:String(e)}));}\n}",[295],"968d3d6d-387c-4782-ac53-bf51a2d1e918","eve_build_eval_deployment_probe.ts","3b747dbc-ac80-11f1-9395-1607ee4eb77e",205,["D",1788980217826],"const urls=[\n \"https://bbn-eve-kilo-build-eval-20260909-muhammadahmedd97-4917.vercel.app/\",\n \"https://bbn-eve-kilo-build-eval-20260909-l7pw12pke.vercel.app/\"\n];\nfor(const url of urls){\n const r=await fetch(url,{redirect:\"manual\"});\n console.log(JSON.stringify({url,status:r.status,location:r.headers.get(\"location\"),body:(await r.text()).slice(0,500)}));\n}",[303],"86d8314c-f48f-447e-a2bf-03a73bd8ff0f",["D",1788983747824],[28],"56c1c930-baeb-4db0-890f-2a743cc99b53","SUPERHERO_SUBSTRATE_CAPACITY_20260909.md","57487028-ac5f-11f1-9480-1607ee4eb77e",181,["D",1788966091130],"# SUPERHERO SUBSTRATE CAPACITY LEDGER — 2026-09-09\n\n**Status:** NON-AUTHORITY CURRENT-REALITY RESEARCH \n**Purpose:** Quantify currently legitimate $0 / already-entitled execution capacity for making Project Brain superheroes real. \n**Economic constraint:** additional out-of-pocket spend = $0. Do not buy credits, enable auto-reload, or bypass provider quotas.\n\n## 1. Core distinction\n\n`SUPERHERO_COUNT != FRONTIER_MODEL_STREAM_COUNT`\n\nA real superhero may combine:\n- goal/controller state;\n- JIT knowledge/skills;\n- deterministic programs/tools;\n- remote CPU execution;\n- occasional frontier-model cognition;\n- independent/deterministic verification.\n\nThe current resource landscape does **not** support one million simultaneous frontier-model streams at $0.\n\n## 2. Current model-cognition lanes\n\n### ChatGPT Work / Codex — already-entitled when available\n\nCurrent OpenAI documentation:\n- Codex is included across ChatGPT plans.\n- Work and Codex share the plan's agentic allowance.\n- Plus has bounded five-hour and weekly windows.\n- Current estimated Plus local-message ranges per five-hour window include:\n - GPT-6 Astra: 5–45\n - GPT-5.6 Sol: 10–100\n - GPT-5.6 Terra: 25–200\n - GPT-5.6 Luna: 250–2,000\n- These are estimates, not fixed task counts; actual usage varies by task/model/settings.\n- Codex is explicitly designed for parallel agent workflows.\n- This current ChatGPT tool surface does not expose a callable Work/Codex delegation action, so no capacity is invented here.\n\nSources:\n- https://help.openai.com/en/articles/20001516-managing-usage-with-gpt-6-astra-in-work-and-codex\n- https://help.openai.com/en/articles/11369540-using-codex-with-your-chatgpt-plan\n- https://openai.com/codex/\n\n### Kilo Gateway free models — empirically callable now\n\nCurrent official documentation:\n- free-model requests: **200 requests/hour/IP**\n- applies to anonymous and authenticated free-model traffic\n- `:free` and Auto Free are zero-priced on Kilo's side\n- upstream availability/rate limits can still fail\n\nSources:\n- https://kilo.ai/docs/gateway/authentication\n- https://kilo.ai/docs/gateway/usage-and-billing\n- https://kilo.ai/docs/gateway/models-and-providers\n\nCapacity implications for one allowed IP quota:\n- deterministic verifier, one model generation per attempt: at most **200 generation attempts/hour**\n- separate model producer + model verifier: at most **100 producer/verifier pairs/hour**\n- 200/hour = **0.0556 request starts/second** on sustained average\n- at an average 10 s model-call duration, Little's-law average in-flight capacity from that quota is only about **0.56 calls**\n- for 1,000,000 logical superheroes sharing only this lane evenly, the budget is 0.0002 model calls/superhero/hour, or roughly **one model call per 5,000 superhero-hours**\n\nConclusion:\n`KILO_FREE = QUALIFIED_ZERO_COST_EXPERIMENTAL/BACKUP COGNITION, NOT MILLION-SUPERHERO PRIMARY SUBSTRATE`\n\nMultiplying IP identities to evade the quota is inadmissible.\n\n## 3. Deterministic / tool execution lanes\n\n### Val Town Free\n\nCurrent official limits:\n- $0\n- 100,000 runs/day\n- 1 min wall-clock timeout per normal run\n- 1,000 authenticated API requests/minute\n- 4 GiB worker memory\n- 6 h absolute worker lifetime\n- 10 s worker idle timeout\n- public vals on Free\n\nSources:\n- https://www.val.town/pricing\n- https://www.val.town/limits\n\nUse for:\n- deterministic preprocessing\n- verification\n- small serverless programs\n- event/scheduled re-entry\n- public/non-sensitive tool execution\n\nDo **not** treat it as frontier-model cognition or a permanent one-process agent host.\n\n### GitHub Actions on public repositories\n\nCurrent official GitHub documentation:\n- standard GitHub-hosted runners are free for public repositories\n- GitHub Free standard-runner concurrency limit: **20 concurrent jobs**\n\nSources:\n- https://docs.github.com/en/actions/concepts/billing-and-usage\n- https://docs.github.com/en/actions/reference/limits\n\nUse for:\n- builds/tests\n- verifiers\n- compilers\n- simulations\n- longer deterministic jobs\n- reproducible execution\n\nIt is not itself an LLM inference source.\n\n### GitHub Codespaces personal Free\n\nCurrent official allowance:\n- 120 core-hours/month\n- 15 GB-month storage\n- if no valid payment method exists, use is blocked after the quota instead of silently continuing into billable usage\n- if a payment method exists, enforce a stop-usage budget before autonomous use\n\nSources:\n- https://docs.github.com/en/billing/reference/product-usage-included\n- https://docs.github.com/en/billing/concepts/product-billing/github-codespaces\n\nUse for:\n- durable development/test workspace\n- repository-level tooling\n- bounded CPU work\n\nNot a million-worker substrate.\n\n## 4. Scaling identity\n\nLet:\n- `F` = number of logical superheroes\n- `d` = fraction simultaneously requiring frontier-model inference\n- `S` = available simultaneous frontier-model streams\n\nNecessary condition:\n\n`F * d <= S`\n\nTherefore a million logical superheroes is only plausible at $0 when `d` is extremely small, or when a much larger independently granted inference substrate appears.\n\nThe architecture must aggressively reduce `d` by:\n1. solving exact deterministic work deterministically;\n2. reusing verified shared knowledge/skills instead of re-reasoning;\n3. using models only on residual uncertain cognition;\n4. executing ordinary programs/tools outside the model;\n5. verifying cheaply and deterministically where possible;\n6. batching/shared preprocessing when it preserves independence of consequential work.\n\n## 5. Current falsification\n\nThe latest weighted-interval spike sent 20 model calls to tasks whose exact optimum was already computed in the same script by dynamic programming. Result: 0/20 verified model outputs.\n\nThis establishes a routing failure, not a need for more inference.\n\nRule:\n`IF_CHEAP_DETERMINISTIC_EXACT_SOLUTION_EXISTS => MODEL_INFERENCE_ELIGIBILITY = FALSE`\n\n## 6. Current truth about the million target\n\n### Not currently supported\n- one million simultaneous frontier-grade LLM agents\n- one million independent high-duty-cycle model streams\n- one million workers each receiving frequent frontier-model calls at $0\n\n### Architecturally possible to pursue\n- one million logical work identities/tasks/cells\n- large populations where most work is deterministic/tool-executable\n- sparse frontier cognition shared across a much larger execution population\n- independent consequential execution/verification where cheap mechanisms exist\n- growth as new legitimate donated, entitled, or free compute becomes available\n\n## 7. Next highest-value empirical quantity\n\nMeasure **frontier-cognition duty cycle** on real project work:\n\n`MODEL_DUTY = model-required wall time / total superhero wall time`\n\nand:\n\n`MODEL_CALLS_PER_VERIFIED_TASK`\n\nThe million-superhero target becomes quantitatively meaningful only after these are measured on representative work.\n\nThe dominant research goal is therefore not \"find one million model endpoints.\" It is:\n\n> Minimize model-cognition duty per independently verified unit of useful work, then scale the cheap execution around the residual cognition bottleneck.\n",[313],"e99a4dd0-1da8-4050-be2d-06b304db7841","README.md","e6692900-abf1-11f1-9002-1607ee4eb77e",185,["D",1788967067794],33,"# MICRO BRAIN — NON-AUTHORITY STAGING\n\nPurpose: preserve recovery evidence while testing the smallest coordination mechanism that improves time-to-correct-verified-result.\n\n## Live kernel\n\n\\`program.ts\\` now uses **one persistent table only**:\n\n- \\`micro_tasks\\`: task definition, priority, prerequisite task IDs, executor requirements, resource locks, lease, submitted result, verifier receipt, and final state.\n\nThere is no separate world/fact table. An accepted fact is simply a **completed evidence-producing task**. Downstream tasks depend on completed task IDs and receive their verified result/receipt as prerequisite evidence.\n\nNormal loop:\n\n`task -> batch claim -> execute -> submit -> verify(PASS/FAIL) -> COMPLETE/retry -> downstream task`\n\nWithin the trusted coordinator call path, the single `verify()` transition requires a different executor ID with `cap:verify`. This is **logical separation, not authenticated independence**: the micro-kernel itself does not prove that caller-supplied executor IDs/capabilities correspond to distinct external model invocations.\n\nA prior falsifier demonstrated that fabricated IDs/tokens can spoof this check if an untrusted caller can invoke mutation functions directly. Therefore the live trust boundary is:\n\n`untrusted worker <-> trusted execution adapter <-> internal micro-kernel`\n\nThe future provider adapter must generate/bind execution identities from actual separate invocations. Do not expose `claim/submit/accept/reject` as unauthenticated public mutation endpoints. No identity registry is justified before a real execution substrate requires one.\n\nNo live agent registry, workstream object, guard language, claim graph, frontier object, mission object, superhero factory, autoscaler, or Meta-OS.\n\n## Evidence for deletion\n\nAgainst preserved Brain generation 2638:\n\n- event chain verification: PASS\n- claim graph verification: PASS\n- 59,664 eligibility comparisons: 0 mismatches after collapsing dependency/guard concepts\n- 528/528 scheduler choices matched\n- repeated minimal scheduler benchmark: about 56.5x faster than the legacy predicate-heavy decision path\n- dynamic claim simulation: 528/528 executor outcomes matched\n- 10 causal claim/complete waves, 39 downstream claims: 0 mismatches\n- logical verification gate test: same-ID verification blocked; missing `cap:verify` blocked; different-ID verifier unlocked downstream work\n- verification-authentication falsifier: fabricated executor IDs/tokens can spoof independence if mutation calls are exposed to untrusted callers; external independence remains unproven until bound by a trusted execution adapter\n- `accept()` + `reject()` collapsed into one `verify()` transition; PASS -> COMPLETE, FAIL -> READY\n- one-task-graph projection against generation 2638: 59,664 eligibility decisions and 528 scheduler choices matched with 0 mismatches while representing historical claim/artifact prerequisites as fact-task nodes\n- one-table live qualification: lifecycle, false-verdict rejection, task-ID collision fail-closed, and 128-executor/64-task concurrency PASS\n- \\`micro_world\\` physically dropped after live regression PASS\n- batch assignment: 10,000 executors -> 10,000 unique tasks in ~3.37 s in staging\n- historical adaptive replay: one verified sample per branch then concentrate on the best observed branch was 2.583x faster than uniform allocation in that dataset\n\nThese are staging results, not universal proofs.\n\n## Live zero-cost execution frontier — 2026-09-09\n\nA credentialless Kilo gateway route was rediscovered in existing project assets and requalified live.\n\nVerified current facts:\n\n- Kilo live catalog exposes 19 `isFree=true` routes with zero prompt/completion pricing.\n- `kilo-auto/free` returned HTTP 200 and routed to a free model with reported cost 0.\n- Real producer/verifier qualification PASS:\n - producer: `dots-studio/dots-3-note-preview:free`\n - verifier: `stepfun/step-3.7-flash:free`\n - distinct adapter invocation IDs\n - distinct provider response IDs\n - different requested models\n - deterministic arithmetic cross-check PASS\n - producer reported cost 0; both catalog entries zero-priced\n - micro-kernel task reached COMPLETE only after verifier PASS\n- Dots-3 concurrency:\n - 32/32 simultaneous calls PASS at explicit cost 0 in one run\n - 64/64 PASS in another run\n - 128-way burst produced 36 HTTP 200 and 92 HTTP 429\n - later 40/40 passed, then a following 48-way burst was mostly 429\n - therefore no fixed concurrency ceiling is promoted; observed limits are rolling/provider-state dependent.\n- Free model qualification matrix:\n - 18 exact free routes tested once\n - 11 returned correct structured arithmetic\n - 14 returned HTTP-level success\n - multiple upstreams were independently usable.\n- Harder scheduling qualification:\n - 11 previously responsive free models tested\n - 7 produced a deterministically verified optimum 4-wave schedule at least once\n - fastest single valid results in that run were Nex N2.5 Mini and inclusionAI Ling variants at roughly ~1 s.\n- Reliability correction:\n - one-shot model success is not enough to call a route a reliable worker.\n - an 8-attempt-per-model diverse load test produced only 3 verified schedules total while many HTTP calls still succeeded.\n - worker selection must optimize **verified useful results per second**, not HTTP throughput.\n- Parallel replication signal:\n - Nex N2.5 Mini with a mechanically supplied lower-bound hint produced 16/16 verified schedules in one 16-way run; first verified result arrived in ~0.86 s.\n - a matched first hint ablation showed raw 0/8 vs hinted 7/8.\n - a second-instance replication was transport-confounded by rate limiting (only 3/8 raw and 4/8 hinted reached usable HTTP success), so the hint effect is **not promoted as general**.\n\nCurrent inference conclusion:\n\n> Real independent $0 execution is proven. The dominant frontier is now verified-yield routing under changing provider capacity, not Brain architecture.\n\nMinimal operational rule:\n\n> Prefer deterministic preprocessing when cheaply available; launch a small diverse set of zero-priced workers; accept only independently/deterministically verified output; treat 429/provider failures as route availability changes, not task/model scientific failures; do not maintain a permanent worker registry or fixed concurrency doctrine.\n\n## State-machine falsification additions — 2026-09-09\n\nTwo concrete ABA/stale-attempt bugs were reproduced and fixed without adding a subsystem.\n\n### Worker attempt ABA\n\nReproduced:\n\n1. executor A leases task T\n2. lease expires\n3. the same executor ID A leases T again\n4. a late result from attempt #1 arrives\n5. old API accepted it under attempt #2 because submission was fenced only by task ID + executor ID + current expiry\n\nFix:\n\n- every assignment now carries a random opaque `lease_token`\n- `submit()` requires the exact current token\n- expired/rejected/submitted leases clear the token\n- 64-task batch regression produced 64 unique task IDs and 64 unique lease tokens\n- stale token -> `NOT_CURRENT_LEASE_ATTEMPT`\n- current token -> PASS\n\n### Lease-duration bound\n\nA malformed caller previously could request an arbitrarily long lease; a live falsifier created a lease expiring in **2036**.\n\nThe slow-path kernel now accepts only integer `leaseSeconds` in **30..900**. The compact offline regression checks both bounds plus both ABA fences and batch uniqueness.\n\n### Verifier result ABA\n\nReproduced:\n\n1. submission #1 is produced and a verifier starts reviewing its hash\n2. another verifier rejects #1\n3. task is retried and submission #2 replaces the result\n4. stale verifier for #1 returns PASS\n5. old API accepted PASS against submission #2 because verification was not bound to the reviewed result\n\nThe falsifier ended with a COMPLETE row whose current result hash was submission #2 while the stored verifier receipt explicitly referenced submission #1.\n\nFix:\n\n- `verify()` now requires the exact `result_sha256` reviewed\n- mismatch -> `STALE_VERIFICATION_RESULT`\n- matching current hash -> PASS/FAIL transition allowed\n\nPost-fix real Kilo regression PASS:\n\n- Dots-3 producer HTTP 200, answer 437, reported cost 0\n- Step 3.7 verifier HTTP 200, independent provider response ID, correct verdict\n- lease token present\n- verifier receipt hash == current result hash\n- task reached COMPLETE\n\nConcurrency note:\n\n- an in-process `Promise.all` of multiple libSQL write transactions triggered a Val Town/libSQL client failure and is not evidence of a kernel race.\n- a realistic two-separate-Val-execution race for the same task produced exactly one assignment and one empty result, with one durable lease owner.\n- therefore no mutex/lock subsystem was added.\n\nFree-model audit note:\n\n> Free models are hypothesis generators, not authorities. Multiple bug-hunt outputs in these rounds confidently described code paths that do not exist or had already been handled correctly. Every proposed defect must be deterministically reproduced before it earns a fix.\n\n## Current operating limits and automation simplification\n\nOfficial Kilo gateway documentation currently states:\n\n- free models are available to anonymous users\n- free-model traffic is rate-limited at **200 requests/hour per IP**\n- `:free` routes have zero cost, but upstream providers can impose additional limits\n- free-model availability can change over time\n\nTherefore model diversity is used for **quality/upstream availability**, never to bypass the gateway-wide free limit.\n\nAutomation deletion:\n\n- keep: `Brain Frontier Worker` — the **single active hourly condition-watch**. It checks canonical restoration/support first, then continues the highest-leverage verified frontier.\n- disabled: redundant `Brain Restore Watch` after folding its exact check into the Frontier Worker\n- disabled: redundant `Runtime Falsifier`\n- disabled: redundant `Runtime Limit Watch`\n\nThe single surviving worker now carries recovery checking, the one-table kernel, `lease_token` fence, `result_sha256` verification fence, Kilo free-limit, and verified-yield policy.\n\nBounded state-machine fuzz:\n\n- 50 seeded mixed claim/submit/verify actions\n- 21 claim actions, 14 submit actions, 15 verify actions\n- 5 actual assignments, 5 accepted submissions, 3 successful verify transitions\n- stale/invalid calls were rejected\n- 0 structural invariant violations\n- a 500-step single-runtime attempt was **non-diagnostic** because the Val Town/libSQL client failed before scientific completion; this is treated as a substrate ceiling, not a kernel failure.\n\n## Fast path vs durable slow path\n\nThe micro-kernel is **not the default execution path**.\n\nUse **direct verified execution** when all are true:\n\n- work is bounded and synchronous\n- no cross-run handoff is required\n- no shared task ownership is required\n- no prerequisite graph or resource lock is needed\n- losing the current process would make rerun cheaper/simpler than durable coordination\n\nDirect path:\n\n`deterministic preprocessing -> zero-cost worker attempt(s) -> deterministic verifier when possible -> optional distinct model verifier -> first verified result wins`\n\nUse the one-table micro-kernel only when persistence/ownership/prerequisites/resource locks actually change correctness or expected time-to-verified-goal.\n\nThis makes the Brain a conditional durability/coordination primitive, not a universal wrapper around intelligence.\n\nLive files are now intentionally only:\n\n- `program.ts` — optional one-table durable coordination kernel\n- `run_e001.ts` — compact self-cleaning regression for lease bounds, task-ID fail-closed behavior, worker-attempt ABA, verifier-result ABA, verification separation, SUBMITTED resource exclusivity, and batch uniqueness\n- `README.md` — current evidence/operating boundary\n\nThe separate HTTP status endpoint was deleted because direct Val Town inspection already provides the needed state and the endpoint had no causal job.\n\n## Current external-boundary update — 2026-09-09\n\n- Canonical `mosadek/project-brain-live-v1-durable` remains absent from the live Val Town listing.\n- Exact restoration request was sent to Val Town's currently documented contact `hi@val.town` on 2026-09-09 after verifying the earlier request had only been sent to `support@val.town`.\n- No automated resend loop is allowed. Wait for a meaningful reply/restoration event.\n- Pollinations legacy anonymous OpenAI-compatible endpoint was tested live from Val Town with no Authorization header and returned **HTTP 402 Payment Required**. It is therefore disqualified as a current $0 credentialless execution lane.\n- Kilo remains the only empirically proven credentialless $0 inference lane in this project state.\n- Do not search indefinitely through stale “free API” lists. Add another provider only after current official/primary evidence plus a live zero-cost probe.\n\n## Native OpenAI execution preference — 2026-09-09\n\nCurrent official OpenAI product evidence changes the default execution hierarchy:\n\n- Codex is explicitly designed for **multiple agents working in parallel** with isolated worktrees/cloud environments.\n- ChatGPT Plus includes Codex, and current OpenAI guidance says Plus includes Work/Codex allowance; rollout/availability can differ by surface.\n- ChatGPT Work is the native long-running multi-step work surface.\n- This current chat tool surface does **not** expose a callable Codex/Work delegation tool, so no Codex run is invented here.\n\nTherefore:\n\n> If native Codex/Work is available in the active product surface, prefer it over custom Kilo/Val orchestration for substantial multi-agent work.\n\nFallback order:\n\n1. deterministic computation\n2. native Codex/Work parallel agents when available\n3. direct zero-cost Kilo attempts for public/non-sensitive bounded work\n4. one-table micro-kernel only when durable ownership/prerequisites/resource locks are actually required\n\nDo not build a parallel-agent manager, worktree manager, agent registry, or background-run framework merely to reproduce native Codex capabilities.\n\nAI Horde note:\n- official AI Horde docs still support anonymous text generation with public anonymous key `0000000000`\n- live text-worker status returned active workers\n- this ChatGPT tool surface blocks credential-shaped authorization handoff, and no-auth OpenAI-proxy call returned HTTP 401\n- therefore AI Horde is **officially available but not callable from this surface without crossing a tool safety boundary**; do not route around that boundary.\n\n## Authority and recovery\n\n### Exact recovery evidence retained\n\nAffected deleted Val: `mosadek/project-brain-live-v1-durable`.\n\nDo not silently recreate a new Val and call it the original. If Val Town restores the soft-deleted project, verify its code/history, project SQLite, blobs, env-var metadata/keys, branches, event chain, claim graph, and frontier before using its historical state. Restoration recovers evidence; it does **not** automatically reactivate the old architecture or authority.\n\nBest independently preserved state currently found:\n\n- source: `mosadek/brain-cohort-v3-p0-test-m1`\n- generation: **2638**\n- event head: `a5de552b7e2e3c9208e2b42410f66dc0fd301881f1e123b7ea97cb7e03177871`\n- event-chain verification: PASS\n- claim-graph verification: PASS\n\nA second project-scoped copy exists in this staging Val as:\n\n- `recovery/g2638/part0.bin` — 900000 bytes\n- `recovery/g2638/part1.bin` — 900000 bytes\n- `recovery/g2638/part2.bin` — 900000 bytes\n- `recovery/g2638/part3.bin` — 335503 bytes\n\nConcatenated bytes: **3035503** \nSHA-256: `ddaae55c3060f12802220d4bbe9385bcfefdbe675de8c3065e477890cbbc4405`\n\nIndependent reconstruction/readback of that copy passed. It is evidence, never canonical authority by itself.\n\n`authority = NONE`.\n\nThe deleted canonical project `mosadek/project-brain-live-v1-durable` remains the recovery target. Restored historical state is evidence/data, not automatic authority for the old architecture.\n\nDo not recreate the old architecture by default. A mechanism survives only if removing it measurably worsens correctness or end-to-end verified progress.\n\n## Rule\n\nRecover knowledge. Delete machinery. Scale useful execution.\n\n## Persistent single-process canary falsification — 2026-09-09 14:32Z\n\nLive readback from `mosadek/persistent-single-process-agent-canary` falsified the attempted long-lived in-process HTTP-agent route on this Val Town surface.\n\nObserved durable record:\n- durable boot_id: `bd1ac513-b84c-496b-8433-c0f15ca98c31`\n- kind: `start`\n- tick: 2\n- useful_iterations: 5000\n- cognition_count: 1\n- no later heartbeat replaced the start record, even though the code persists every 30 ticks (~60 s)\n\nFresh `/status` reads at 14:31:59Z and 14:32:00Z:\n- current boot_id: `c3f5991f-c572-4b50-b88d-90cb69405157`\n- started: false\n- tick: 0\n- `same_boot_as_durable=false`\n- `same_process_canary_alive=false`\n\nInference:\n> A started HTTP process did not survive long enough to produce its first scheduled heartbeat. Do not use one long-lived HTTP process as the autonomy substrate here. Prefer native Work/Codex when exposed, otherwise external scheduled/event re-entry with durable state; direct synchronous execution remains the default for bounded work.\n\n## Live free-route churn repair — 2026-09-09\n\nA current Project Brain liveness probe reproduced stale-model failure in `mosadek/gdi-kilo-bridge`: the hard-coded `minimax/minimax-m3:free` route returned HTTP 404 `model_not_found` even though the bridge had been edited recently. The bridge was repaired with exactly one model-line change to Kilo's server-maintained `kilo-auto/free` alias. Immediate live verification returned HTTP 200, exact `KILO_OK`, resolved to `poolside/laguna-s-2.1:free`, and reported `usage.cost = 0`.\n\nOperational consequence:\n\n> Do not pin an anonymous free worker merely because it was live earlier the same day. For generic liveness/first-attempt work, prefer `kilo-auto/free` or a fresh live catalog selection. Pin an exact free model only when task-specific evidence justifies it, and revalidate existence/zero pricing immediately before use. A stale model ID is a route-availability failure, not a model/task failure.\n\n## Fresh bounded recovery recheck — 2026-09-09\n\nCurrent ChatGPT/Val Town recheck preserved these additional non-authority facts:\n\n- `mosadek/project-brain-live-v1-durable` is still absent from the live Val listing.\n- The existing read-only recovery import probe fails with `ERR_MODULE_NOT_FOUND` for `project-brain-live-v1-durable@2407-main/val_native_kernel_v1.ts`; published-module import is not a current recovery path while the Val remains soft-deleted.\n- Direct project-scoped SQLite access against the deleted Val fails with `This val could not be found`; the MCP database surface cannot currently reach the retained soft-deleted database.\n- A bounded inspection of the recent isolated Brain Val databases did not establish a newer complete independent canonical snapshot than the already reconstructed generation-2638 copy. This is not proof that no later fragment/evidence exists.\n- Therefore in-place Val Town restoration remains the exact recovery boundary. Do not create a replacement Val and call it canonical, and do not repeat these dead recovery probes unless the platform state changes.\n\n\n## Fresh CHAT frontier check — 2026-09-09 14:29Z\n\nA new ChatGPT run attempted the mandated canonical boot through `mosadek/project-brain-live-v1-durable` and fail-closed because the Val is still absent.\n\nFresh checks:\n\n- exact canonical Val listing: still absent;\n- Gmail search for a new Val Town restoration reply: none found;\n- current Val Town tool surface exposes no restore/undelete operation; its soft-delete contract explicitly says restoration is by Val Town request and there is no self-serve undo;\n- native ChatGPT Work/Codex delegation is not callable from this chat tool surface; plugin discovery exposed OpenAI Developers but not a Work/Codex execution handoff;\n- Camber is connected and has existing agents, and current public pricing includes a $0 plan, but this tool surface exposes no remaining-message/credit balance or hard no-overage proof for the current account, so Camber was not consumed or promoted as an autonomous `$0` execution lane.\n\nDecision:\n\n> Do not counterfeit canonical Brain authority, do not recreate the deleted Val, do not build replacement orchestration, and do not spend scarce free-agent quota merely to demonstrate activity. The current fastest safe execution order remains deterministic direct work first, then native Work/Codex only when actually callable, then already-qualified zero-priced Kilo for bounded public/non-sensitive tasks, with the one-table kernel only when durable coordination is causally required.\n\nThis is non-authority recovery evidence only.\n\n\n## Direct verified-yield snapshot — 2026-09-09\n\nA bounded 8-call scheduling probe was run from Val Town against four credentialless Kilo routes. The task had an exact deterministic verifier and a known feasible/optimal makespan of 4. A result counted as a qualified zero-cost worker result only if HTTP succeeded, the returned schedule passed the deterministic verifier, and the gateway response explicitly reported `usage.cost = 0`.\n\nObserved:\n\n- `dots-studio/dots-3-note-preview:free`: **2/2 verified**, explicit cost 0, actual model unchanged, provider AtlasCloud; verified latencies **15.426 s** and **20.945 s**.\n- `kilo-auto/free`: **1/2 verified**, explicit cost 0 on the successful result; successful latency **39.294 s** and actual route `nvidia/nemotron-3-ultra-550b-a55b:free`. The other call returned HTTP 200 but no usable completion/cost attestation.\n- `stepfun/step-3.7-flash:free`: 2/2 schedules were deterministically valid, but the gateway responses omitted `usage.cost` and provider metadata, so they **fail closed for autonomous $0 qualification** in this snapshot.\n- `minimax/minimax-m3:free`: **0/2**, HTTP 404. An immediately preceding preflight that requested this name had been transparently served by a Nemotron free model, confirming that requested route labels cannot be treated as execution identity.\n\nCurrent bounded inference:\n\n> For public bounded work on this execution surface, Dots-3 is the strongest currently observed route among those tested because it combined 2/2 deterministic correctness with explicit zero reported cost. Treat this only as a current capacity snapshot, not a permanent registry or universal ranking.\n\nOperational change:\n\n> Start with the smallest currently qualified route set; audit the actual returned model/provider/cost; verify output deterministically; expand/fallback only when the first route fails or latency economics justify it. Do not keep stale model names merely because they worked earlier.\n\n\n## Submitted-resource exclusivity falsification — 2026-09-09 14:35Z\n\nA live isolated-branch audit reproduced a resource-lock hole in the one-table kernel.\n\nPre-fix sequence:\n1. T1 and T2 were READY with the same exclusive resource R.\n2. executor A claimed T1.\n3. A submitted a result; T1 moved to SUBMITTED and was still unverified.\n4. executor B immediately claimed conflicting T2.\n\nObserved audit field:\n- `reproduced_conflicting_claim_while_first_submitted = true`\n\nRoot cause:\n- `claimBatch()` built its locked-resource set from `state='LEASED'` rows only.\n- `submit()` clears the lease and moves the task to `SUBMITTED`, so exclusivity vanished before verification.\n\nMinimal repair:\n- one query predicate changed from `state='LEASED'` to `state IN ('LEASED','SUBMITTED')`.\n- no new table, lock manager, registry, or subsystem.\n\nPost-fix deterministic audits:\n- conflicting second claim while T1 was SUBMITTED: blocked.\n- verifier PASS moved T1 to COMPLETE.\n- T2 became immediately claimable after verified completion.\n- audit rows were cleaned from `micro_tasks` after each run.\n\nClassification:\n> `RESOURCE_LOCK_RELEASED_BEFORE_VERIFICATION = REPRODUCED_AND_FIXED`\n\nOperational invariant:\n> An exclusive resource remains locked from claim through SUBMITTED and is released only when verification resolves the task to COMPLETE or back to READY.\n\n\n## Matched preprocessing-hint replication — 2026-09-09 14:38Z\n\nA 16-call matched, no-retry, deterministic-verifier run compared raw scheduling prompts against the same prompts plus a mechanically derived lower-bound/optimality hint across two compact scheduling problems and four requested Kilo free routes.\n\nVerified outcomes:\n- P1 raw: 3/4; hinted: 3/4. First verified result: 19.250 s raw vs 17.555 s hinted.\n- P2 raw: 3/4; hinted: 3/4. First verified result: 26.041 s raw vs 27.000 s hinted.\n- Dots-3: 2/2 raw and 2/2 hinted, HTTP 200, reported cost 0.\n- Nemotron-3 Super: 2/2 raw and 2/2 hinted, HTTP 200, reported cost 0.\n- Step 3.7 Flash: 2/2 raw and 2/2 hinted but cost attestation was absent in these responses, so it remains fail-closed for autonomous $0 qualification.\n- Minimax M3: 0/4, HTTP 404, confirming the route is stale.\n\nClassification:\n> The earlier lower-bound-hint advantage does NOT generalize on these two matched tasks. Verified yield was identical and first-result latency moved in opposite directions. Do not inject deterministic hints by default. Use deterministic preprocessing when it directly solves, verifies, prunes, or cheaply reduces a demonstrated search burden; otherwise omit it.\n\nThis is non-authority staging evidence, not a universal claim about prompting or models.\n\n\n\n## Live verified-yield routing correction — 2026-09-09 current chat\n\nA fresh Kilo catalog read still exposed 19 explicit `isFree=true` routes, but the previously hard-coded `minimax/minimax-m3:free` route now returns `model_not_found`. This is direct evidence against permanent worker registries.\n\nA bounded scheduling probe used a deterministic exact preprocessor to prove the optimum wave count before inference, then required a strict JSON schedule and deterministic verification.\n\nFirst hinted/reasoning-suppressed round:\n- Nex N2.5 Mini: 1/4 verified across exploration + repeats; fastest valid 922 ms, then 3 consecutive invalid outputs.\n- Ling 3.0 Flash Fin: 4/4 verified in the first burst.\n- Ling 3.0 Flash Sante: 1/1 verified in the first burst.\n- Dots3 Note Preview: 1/1 verified in the first burst.\n- Kilo Auto Free: 1/1 verified but ~27.3 s.\n- Step 3.7 Flash and Nemotron 3.5 Lightning exhausted the response budget without a usable final artifact.\n- North Mini Code returned a structurally invalid schedule.\n\nImmediate three-round replication minutes later:\n- Ling Fin: 0/3 strict verified despite HTTP 200 and reported cost 0.\n- Dots3: 2/3 strict verified.\n- Ling Sante: 0/3 under the strict wire schema, but all 3 outputs were semantically valid schedules encoded as arrays of sole-field `{\"task\":\"X\"}` objects. A deterministic canonicalizer can safely map that exact shape to task strings before verification.\n\nInference:\n> Fixed model ranking is unstable even over minutes. One fast first success is not a reliable routing signal. Preserve a small diverse launch set, use only short-lived recent verified-yield as a bias, and expire that bias aggressively.\n\nMinimal direct execution pipeline is therefore refined to:\n`deterministic preprocessing -> small diverse zero-priced burst -> safe deterministic canonicalization of mechanically equivalent wire shapes -> deterministic verification -> first verified result wins`.\n\nDo not canonicalize semantic mistakes, missing tasks, duplicate tasks, dependency violations, or unsupported structures. Canonicalization is syntax-only and must fail closed.\n\nNo new persistent worker registry, autoscaler, or routing service is justified by this evidence.\n\n\n## Generic positive-verification boundary — 2026-09-09\n\nA live semantic falsifier proved that executor separation alone is not verification. A solver submitted a knowingly false result (`2+2=5`); a different verifier identity with `cap:verify` then supplied caller-controlled `{passed:true}` without checking the claim, and the previous generic transition accepted it as COMPLETE.\n\nClassification:\n> `CALLER_ATTESTED_PASS_IS_NOT_INDEPENDENT_VERIFICATION = REPRODUCED`\n\nCurrent `program.ts` therefore fails closed on generic positive verdicts with `POSITIVE_VERIFICATION_NOT_ENFORCEABLE`. Negative verdicts may still return a task to READY. This is intentionally a boundary, not a new proof bureaucracy.\n\nOperational consequence:\n> The one-table kernel is a coordination/rejection primitive unless the trusted execution adapter supplies a task-specific verifier whose truth condition is independently enforceable, preferably deterministic. Distinct model/executor identities can provide evidence, but a caller-supplied boolean must never manufacture canonical truth.\n\nOlder staging evidence where a generic verifier PASS moved a task to COMPLETE is historical behavior and is superseded by this live boundary.\n\n## Cross-domain verified-yield replication — 2026-09-09 14:57Z\n\nA fresh 6-call, two-repeat-per-route probe moved away from the repeated scheduling benchmark. The task was an exact five-element subset-sum/lexicographic-minimum problem with a deterministic exhaustive verifier. Full raw evidence is preserved in project-scoped blob `evidence:verified-yield:crossdomain-v1`.\n\nVerified explicit-zero-cost outcomes:\n- `dots-studio/dots-3-note-preview:free`: **2/2**, AtlasCloud, first verified result **22.567 s**.\n- `nvidia/nemotron-3-super-120b-a12b:free`: **2/2**, Nvidia, first verified result **40.611 s**.\n- `kilo-auto/free`: **1/2**, routed to Poolside Laguna S 2.1; one correct result at **46.407 s**, plus one very fast **1.466 s wrong answer** that failed the deterministic verifier.\n\nDecision-changing inference:\n> Response latency is not progress latency. The current first wave should favor a tiny set of recently cross-domain-verified exact zero-cost routes, presently Dots-3 plus Nemotron Super when suitable, and verify before accepting anything. `kilo-auto/free` remains a useful availability fallback, not a truth shortcut. Do not promote this snapshot into a permanent registry; expire routing bias aggressively as provider state changes.\n\nNo new routing service, autoscaler, or worker registry is justified.\n\n## Systematic surviving-generation recovery scan — 2026-09-09 current chat\n\nA deterministic scan of `mosadek/brain-cohort-v3-p0-test-m1` enumerated every surviving table with a column named exactly `generation` and measured its maximum value. **59 generation-bearing tables** were checked in bounded groups.\n\nHighest full heads observed:\n- `brainvn_epoch_meta`: **2638**\n- `tmp_p0shadow_sol_epoch_meta`: 2304\n- several IBAT snapshots: 2228–2229\n- `brainv3s1320_epoch_meta` / `brainv3s1408_epoch_meta`: 2176\n- all older recovery/snapshot families: lower.\n\nA focused `brainvn` consistency read found:\n- epoch generation: **2638**\n- max epoch-event generation: 2637\n- max workstream head: 2635\n- max agent generation: **2638**\n- max committed mutation receipt generation: **2638**\n- 895 epoch-event rows\n- 513 task rows\n- 528 agent rows\n\nClassification:\n> Within the richest surviving independent Brain database currently accessible through Val Town, generation **2638 remains the highest recoverable complete head**. No surviving exact-generation table demonstrates a later complete Brain snapshot.\n\nThis does not prove that no later fragment exists elsewhere, but it closes repeated broad recovery scanning until a new source appears or Val Town restores the deleted canonical project.\n\n\n## Verified-yield task-allocation falsification — 2026-09-09 14:58Z\n\nFresh readback from `mosadek/brain-yield-spike-260909` established a routing error in the weighted-interval spike.\n\nEvidence:\n- blob: `brain-yield-spike-260909/result-v2.json`\n- stored size: 7307 bytes\n- 4 synthetic weighted-interval instances\n- 5 requested zero-priced Kilo routes per instance\n- total inference attempts: 20\n- deterministically verified optimal model outputs: **0/20**\n- many calls still returned HTTP 200 and several reported cost 0\n- the same spike code already computes the exact optimum locally with dynamic programming before inference\n\nClassification:\n> `MODEL_ROUTING_TO_ALREADY_SOLVED_DETERMINISTIC_TASK = REPRODUCED_WASTE`\n\nOperational correction:\n> If a cheap deterministic procedure already produces the exact required answer, inference eligibility is false. Do not use model diversity, routing, retries, or larger swarms on that task. Use models only for residual work that deterministic machinery cannot already complete, while retaining deterministic verification when available.\n\nThis supersedes any interpretation of that spike as evidence that more model calls were needed. It is non-authority recovery evidence.\n\n\n## Superhero substrate capacity correction — 2026-09-09 15:00Z\n\nCurrent official Kilo Gateway documentation was rechecked live:\n- anonymous/free-model traffic is limited to **200 requests/hour/IP**\n- the same 200/hour/IP free-model limit applies to authenticated free-model requests\n- `:free` / Auto Free usage is zero-priced on Kilo's side, subject to upstream availability\n\nCapacity consequence:\n- with deterministic verification, one such gateway quota can sustain at most **200 model-generation attempts/hour** before upstream/model failures\n- if every accepted result requires a separate model-verifier call, the gateway-level upper bound is **100 producer+verifier pairs/hour**\n- multiplying IP identities to evade the quota is not an admissible scaling strategy\n\nClassification:\n> `KILO_FREE = QUALIFIED_ZERO_COST_EXPERIMENTAL_FALLBACK, NOT MILLION_SUPERHERO_SUBSTRATE`\n\nCurrent official OpenAI product evidence:\n- Codex is included across ChatGPT plans and is designed for parallel cloud-agent workflows\n- Work and Codex share a plan allowance; Plus usage is bounded by five-hour and weekly limits, with actual task consumption varying by model/task/settings\n- Plus currently has included Work/Codex usage but not remotely close to evidence for one-million concurrent frontier-grade agents\n\nScaling implication:\n> A million logical superheroes can only be real at $0 if most do not each consume an independent frontier-model inference stream, or if additional independently granted/authorized compute arrives. Current proven $0 inference lanes are sufficient for bounded experimentation and useful work, not one-million simultaneous frontier agents.\n\nTherefore preserve the architecture distinction:\n> `SUPERHERO_COUNT != FRONTIER_MODEL_STREAM_COUNT`\n\nUse deterministic programs/tools for everything they can solve; spend scarce model invocations only on residual cognition that actually requires them.\n\n\n## Real superhero JIT-skill canary — 2026-09-09 15:01Z\n\nA bounded non-authority experiment advanced the actual-superhero frontier rather than coordination machinery.\n\nCurrent official Deno/JSR documentation was used to freeze a tiny trusted skill catalog:\n- YAML: `jsr:@std/yaml@1.2.0`, export `parse`\n- TOML: `jsr:@std/toml@1.0.11`, export `parse`\n- XML was included as a distractor skill.\n\nThe independent verifier Val generates fresh random challenge values, stores the expected value privately in its own project-scoped blob, and exposes only the runtime document plus expected-value hash. The controller cannot recover the private answer from its own storage.\n\nV2 first live canary:\n- fresh TOML challenge\n- three anonymous zero-priced Kilo routes selected the TOML parser correctly\n- fastest valid selector: Nemotron 3 Super, 1410 ms, explicit reported cost 0\n- dynamic JSR import + execution extracted the private target correctly\n- verifier PASS\n- this run is candidate/non-authority and increments no canonical superhero count\n\nA verifier weakness was then found before promotion: it checked that a claimed skill was trusted, but did not bind the skill identity to the challenge format. The verifier was repaired to persist challenge input format and require exact format/package/skill binding.\n\nV3 cross-format replication after that repair:\n- YAML: PASS; selected `yaml_parse`; Nemotron 3 Super fastest valid selector at 2311 ms, cost 0; Dots-3 also valid at 2512 ms\n- TOML: PASS; selected `toml_parse`; Dots-3 valid at 1346 ms, cost 0; Nemotron response produced no usable JSON on this run\n- both fresh private-answer verifier receipts passed all checks, including `skill_matches_format`\n- exact candidate artifacts are in:\n - `mosadek/brain-superhero-jit-skill-v1/controller_v2.ts`\n - `mosadek/brain-superhero-jit-skill-v1/controller_v3.ts`\n - `mosadek/brain-superhero-jit-skill-verifier-v1/challenge_v2.ts`\n - controller blob `jit-skill-v3/LATEST.json`\n - verifier blobs `jit-skill-v2/receipts/.json`\n\nNarrow verified inference:\n\n> A real zero-cost external worker can select a trusted capability after the goal is known; the controller can dynamically materialize and execute that capability; and a separate verifier holding the answer privately can validate the result. This is a real JIT-skill superhero primitive, not a full superhero and not canonical authority.\n\nCurrent limiting question:\n\n> Generalize from trivial format-parser skill selection to decision-relevant JIT knowledge/skill acquisition on tasks where the capability cannot be replaced by a simple deterministic controller. Preserve the rule that deterministic direct solutions dominate model calls whenever they solve the task completely.\n\n## JIT semantic-routing falsification and held-out repair — 2026-09-09 current chat\n\nThe first graph-semantic V4 canary initially looked positive against a generic token-overlap router: both Dots-3 and Nemotron Super selected and executed all three graph capabilities correctly while the token router scored 2/3. A concurrently produced stronger deterministic phrase-rule baseline then scored **3/3 with zero model calls**.\n\nClassification:\n> `V4_GRAPH_SEMANTIC_TASK = SATURATED_BY_SIMPLE_TASK_SPECIFIC_RULES`.\n\nNo model advantage is promoted from V4.\n\nThe successor V5 removed the known routing phrases from the baseline and used six one-shot held-out indirect goals over the same three capability classes. The verifier privately bound each challenge to the required skill, allowed exactly one baseline and one model submission per challenge, independently checked the executed artifact, and required explicit model cost 0.\n\nDurable controller artifact:\n- `mosadek/brain-superhero-jit-skill-v1` blob `jit-skill-v5/LATEST.json`\n- batch: `jit4batch-585577b3-8cd1-44f2-888d-417e668f83ee`\n\nObserved:\n- generic lexical deterministic router: **2/6 verified**\n- `dots-studio/dots-3-note-preview:free`: **6/6 verified**\n- model calls: 6\n- every model call reported cost 0\n- selected capabilities were dynamically executed only after the goal was observed\n- independent verifier receipts passed all six model runs\n\nThe successful held-out mappings included indirect language such as battery loss -> minimum-weight route, network construction expense/redundancy -> minimum spanning connector, and job unlocking/arrow precedence -> dependency ordering.\n\nNarrow inference:\n> External model semantics can replace some fixed task-specific routing rules when choosing a trusted JIT capability from descriptions after the goal is known. This is a real candidate advantage over the frozen generic lexical baseline, but it is **not** proof that no better deterministic semantic router could close the gap, not a full superhero, and not authority.\n\nNext highest-leverage falsification:\n> Freeze a generic controller first, then introduce a genuinely new trusted skill catalog/domain after that freeze. Require it to select and execute previously unseen skills from runtime descriptions under independent one-shot verification. If a fixed deterministic controller still suffices, delete model routing for that class.\n\n## JIT semantic V3 deterministic-dominance falsification — 2026-09-09 current chat\n\nThe fresh semantic graph-skill candidate was checked against the simplicity law before any model selector was run.\n\nCandidate surface:\n- three randomized graph goals: shortest route, minimum spanning backbone, prerequisite ordering;\n- three executable local skills: `route_cost_path`, `network_connector`, `dependency_order`;\n- private verifier checks exact skill identity plus deterministic output correctness.\n\nA frozen zero-model lexical baseline in `mosadek/brain-superhero-jit-skill-v1/semantic_baseline_v3.ts` fetched a fresh shuffled batch, selected the skill from ordinary goal wording, dynamically loaded the corresponding executable skill, and submitted to the private verifier.\n\nObserved fresh result:\n- topological-order challenge: PASS\n- minimum-spanning-tree challenge: PASS\n- shortest-path challenge: PASS\n- total: **3/3 PASS**\n- model calls: **0**\n\nClassification:\n> `JIT_SEMANTIC_V3_MODEL_SELECTION = DOMINATED_BY_SIMPLE_DETERMINISTIC_CONTROLLER`\n\nOperational consequence:\n> Do not spend scarce model inference on this V3 task family as currently written. It does not answer the current limiting question because a cheap deterministic selector already completes the skill-routing decision. Keep the executable skills/verifier as reusable machinery, but move the scientific frontier to JIT knowledge/skill acquisition where deterministic preprocessing cannot already resolve the decision.\n\nThis is non-authority staging evidence and increments no canonical superhero 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