\n1. Start forwarding leads to this webhook from any source as a POST request.\n1. That's it! You now have a growing `leads` SQLite table with one column for\n your original `input_data` and a second column for the AI evaluator's\n `output_data`. You also have a dashboard of this data hosted at the\n [`main.ts`](./main.ts) val endpoint.\n\n## How it works\n\n- When a new lead comes in via POST, it is sent to the OpenAI agent in\n [`agent.ts`](./agent.ts).\n- The agent uses the lead data from your POST request and its web search tool to\n determine if the lead is a `match` for the criteria in\n [`PROMPT.txt`](./PROMPT.txt).\n- By default, the AI's response looks like:\n ```json\n {\n \"match\": \"(true or false)\",\n \"name\": \"(normalized name)\",\n \"reasoning\": \"(explanation)\"\n }\n ```\n- Every lead is added to the `leads` SQLite table:\n - `id` — auto-increment\n - `timestamp` — Unix timestamp\n - `input_data` — JSON of your POST body\n - `output_data` — JSON of AI response\n\n- The [`main.ts`](./main.ts) dashboard shows a history of all lead assessments,\n successful matches first. Clicking any lead shows the full inbound and output\n data from the assessment.\n\n## Options\n\n- You can add any number of fields to the AI's output instructions in\n [`PROMPT.txt`](./PROMPT.txt) and they'll be added to `output_data`. You can\n use this to expand the AI's assessment, enrich your leads, or even just\n normalize lead data coming from different sources.\n- You can also add query parameters when you POST to the val endpoint. (ex:\n `your-val-endpoint.val.run?source=signup-page`). The parameters will be\n bundled in the `_query` object of `input_data`. This can be useful for\n tracking where a lead was forwarded from.",[],[180],{"_105":189,"_96":101,"_159":190,"_161":-5,"_162":142,"_163":191,"_165":166,"_107":192,"_102":193,"_169":194,"_171":195,"_173":22,"_174":-5,"_175":196,"_100":197},"26fe4c2e-db5b-11f0-8360-42dde27851f2","019b240d-f922-75c9-b5f8-30fd2f3df69f",162,["D",1765984499112],9,"script","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(inputData: Record) {\n const result = await run(agent, JSON.stringify(inputData));\n const outputData = JSON.parse(result.finalOutput);\n await storeLead(inputData, outputData);\n\n console.log(\"Stored lead\");\n console.log(result.finalOutput);\n\n return { outputData };\n}",[],[101],{"_105":199,"_96":200,"_159":201,"_161":-5,"_162":142,"_163":141,"_165":166,"_107":202,"_102":203,"_169":194,"_171":204,"_173":22,"_174":-5,"_175":205,"_100":206},"3df11754-db5b-11f0-99dd-42dde27851f2","dashboard.tsx","019b240d-f922-75c9-b5f8-36b85447eb4b",["D",1765984537613],10,"/** @jsxImportSource npm:hono@4/jsx */\nimport { Hono } from \"npm:hono@4\";\nimport { getAllLeads, getLeadById, Lead } from \"./db.ts\";\n\nexport const app = new Hono();\n\nfunction Layout({ children, title }: { children: any; title: string }) {\n return (\n \n \n \n \n {title}\n \n \n {children}\n \n );\n}\n\nfunction LeadRow({ lead, isMatch }: { lead: Lead; isMatch: boolean }) {\n const output = JSON.parse(lead.output_data);\n const date = new Date(lead.timestamp).toLocaleDateString(\"en-US\", {\n month: \"short\",\n day: \"numeric\",\n year: \"numeric\",\n });\n\n return (\n \n \n \n {output.name || \"Unknown\"}\n \n {date}\n \n );\n}\n\nfunction DataTable(\n { title, data }: { title: string; data: Record },\n) {\n const entries = Object.entries(data);\n if (entries.length === 0) return null;\n\n return (\n

\n {title}\n

\n \n \n {entries.map(([key, value], idx) => (\n \n \n \n \n ))}\n \n

{key}

\n {typeof value === \"object\"\n ? JSON.stringify(value)\n : String(value ?? \"\")}\n

\n );\n}\n\napp.get(\"/\", async (c) => {\n const leads = await getAllLeads();\n\n const matches = leads.filter((l) => JSON.parse(l.output_data).match === true);\n const nonMatches = leads.filter((l) =>\n JSON.parse(l.output_data).match !== true\n );\n\n return c.html(\n \n

Leads

\n {leads.length} leads · {matches.length} matches\n

\n\n {leads.length === 0\n ? (\n

\n No leads yet. POST to this endpoint to add leads.\n

\n )\n : (\n

\n {matches.map((lead) => )}\n\n {nonMatches.length > 0 && (\n

\n \n \n {nonMatches.length} not matched\n \n ▼\n \n

\n {nonMatches.map((lead) => (\n \n ))}\n

\n )}\n

\n ,\n );\n});\n\napp.get(\"/lead/:id\", async (c) => {\n const id = parseInt(c.req.param(\"id\"));\n const lead = await getLeadById(id);\n\n if (!lead) {\n return c.html(\n \n

Lead Not Found

\n \n ← Back\n \n

\n ,\n 404,\n );\n }\n\n const input = JSON.parse(lead.input_data);\n const output = JSON.parse(lead.output_data);\n\n return c.html(\n \n

\n \n ← Back\n \n\n

\n {output.name || \"Unknown\"}\n

\n {new Date(lead.timestamp).toLocaleString()}\n

\n\n {/* Result Summary */}\n \n

\n \n \n {output.match ? \"Match\" : \"No Match\"}\n \n

\n {output.reasoning || \"No reasoning provided\"}\n

\n\n {/* Input Data */}\n \n\n {/* AI Output */}\n \n \n ,\n );\n});\n\nexport default app.fetch;",[],[200],{"_105":208,"_96":209,"_159":210,"_161":-5,"_162":142,"_163":211,"_165":166,"_107":212,"_102":213,"_169":194,"_171":214,"_173":22,"_174":-5,"_175":215,"_100":216},"8c61b72e-daf0-11f0-ba97-42dde27851f2","db.ts","019b240d-f922-75c9-b5f8-3aad7088ad64",149,["D",1765938713060],8,"import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\nconst TABLE_NAME = \"leads\";\n\nawait createTable();\n\nexport interface Lead {\n id: number;\n timestamp: number;\n input_data: string;\n output_data: string;\n}\n\nexport async function storeLead(\n inputData: Record,\n outputData: Record,\n) {\n await sqlite.execute(\n `INSERT INTO ${TABLE_NAME} (timestamp, input_data, output_data)\n VALUES (?, ?, ?)`,\n [Date.now(), JSON.stringify(inputData), JSON.stringify(outputData)],\n );\n}\n\nexport async function getAllLeads(): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${TABLE_NAME} ORDER BY timestamp DESC`,\n );\n return rowsToLeads(result);\n}\n\nexport async function getLeadById(id: number): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${TABLE_NAME} WHERE id = ?`,\n [id],\n );\n const leads = rowsToLeads(result);\n return leads[0] || null;\n}\n\nfunction rowsToLeads(result: { columns: string[]; rows: unknown[] }): Lead[] {\n return result.rows.map((row: any) => {\n const obj: Record = {};\n result.columns.forEach((col, idx) => {\n obj[col] = row[idx];\n });\n return obj as Lead;\n });\n}\n\nasync function createTable() {\n await sqlite.execute(\n `CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n timestamp INTEGER NOT NULL,\n input_data TEXT NOT NULL,\n output_data TEXT NOT NULL\n )`,\n );\n}\n",[],[209],{"_105":218,"_96":219,"_159":220,"_161":-5,"_162":142,"_163":221,"_165":166,"_107":222,"_102":168,"_169":223,"_171":224,"_173":22,"_174":-5,"_175":225,"_100":226},"72be2de6-dacf-11f0-a8c9-42dde27851f2","main.ts","019b240d-f922-75c9-b5f8-40e88aa7485a",85,["D",1765924496615],"http","import { Hono } from \"npm:hono@4\";\nimport { processLead } from \"./agent.ts\";\nimport { app as dashboard } from \"./dashboard.tsx\";\n\nconst app = new Hono();\n\napp.post(\"/\", async (c) => {\n const body = await c.req.json();\n const url = new URL(c.req.url);\n const query = Object.fromEntries(url.searchParams);\n const inputData = Object.keys(query).length ? { ...body, _query: query } : body;\n\n console.log(inputData);\n\n fetch(`${url.origin}/process`, {\n method: \"POST\",\n headers: { \"Content-Type\": \"application/json\" },\n body: JSON.stringify(inputData),\n });\n\n return c.json({ ok: true });\n});\n\napp.post(\"/process\", async (c) => {\n const inputData = await c.req.json();\n await processLead(inputData);\n return c.json({ ok: true });\n});\n\napp.route(\"/\", dashboard);\n\nexport default app.fetch;\n",[],[219],"files",[156,178,188,198,207,217],"counts",{"_231":32,"_232":233,"_234":235,"_236":237},"pulls","branches",3,"forks",1,"envVars",{"_238":235,"_239":32},"count","emptyCount","contents",[],{"_105":189,"_96":101,"_159":190,"_161":-5,"_162":142,"_163":191,"_165":166,"_107":243,"_102":193,"_169":194,"_171":195,"_173":22,"_174":-5,"_100":244},["D",1765984499112],[101],"upstreamProject","upstreamBranch",{"_105":145,"_107":248,"_249":250,"_96":44,"_143":106,"_102":251,"_144":-5,"_146":-5,"_252":253,"_109":-5,"_153":22,"_111":112,"_152":95,"_16":123,"_151":97},["D",1765818489674],"updatedAt",["D",1766000370106],118,"lockfileKey","1766000370243-esm.town_v_valdottown_leads@118-main","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.branch.$branch.history_.$",{"_94":95,"_96":97,"_98":99,"_100":101,"_103":260,"_170":265,"_268":269,"_319":320,"_332":-7,"_333":32,"_334":22},{"_105":106,"_96":97,"_107":261,"_109":-5,"_110":22,"_111":112,"_113":114,"_115":116,"_14":117,"_118":-5,"_119":22,"_120":-5,"_121":-5,"_122":32,"_16":123,"_124":125,"_126":125,"_127":128,"_129":128,"_130":128,"_131":125,"_132":125,"_23":262,"_136":263,"_139":264,"_153":22},["D",1765818489674],{"_94":95,"_134":135},{"_94":95,"_138":135,"_14":-5},{"_102":141,"_96":99,"_105":142,"_143":106,"_144":145,"_146":147,"_148":112,"_149":106,"_150":123,"_151":97,"_152":95},{"_105":189,"_96":101,"_159":190,"_161":-5,"_162":142,"_163":191,"_165":166,"_107":266,"_102":193,"_169":194,"_171":195,"_173":22,"_174":-5,"_100":267},["D",1765984499112],[101],"history",[270,272,277,283,289,294,300,305,311,315],{"_105":189,"_162":142,"_159":190,"_96":101,"_171":195,"_169":194,"_102":193,"_161":-5,"_107":271,"_163":191,"_174":-5},["D",1765984499112],{"_105":273,"_162":142,"_159":190,"_96":101,"_171":274,"_169":194,"_102":213,"_161":-5,"_107":275,"_163":276,"_174":-5},"cdbb0094-dadd-11f0-9362-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5.2\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(inputData: Record) {\n const result = await run(agent, JSON.stringify(inputData));\n const outputData = JSON.parse(result.finalOutput);\n await storeLead(inputData, outputData);\n\n console.log(\"Stored lead\");\n console.log(result.finalOutput);\n\n return { outputData };\n}",["D",1765930662263],97,{"_105":278,"_162":142,"_159":190,"_96":101,"_171":279,"_169":194,"_102":280,"_161":-5,"_107":281,"_163":282,"_174":-5},"c8fc8604-dadd-11f0-a884-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5,2\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(inputData: Record) {\n const result = await run(agent, JSON.stringify(inputData));\n const outputData = JSON.parse(result.finalOutput);\n await storeLead(inputData, outputData);\n\n console.log(\"Stored lead\");\n console.log(result.finalOutput);\n\n return { outputData };\n}",7,["D",1765930654297],96,{"_105":284,"_162":142,"_159":190,"_96":101,"_171":285,"_169":194,"_102":286,"_161":-5,"_107":287,"_163":288,"_174":-5},"bd467032-dacd-11f0-9bec-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(inputData: Record) {\n const result = await run(agent, JSON.stringify(inputData));\n const outputData = JSON.parse(result.finalOutput);\n await storeLead(inputData, outputData);\n\n console.log(\"Stored lead\");\n console.log(result.finalOutput);\n\n return { outputData };\n}\n",6,["D",1765923762705],84,{"_105":290,"_162":142,"_159":190,"_96":101,"_171":291,"_169":194,"_102":168,"_161":-5,"_107":292,"_163":293,"_174":-5},"1a9c08d4-dabd-11f0-b9c3-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(inputData: Record) {\n const result = await run(agent, JSON.stringify(inputData));\n const outputData = JSON.parse(result.finalOutput);\n const id = await storeLead(inputData, outputData);\n\n console.log(`Stored lead #${id}`);\n console.log(result.finalOutput);\n\n return { id, outputData };\n}\n",["D",1765916617848],59,{"_105":295,"_162":142,"_159":190,"_96":101,"_171":296,"_169":194,"_102":297,"_161":-5,"_107":298,"_163":299,"_174":-5},"904aea4a-da2d-11f0-9988-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { blob } from \"https://esm.town/v/std/blob\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(input: Record, source?: string) {\n const result = await run(agent, JSON.stringify(input));\n\n const output = JSON.parse(result.finalOutput);\n const id = await storeLead(input, output, source);\n\n // Full debug to blob, keyed by id\n await blob.setJSON(`lead-scores/${id}`, {\n id,\n input,\n fullResult: result,\n finalOutput: output,\n });\n\n console.log(`lead-scores/${id}`);\n console.log(result.finalOutput);\n\n return { id, output };\n}\n",4,["D",1765854967747],45,{"_105":301,"_162":142,"_159":190,"_96":101,"_171":302,"_169":194,"_102":233,"_161":-5,"_107":303,"_163":304,"_174":-5},"274c0a18-da2a-11f0-a16e-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { blob } from \"https://esm.town/v/std/blob\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"Researcher\",\n model: \"gpt-5\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function processLead(input: Record, source?: string) {\n const runId = Date.now();\n\n const result = await run(agent, JSON.stringify(input));\n\n // Full debug to blob\n await blob.setJSON(`lead-scores/${runId}`, {\n timestamp: runId,\n input,\n fullResult: result,\n finalOutput: result.finalOutput,\n });\n\n const output = JSON.parse(result.finalOutput);\n const id = await storeLead(input, output, source);\n\n console.log(`/lead-scores/${runId}`);\n console.log(result.finalOutput);\n\n return { id, runId, output };\n}\n",["D",1765853503103],22,{"_105":306,"_162":142,"_159":190,"_96":101,"_171":307,"_169":194,"_102":308,"_161":-5,"_107":309,"_163":310,"_174":-5},"9f19a72c-da24-11f0-926e-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"researcher\",\n model: \"gpt-5.1-2025-11-13\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\ninterface AIOutput {\n idealCustomer: \"yes\" | \"no\" | \"insufficient_data\";\n reasoning: string;\n}\n\nexport async function processLead(\n input: Record,\n source: string,\n): Promise<{ id: number; aiOutput: AIOutput }> {\n const startedAt = Date.now();\n\n const result = await run(agent, JSON.stringify(input));\n\n // Strip markdown code fences if present\n const jsonMatch = result.finalOutput.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) {\n throw new Error(\"No JSON found in AI response\");\n }\n const aiOutput: AIOutput = JSON.parse(jsonMatch[0]);\n\n const id = await storeLead(\n source,\n aiOutput.idealCustomer,\n aiOutput.reasoning,\n { input, aiOutput, runData: { startedAt, completedAt: Date.now() } },\n );\n\n console.log(`[Agent] Stored lead #${id} (${aiOutput.idealCustomer})`);\n\n return { id, aiOutput };\n}\n",2,["D",1765851127133],16,{"_105":312,"_162":142,"_159":190,"_96":101,"_171":313,"_169":194,"_102":235,"_161":-5,"_107":314,"_163":233,"_174":-5},"6de8b4a6-da04-11f0-8e2c-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"researcher\",\n model: \"gpt-5.1-2025-11-13\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\ninterface AIOutput {\n name: string;\n idealCustomer: \"yes\" | \"no\" | \"insufficient_data\";\n reasoning: string;\n}\n\nexport async function processLead(\n input: Record,\n source: string,\n): Promise<{ id: number; aiOutput: AIOutput }> {\n const startedAt = Date.now();\n\n const result = await run(agent, JSON.stringify(input));\n\n // Strip markdown code fences if present\n const jsonMatch = result.finalOutput.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) {\n throw new Error(\"No JSON found in AI response\");\n }\n const aiOutput: AIOutput = JSON.parse(jsonMatch[0]);\n\n const id = await storeLead(\n source,\n aiOutput.name,\n aiOutput.idealCustomer,\n aiOutput.reasoning,\n { input, aiOutput, runData: { startedAt, completedAt: Date.now() } },\n );\n\n console.log(`[Agent] Stored lead #${id}: ${aiOutput.name} (${aiOutput.idealCustomer})`);\n\n return { id, aiOutput };\n}\n",["D",1765837300711],{"_105":316,"_162":142,"_159":190,"_96":101,"_171":317,"_169":194,"_102":32,"_161":-5,"_107":318,"_163":235,"_174":-5},"755900e4-da02-11f0-a1a0-42dde27851f2","import { readFile } from \"https://esm.town/v/std/utils/index.ts\";\nimport { Agent, run, webSearchTool } from \"npm:@openai/agents@0.3.0\";\nimport { storeLead, LeadInput } from \"./db.ts\";\n\nconst PROMPT = await readFile(\"/PROMPT.txt\");\nconst agent = new Agent({\n name: \"researcher\",\n model: \"gpt-5.1-2025-11-13\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\ninterface AIOutput {\n name: string;\n company: string | null;\n role: string | null;\n linkedinUrl: string | null;\n email: string | null;\n idealCustomer: \"yes\" | \"no\" | \"insufficient_data\";\n reasoning: string;\n}\n\nexport async function processLead(\n input: Record,\n source: string,\n): Promise<{ id: number; aiOutput: AIOutput }> {\n const startedAt = Date.now();\n\n const result = await run(agent, JSON.stringify(input));\n\n // Strip markdown code fences if present\n const jsonMatch = result.finalOutput.match(/\\{[\\s\\S]*\\}/);\n if (!jsonMatch) {\n throw new Error(\"No JSON found in AI response\");\n }\n const aiOutput: AIOutput = JSON.parse(jsonMatch[0]);\n\n const lead: LeadInput = {\n name: aiOutput.name || \"Unknown\",\n company: aiOutput.company || \"Unknown\",\n role: aiOutput.role || \"Unknown\",\n linkedinUrl: aiOutput.linkedinUrl,\n email: aiOutput.email,\n source,\n idealCustomer: aiOutput.idealCustomer,\n reasoning: aiOutput.reasoning,\n rawData: {\n input,\n aiOutput,\n runData: {\n startedAt,\n completedAt: Date.now(),\n },\n },\n };\n\n const id = await storeLead(lead);\n\n console.log(`[Agent] Stored lead #${id}: ${aiOutput.name} (${aiOutput.idealCustomer})`);\n\n return { id, aiOutput };\n}\n",["D",1765836454185],"versions",[321,323,324,325,326,327,328,329,330,331],{"_170":270,"_322":272},"previous",{"_170":272,"_322":277},{"_170":277,"_322":283},{"_170":283,"_322":289},{"_170":289,"_322":294},{"_170":294,"_322":300},{"_170":300,"_322":305},{"_170":305,"_322":311},{"_170":311,"_322":315},{"_170":315,"_322":-5},"versionNumber","page","hasNext","actionData","errors"]

valdottown

leads

History for agent.ts