Request received.

Thank you. CLOSER has received your request for qualification and follow-up.

Back to offers`,{headers:{\"content-type\":\"text/html; charset=utf-8\"}});\n }\n let products:any[]=[];try{const r=await fetch(HUB);const d=await r.json();products=Array.isArray(d.products)?d.products:[]}catch{}\n const cards=products.map(p=>`

PUBLIC MARKET TEST

${esc(p.title)}

For: ${esc(p.audience)}

${esc(p.offer)}

${esc(p.price_hypothesis)}

`).join(\"\");\n const options=products.map(p=>``).join(\"\");\n const html=`IMPERIAL Core — Professional Services Lab

FORGE · NCA-REVENUE-004 · LIVE REVENUE EXPERIMENT

Professional AI-Agent
Architecture Services

Evidence-led offers built from IMPERIAL Core’s governance and multi-agent engineering work. Prices shown are market-test hypotheses, not proof of prior revenue. No investment, profit or certification claims.

${cards||\"

Offers are being initialized.

\"}

Request a discovery call / scoped proposal

`;\n return new Response(html,{headers:{\"content-type\":\"text/html; charset=utf-8\",\"cache-control\":\"no-store\"}})\n}","imperial-forge-offers",[143],"89f0b446-4f4a-457c-9784-67917bf41396","forge-cycle.ts","2a905efc-a09c-11f1-bb24-1607ee4eb77e",11,["D",1787674046284],8,"interval","import { sqlite } from \"https://esm.town/v/std/sqlite/main.ts\";\nimport Anthropic from \"npm:@anthropic-ai/sdk\";\n\nconst AGENT=\"FORGE\";\nconst AGENT_ID=\"NCA-REVENUE-004\";\nconst HUB=\"https://imperial-agent-dealroom.val.run/\";\nfunction key(){return Deno.env.get(\"CLOSER_FORGE_KEY\")||\"\"}\nasync function hubGet(){const r=await fetch(HUB,{headers:{\"x-imperial-agent-key\":key(),\"user-agent\":\"FORGE-NCA-REVENUE-004\"}});if(!r.ok)throw new Error(`HUB_GET_${r.status}`);return await r.json()}\nasync function hubPost(body:any){const r=await fetch(HUB,{method:\"POST\",headers:{\"content-type\":\"application/json\",\"x-imperial-agent-key\":key()},body:JSON.stringify(body)});if(!r.ok)throw new Error(`HUB_POST_${r.status}:${await r.text()}`);return await r.json()}\n\nconst BASE_OFFERS=[\n {slug:\"ai-governance-audit\",title:\"AI Agent Governance Audit\",audience:\"Startups and teams deploying AI agents or agentic workflows\",offer:\"Evidence-led review of identity, capability boundaries, approval gates, runtime separation, auditability and production-readiness gaps. Deliverable: prioritized governance gap report and target architecture. This is an architecture/review service, not legal certification.\",price_hypothesis:\"USD 490 pilot / USD 1,500 full review — hypothesis, not validated revenue\",status:\"PUBLIC_TEST\"},\n {slug:\"multi-agent-blueprint-sprint\",title:\"Governed Multi-Agent Blueprint Sprint\",audience:\"Founders and engineering teams planning multi-agent products\",offer:\"Structured architecture sprint covering agent roles, orchestration boundaries, runtime domains, tool permissions, human approvals, audit trails and implementation backlog. Deliverable: system blueprint + staged execution plan.\",price_hypothesis:\"USD 1,500 pilot / USD 3,500 expanded sprint — hypothesis, not validated revenue\",status:\"PUBLIC_TEST\"},\n {slug:\"agent-security-readiness-review\",title:\"AI Agent Security & Readiness Review\",audience:\"Teams preparing an agent system for controlled pilot or production\",offer:\"Defensive architecture-level review of attack surface, secret/tool boundaries, replay/TOCTOU risks, approval bypass paths, evidence quality and launch gates. Deliverable: blocker list, risk matrix and remediation sequence. Not a penetration test.\",price_hypothesis:\"USD 750 pilot / USD 2,500 full review — hypothesis, not validated revenue\",status:\"PUBLIC_TEST\"}\n];\n\nfunction validateOffer(p:any,data:any){\n const messages=Array.isArray(data?.messages)?data.messages:[];\n const campaigns=Array.isArray(data?.campaigns)?data.campaigns:[];\n const slug=String(p.slug).toLowerCase();\n const inbound=messages.filter((m:any)=>String(m.kind)===\"INBOUND_PRODUCT_LEAD\"&&String(m.payload||\"\").toLowerCase().includes(slug)).length;\n const demandCampaigns=campaigns.filter((c:any)=>String(c.title||\"\").toLowerCase().includes(slug)&&[\"X\",\"LinkedIn\",\"Reddit\",\"Telegram\"].includes(String(c.channel))).length;\n const salesInputs=messages.filter((m:any)=>[\"MARKET_OBJECTION_INPUT\",\"DEMAND_GENERATION_PACK\",\"SALES_PRIORITY_BRIEF\"].includes(String(m.kind))).length;\n const score=Math.min(100,35+Math.min(20,demandCampaigns*5)+Math.min(30,inbound*15)+Math.min(15,salesInputs*3));\n const status=inbound>=2?\"VALIDATING\":inbound>=1?\"VALIDATING\":\"PUBLIC_TEST\";\n return {slug:p.slug,score,status,inboundQualifiedSignals:inbound,demandCampaigns,salesInputs,experiment:{hypothesis:`${p.audience} will request a scoped conversation for ${p.title} when the offer is framed around a concrete delivery outcome.`,primaryKPI:\"QUALIFIED_INBOUND_REQUESTS\",secondaryKPI:\"DISCOVERY_CALLS\",successThreshold:\"At least 1 qualified inbound request or 2 discovery calls before changing price\",nextAction:inbound?\"INTERVIEW_LEAD_AND_CAPTURE_OBJECTIONS\":\"RUN_CHANNEL_DEMAND_TEST_AND_COLLECT_EXPLICIT_PROBLEM_SIGNAL\"},truthBoundary:\"SCORE_IS_EXPERIMENT_READINESS_NOT_REVENUE\"};\n}\n\n\nasync function productAdvice(context:any){\n const apiKey=Deno.env.get(\"ANTHROPIC_API_KEY\");\n if(!apiKey){\n const local=Deno.env.get(\"LOCAL_LLM_URL\");\n if(local){\n try{const r=await fetch(`${local.replace(/\\/$/,\"\")}/v1/chat/completions`,{method:\"POST\",headers:{\"content-type\":\"application/json\"},body:JSON.stringify({model:\"Qwen3.5-0.8B\",messages:[{role:\"system\",content:\"You are a senior evidence-led product and revenue strategist. Never invent customers, revenue, adoption or certifications.\"},{role:\"user\",content:JSON.stringify(context).slice(0,30000)}],temperature:0.2,max_tokens:800})});const j=await r.json();return {mode:\"FREE_LOCAL_QWEN3_5\",text:String(j?.choices?.[0]?.message?.content||\"\").slice(0,9000)}}catch(e){return {mode:\"FREE_LOCAL_LLM_ERROR\",error:String(e)}}\n }\n return {mode:\"FABLE_5_ADAPTER_INSTALLED_NOT_ACTIVATED\",reason:\"ANTHROPIC_API_KEY_MISSING\",freeFallback:\"LOCAL_LLM_URL_READY_FOR_QWEN3_5\"};\n }\n try{\n const client=new Anthropic({apiKey});\n const res=await client.messages.create({model:\"claude-fable-5\",max_tokens:1000,system:\"You are the senior product and revenue strategist for IMPERIAL Core. Improve B2B offers using evidence, customer objections and conversion logic. Never invent customers, revenue, adoption, certifications, testimonials or partnerships. Treat prices as hypotheses until validated. Return concise JSON with offer_changes, pricing_tests, proof_needed, and next_experiment.\",messages:[{role:\"user\",content:JSON.stringify(context).slice(0,50000)}]});\n const text=res.content.filter((x:any)=>x.type===\"text\").map((x:any)=>x.text).join(\"\\n\");\n return {mode:\"CLAUDE_FABLE_5\",text:text.slice(0,12000)};\n }catch(e){return {mode:\"FABLE_5_ERROR\",error:String(e)}}\n}\n\nexport default async function(_interval:Interval){\n const observedAt=new Date().toISOString();\n await sqlite.execute(\"CREATE TABLE IF NOT EXISTS cycles(id INTEGER PRIMARY KEY AUTOINCREMENT,observed_at TEXT NOT NULL,payload TEXT NOT NULL)\");\n await sqlite.execute(\"CREATE TABLE IF NOT EXISTS state(key TEXT PRIMARY KEY,value TEXT NOT NULL)\");\n const data:any=await hubGet();\n const inputs=(Array.isArray(data.messages)?data.messages:[]).filter((m:any)=>String(m.recipient)===\"FORGE\"||String(m.kind).includes(\"MARKET\")||String(m.kind).includes(\"GROWTH\")).slice(0,20);\n const deals=(Array.isArray(data.deals)?data.deals:[]).slice(0,20);\n const campaigns=(Array.isArray(data.campaigns)?data.campaigns:[]).filter((c:any)=>c.owner===\"REM\").slice(0,20);\n const evidence={marketInputs:inputs.map((m:any)=>({kind:m.kind,priority:m.priority,payload:String(m.payload).slice(0,1200)})),dealStages:deals.map((d:any)=>({account:d.account,stage:d.stage,nextAction:d.next_action})),campaignChannels:[...new Set(campaigns.map((c:any)=>c.channel))]};\n\n const validations=BASE_OFFERS.map(p=>validateOffer(p,data));\n for(const p of BASE_OFFERS){\n const validation=validations.find(v=>v.slug===p.slug)!;\n await hubPost({action:\"product\",owner:AGENT,...p,status:validation.status,evidence:{createdFrom:\"IMPERIAL Core proven architecture/governance work + current institutional qualification signals\",observedAt,evidence,validation}});\n }\n\n const q=await sqlite.execute(\"SELECT value FROM state WHERE key='last_fable_at'\");\n const last=Date.parse(String(q.rows?.[0]?.value||\"\"));\n const due=!Number.isFinite(last)||Date.now()-last>6*60*60*1000;\n const advice=due?await productAdvice({observedAt,offers:BASE_OFFERS,validations,evidence}):{mode:\"SKIPPED_NOT_DUE\"};\n if(due)await sqlite.execute({sql:\"INSERT INTO state(key,value) VALUES('last_fable_at',?) ON CONFLICT(key) DO UPDATE SET value=excluded.value\",args:[observedAt]});\n\n const digest=JSON.stringify(validations.map(v=>[v.slug,v.status,v.score,v.inboundQualifiedSignals,v.demandCampaigns]));\n const d=await sqlite.execute(\"SELECT value FROM state WHERE key='last_digest'\");\n if(String(d.rows?.[0]?.value||\"\")!==digest){\n await hubPost({action:\"message\",sender:AGENT,recipient:\"REM\",kind:\"PRODUCTS_READY_FOR_DEMAND_TEST\",priority:\"HIGH\",payload:{observedAt,offers:BASE_OFFERS.map(x=>({slug:x.slug,title:x.title,audience:x.audience,priceHypothesis:x.price_hypothesis,validation:validations.find(v=>v.slug===x.slug)})),request:\"Run factual organic demand tests by channel and optimize for qualified inbound requests. Do not imply existing customers or proven revenue.\"}});\n await hubPost({action:\"message\",sender:AGENT,recipient:\"CLOSER\",kind:\"OFFERS_READY_TO_SELL\",priority:\"HIGH\",payload:{observedAt,offers:BASE_OFFERS.map(x=>({slug:x.slug,title:x.title,audience:x.audience,priceHypothesis:x.price_hypothesis,validation:validations.find(v=>v.slug===x.slug)})),request:\"Match offers to qualified B2B prospects; run explicit discovery and capture objections as evidence before changing scope or pricing.\"}});\n await sqlite.execute({sql:\"INSERT INTO state(key,value) VALUES('last_digest',?) ON CONFLICT(key) DO UPDATE SET value=excluded.value\",args:[digest]});\n }\n const payload={schema:\"ic.forge.runtime.v2\",observedAt,agent:AGENT,agentId:AGENT_ID,role:\"PRODUCT_REVENUE_AND_VALIDATION_ENGINEERING\",offers:BASE_OFFERS,validations,advice,truthBoundary:{revenue:\"NOT_YET_VERIFIED\",customers:\"NOT_YET_VERIFIED\",pricing:\"HYPOTHESIS_UNTIL_VALIDATED\",validationScores:\"EXPERIMENT_READINESS_NOT_REVENUE\"}};\n await sqlite.execute({sql:\"INSERT INTO cycles(observed_at,payload) VALUES(?,?)\",args:[observedAt,JSON.stringify(payload)]});\n console.log(JSON.stringify({ok:true,observedAt,agent:AGENT,role:\"PRODUCT_REVENUE_AND_VALIDATION_ENGINEERING\",offers:BASE_OFFERS.length,validations:validations.map(v=>({slug:v.slug,score:v.score,status:v.status,inbound:v.inboundQualifiedSignals,demandCampaigns:v.demandCampaigns,nextAction:v.experiment.nextAction})),llm:advice.mode,revenue:\"NOT_YET_VERIFIED\"}));\n}",[150],"2c8fcd43-1ec1-4054-8ed8-592a472e52e7","skills","01a03e0b-4fa9-7189-86ad-578d321cf53f",["D",1787747323820],"directory",[159],"pulls","branches","forks","envVars",{"_171":126,"_173":42},"connections",{"_171":42,"_172":42},"count","unfilledCount","emptyCount",{"_18":158,"_20":159,"_118":160,"_120":-5,"_121":71,"_122":69,"_124":38,"_22":207,"_68":42,"_127":162,"_129":-5,"_131":26,"_132":-5,"_182":208,"_89":209},{"_18":203,"_20":202,"_118":197,"_120":160,"_121":71,"_122":69,"_124":38,"_22":204,"_68":42,"_127":162,"_129":-5,"_131":26,"_132":-5,"_182":205,"_89":206},{"_18":194,"_20":195,"_118":196,"_120":197,"_121":71,"_122":69,"_124":38,"_22":198,"_68":42,"_127":100,"_129":199,"_131":26,"_132":-5,"_182":200,"_89":201},{"_18":149,"_20":150,"_118":151,"_120":-5,"_121":71,"_122":152,"_124":38,"_22":191,"_68":154,"_127":155,"_129":156,"_131":26,"_132":-5,"_182":192,"_89":193},{"_18":142,"_20":143,"_118":36,"_120":-5,"_121":71,"_122":144,"_124":38,"_22":188,"_68":42,"_127":128,"_129":146,"_131":26,"_132":147,"_182":189,"_89":190},{"_18":135,"_20":136,"_118":137,"_120":-5,"_121":71,"_122":138,"_124":38,"_22":185,"_68":42,"_127":100,"_129":140,"_131":26,"_132":-5,"_182":186,"_89":187},{"_18":116,"_20":117,"_118":119,"_120":-5,"_121":71,"_122":123,"_124":38,"_22":181,"_68":126,"_127":128,"_129":130,"_131":26,"_132":133,"_182":183,"_89":184},["D",1787674162463],"children",[],[117],["D",1787672991432],[],[136],["D",1787672881359],[],[143],["D",1787674046284],[],[150],"dc582b24-041a-4a11-8b91-5cfcdd1af44e","SKILL.md","01a03e0b-4fa9-7189-86ad-5f7a9caf495d","01a03e0b-4fa9-7189-86ad-59d918496cb1",["D",1787747323820],"---\nname: find-skills\ndescription: Helps users discover and install agent skills when they ask questions like \"how do I do X\", \"find a skill for X\", \"is there a skill that can...\", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.\n---\n\n# Find Skills\n\nThis skill helps you discover and install skills from the open agent skills ecosystem.\n\n## When to Use This Skill\n\nUse this skill when the user:\n- Asks \"how do I do X\" where X might be a common task with an existing skill\n- Says \"find a skill for X\" or \"is there a skill for X\"\n- Asks \"can you do X\" where X is a specialized capability\n- Expresses interest in extending agent capabilities\n- Wants to search for tools, templates, or workflows\n- Mentions they wish they had help with a specific domain\n\n## Skills CLI\n\nThe Skills CLI (`npx skills`) is the package manager for the open agent skills ecosystem.\n\nKey commands:\n- `npx skills find [query] [--owner ]`\n- `npx skills add `\n- `npx skills update`\n- `npx skills list`\n\nBrowse skills at: https://skills.sh/\n\n## Selection workflow\n\n1. Understand the domain, exact task, runtime and constraints.\n2. Check the skills.sh leaderboard first for established options.\n3. Search using specific keywords; try alternate terms when needed.\n4. Verify quality before recommending or installing:\n - prefer reputable/official sources such as vercel-labs, anthropics and microsoft;\n - consider install count and repository reputation;\n - inspect SKILL.md and any scripts/hooks before trusting them;\n - reject skills that request unnecessary secrets, excessive permissions, hidden network actions, destructive behavior, bypasses, spam, deceptive claims, or unverified execution authority.\n5. Compare the strongest candidates against the current system before installing. A new skill must materially improve capability, quality, reliability, safety or execution speed; do not install duplicates for collection's sake.\n6. Install only the selected skill and preserve provenance.\n7. Test the target agent after installation and record PASS/BLOCKED/NOT_VERIFIED accurately.\n\n## Typical commands\n\n```bash\nnpx skills find react performance\nnpx skills find pr review\nnpx skills find changelog\nnpx skills add -g -y\n```\n\n## IMPERIAL selection gate\n\nSearch is discovery, not trust. Candidate skill status must pass:\nSOURCE_REPUTATION -> CONTENT_REVIEW -> PERMISSION_MINIMIZATION -> DUPLICATE_CHECK -> COMPATIBILITY -> SANDBOX/TEST -> ADOPT_OR_REJECT.\n\nNever equate popularity with correctness. Never claim a skill is installed, working, or production-ready without runtime evidence.\n\nUpstream: vercel-labs/skills, skills/find-skills/SKILL.md\nReviewed source blob: a41bdd074bb587afd861332cf2f473f3154de4d7\n",[],[159,202,195],"find-skills","9ad3e54b-e1fa-46a4-82f2-99e7c7d0211f",["D",1787747323820],[176],[159,202],["D",1787747323820],[175],[159],["D",1787672801374],["D",1789497078049],{"_16":17,"_87":83},{"_16":17,"_80":81,"_82":83,"_33":34,"_84":85,"_86":26},{"_68":69,"_20":70,"_18":71,"_72":19,"_73":-5,"_74":-5,"_75":-5,"_76":-5,"_77":-5,"_78":21,"_79":17},"ctx",{"_61":-5,"_108":248,"_249":250,"_251":252,"_253":26,"_254":26,"_255":26,"_256":38,"_257":-5,"_258":-7,"_259":-7,"_260":42,"_261":26,"_262":26,"_263":-5,"_264":26,"_265":26,"_266":26,"_267":-5},"ENV",{"_219":220,"_221":222,"_223":70,"_224":225,"_226":227,"_228":229,"_230":231,"_232":233,"_234":235,"_236":237,"_238":239,"_240":241,"_242":243,"_244":245,"_246":247},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","RENDER_GIT_COMMIT","e87eb04e707cf64e7e532c8e8ec395f209e17f15","RENDER_GIT_BRANCH","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","VANITY_WEB_API_TEMPLATE","https://{label}.val.run/","DENOLS_URL","https://lsp.val.town","NODE_ENV","production","CLOUDFLARE_TURNSTILE_SITE_KEY","0x4AAAAAACtaIZJH7s9rBMZ6","GOOGLE_CLIENT_ID","875989696899-jtsqkhlbdv5jrlsk8631p7ipjg3c6o62.apps.googleusercontent.com","STRIPE_PUBLISHABLE_KEY","pk_live_51N2zvWEpZTTLipIkVEwXrUG9AT0yeOOEYxszarZT1jpsZV58Ly6wlg3SltZpHN26CUalOBmUSY7adQRQiSkCZz2500qSXNkf8Y","API_URL","https://api.val.town",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]

Request received.

${esc(p.title)}

Professional AI-AgentArchitecture Services

Offers are being initialized.

Request a discovery call / scoped proposal

Professional AI-Agent
Architecture Services