[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8,"_9":10},"actionData","errors","root",{"_252":253,"_254":255},"routes/_app.x.$handle.$name",{"_139":138,"_38":87,"_148":129,"_33":149,"_13":14,"_150":-5,"_11":151,"_152":153,"_154":155,"_156":157,"_158":159,"_27":-5,"_160":-5,"_161":-5,"_162":31,"_163":164,"_165":101,"_166":-5,"_167":-5,"_168":169},"routes/_app.x.$handle.$name.branch.$branch.version.$version.diff",{"_11":12,"_13":14,"_15":16,"_17":-5,"_18":-5},"project",{"_85":86,"_38":87,"_43":88,"_89":-5,"_90":31,"_91":92,"_93":92,"_94":95,"_96":97,"_18":98,"_99":50,"_100":101,"_102":101,"_103":-5,"_104":105,"_106":107,"_108":-5,"_109":-5,"_110":-5,"_111":-5,"_112":113,"_114":113,"_115":116,"_117":116,"_118":116,"_119":113,"_120":113,"_121":122,"_123":124,"_125":126,"_127":31},"version",1,"changes",[19,20,21,22,23,24,25,26],"aiChatInfo","userId",{"_27":80,"_29":-7,"_30":31,"_32":31,"_33":81,"_35":81},{"_27":75,"_29":-7,"_30":31,"_32":31,"_33":76,"_35":76},{"_27":70,"_29":-7,"_30":31,"_32":31,"_33":71,"_35":71},{"_27":65,"_29":-7,"_30":31,"_32":31,"_33":66,"_35":66},{"_27":60,"_29":-7,"_30":31,"_32":31,"_33":61,"_35":61},{"_27":54,"_29":-7,"_30":31,"_32":31,"_33":55,"_35":55},{"_27":48,"_29":-7,"_30":31,"_32":31,"_33":49,"_35":49},{"_27":28,"_29":-7,"_30":31,"_32":31,"_33":34,"_35":34},"file",{"_36":37,"_38":34,"_39":40,"_41":42,"_43":44,"_45":14,"_46":47,"_30":31},"previous","deleted",false,"deletedHere","path","testing.ts","latestPath","fileId","019aef13-0475-73bd-b8a8-48ee235abd6f","name","fileType","script","content","import { runAgent } from \"./agent.ts\";\nimport { storeLead } from \"./db.ts\";\nimport { blob } from \"https://esm.town/v/std/blob\";\n\nconst testPayload = {\n \"LinkedIn URL\": \"https://www.linkedin.com/in/retentionadam\",\n \"First Name\": \"Adam\",\n \"Last Name\": \"Test Payload\",\n \"Title\": \"Webhook Test Payload from RB2B\",\n \"Company Name\": \"RB2B\",\n \"Business Email\": \"test@test.com\",\n \"Website\": \"https://rb2b.com\",\n \"Industry\": \"Internet Technology & Services\",\n \"Employee Count\": \"1-10\",\n \"Estimate Revenue\": \"$24M rev\",\n \"City\": \"Austin\",\n \"State\": \"Texas\",\n \"Zipcode\": \"73301\",\n \"Seen At\": \"2025-12-02 22:19:26 +0000\",\n \"Referrer\": \"https://google.com\",\n \"Captured URL\": \"https://rb2b.com/pricing\",\n \"Tags\": \"Hot Page, Hot Lead\",\n};\n\n// Run full agent (calls AI, writes to blob + SQLite)\nasync function testRunAgent() {\n console.log(\"Running agent...\");\n const result = await runAgent(testPayload);\n console.log(\"\\n--- Agent Result ---\");\n console.log(result);\n}\n\nasync function testInsertIdealLead() {\n const runId = Date.now();\n const output = {\n idealCustomer: true,\n reasoning: \"Test ideal lead - manually inserted for testing\",\n };\n\n // Write to SQLite\n await storeLead(runId, testPayload, output);\n\n // Write minimal blob so detail page works\n await blob.setJSON(`rb2b-lead-scores/${runId}`, {\n timestamp: runId,\n input: testPayload,\n finalOutput: JSON.stringify(output),\n });\n\n console.log(`Inserted ideal lead with run_id: ${runId}`);\n}\n// === UNCOMMENT ONE ===\nawait testRunAgent();\nawait testInsertIdealLead();","createdAt",["D",1764947592239],"branchVersion","branchId","ea5d0f16-d1ec-11f0-9552-42dde27851f2",{"_36":50,"_38":49,"_39":51,"_41":52,"_43":53,"_45":14,"_46":47,"_30":31},"main.ts","019aef13-0475-73bd-b8a8-440fc33c9390","http","import { Hono } from \"npm:hono@4.10.7\";\nimport { runAgent } from \"./agent.ts\";\nimport { app as dashboard } from \"./dashboard.tsx\";\n\nconst app = new Hono();\n\napp.post(\"/\", async (c) => {\n const data = await c.req.json();\n console.log(data);\n const url = new URL(c.req.url);\n\n // Early return + queue up processing: https://docs.val.town/vals/http/early-return/\n fetch(`${url.origin}/process`, {\n method: \"POST\",\n headers: {\n \"Content-Type\": \"application/json\",\n },\n body: JSON.stringify(data),\n });\n\n return c.json({ ok: true });\n});\n\napp.post(\"/process\", async (c) => {\n const data = await c.req.json();\n await runAgent(data);\n return c.json({ ok: true });\n});\n\napp.route(\"/\", dashboard);\n\nexport default app.fetch;",["D",1764947592239],{"_36":56,"_38":55,"_39":57,"_41":58,"_43":59,"_45":14,"_46":47,"_30":31},"digest.ts","019aef13-0475-73bd-b8a8-40e96d4df849","interval","import { email } from \"https://esm.town/v/std/email?v=11\";\nimport { getIdealLeadsSince, Lead } from \"./db.ts\";\n\nconst RECIPIENTS = [\"charlie@val.town\", \"steve@val.town\"];\n\nexport default async function sendDigest(\n interval: { lastRunAt: Date | undefined },\n) {\n const sinceTimestamp = interval.lastRunAt?.getTime() ?? 0;\n const leads = await getIdealLeadsSince(sinceTimestamp);\n\n if (leads.length === 0) {\n console.log(`[Digest] No ideal leads found since last run, skipping email`);\n return { sent: false, reason: \"No ideal leads today\" };\n }\n console.log(`[Digest] Found ${leads.length} ideal leads, sending email...`);\n\n const subject = `🎯 ${leads.length} Ideal Lead${\n leads.length !== 1 ? \"s\" : \"\"\n } Today`;\n const html = generateEmailHTML(leads);\n await email({\n to: RECIPIENTS,\n subject,\n html,\n });\n return { sent: true, leadCount: leads.length };\n}\n\nfunction generateEmailHTML(leads: Lead[]): string {\n const leadCards = leads.map((lead) => `\n

\n ${lead.first_name} ${lead.last_name} from ${lead.company_name}\n

\n Name: ${lead.first_name} ${lead.last_name}
\n Title: ${lead.title || \"N/A\"}
\n Company: ${lead.company_name || \"N/A\"}
\n Email: ${\n lead.business_email\n ? `${lead.business_email}`\n : \"N/A\"\n }
\n LinkedIn: ${\n lead.linkedin_url\n ? `${lead.linkedin_url}`\n : \"N/A\"\n }
\n Location: ${\n [lead.city, lead.state].filter(Boolean).join(\", \") || \"N/A\"\n }
\n ${\n lead.website\n ? `Website: ${lead.website}
`\n : \"\"\n }\n

\n Why they're ideal:\n

${\n lead.reasoning || \"No reasoning provided\"\n }

\n `).join(\"\");\n\n return `\n \n \n \n \n \n \n \n

🎯 Today's Ideal Leads

${leads.length} ideal customer${\n leads.length !== 1 ? \"s\" : \"\"\n } identified today

\n ${leadCards}\n

\n Sent by RB2B Lead Scorer\n

\n \n \n `;\n}",["D",1764947592239],{"_36":62,"_38":61,"_39":40,"_41":63,"_43":64,"_45":14,"_46":47,"_30":31},"db.ts","019aef13-0475-73bd-b8a8-3f231c175637","import { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\n\nconst TABLE_NAME = \"rb2b_leads_v2\";\n\nawait createTable();\n\nexport async function storeLead(\n runId: number,\n input: Record,\n output: { idealCustomer: boolean; reasoning: string },\n) {\n await sqlite.execute(\n `INSERT INTO ${TABLE_NAME} (\n run_id, linkedin_url, first_name, last_name, title, company_name,\n business_email, website, industry, employee_count, estimated_revenue,\n city, state, zipcode, seen_at, referrer, captured_url, tags,\n ideal_customer, reasoning\n ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n [\n runId,\n input[\"LinkedIn URL\"],\n input[\"First Name\"],\n input[\"Last Name\"],\n input[\"Title\"],\n input[\"Company Name\"],\n input[\"Business Email\"],\n input[\"Website\"],\n input[\"Industry\"],\n input[\"Employee Count\"],\n input[\"Estimate Revenue\"],\n input[\"City\"],\n input[\"State\"],\n input[\"Zipcode\"],\n input[\"Seen At\"],\n input[\"Referrer\"],\n input[\"Captured URL\"],\n input[\"Tags\"],\n output.idealCustomer ? 1 : 0,\n output.reasoning,\n ],\n );\n}\n\nexport interface Lead {\n run_id: number;\n first_name: string;\n last_name: string;\n title: string;\n company_name: string;\n business_email: string;\n linkedin_url: string;\n city: string;\n state: string;\n website: string;\n reasoning: string;\n}\n\nexport async function getIdealLeadsSince(\n sinceTimestamp: number,\n): Promise {\n const result = await sqlite.execute(\n `SELECT * FROM ${TABLE_NAME} \n WHERE ideal_customer = 1 \n AND run_id > ?\n ORDER BY run_id DESC`,\n [sinceTimestamp],\n );\n\n return result.rows.map((row) => {\n const obj: Record = {};\n result.columns.forEach((col, idx) => {\n obj[col] = row[idx];\n });\n return obj;\n });\n}\n\nasync function createTable() {\n await sqlite.execute(\n `CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n run_id INTEGER PRIMARY KEY,\n linkedin_url TEXT,\n first_name TEXT,\n last_name TEXT,\n title TEXT,\n company_name TEXT,\n business_email TEXT,\n website TEXT,\n industry TEXT,\n employee_count TEXT,\n estimated_revenue TEXT,\n city TEXT,\n state TEXT,\n zipcode TEXT,\n seen_at TEXT,\n referrer TEXT,\n captured_url TEXT,\n tags TEXT,\n ideal_customer INTEGER,\n reasoning TEXT\n )`,\n );\n}",["D",1764947592239],{"_36":67,"_38":66,"_39":40,"_41":68,"_43":69,"_45":14,"_46":47,"_30":31},"dashboard.tsx","019aef13-0475-73bd-b8a8-38c1abd20277","/** @jsxImportSource npm:hono@4/jsx */\nimport { Hono } from \"npm:hono@4\";\nimport { blob } from \"https://esm.town/v/std/blob\";\nimport { sqlite } from \"https://esm.town/v/stevekrouse/sqlite\";\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, isIdeal }: { lead: any; isIdeal: boolean }) {\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 {lead.firstName} {lead.lastName}\n \n ·\n \n {lead.title} @ {lead.company}\n \n {date}\n \n );\n}\n\n// List all runs - SQLite only\napp.get(\"/\", async (c) => {\n const leads: any[] = [];\n\n try {\n const result = await sqlite.execute(\n \"SELECT * FROM rb2b_leads_v2 ORDER BY run_id DESC\",\n );\n for (const row of result.rows) {\n const columns = result.columns;\n const rowObj: Record = {};\n columns.forEach((col, idx) => {\n rowObj[col] = row[idx];\n });\n\n const runId = rowObj.run_id;\n const timestamp = runId;\n\n leads.push({\n runId,\n timestamp,\n firstName: rowObj.first_name || \"Unknown\",\n lastName: rowObj.last_name || \"\",\n title: rowObj.title || \"Unknown\",\n company: rowObj.company_name || \"Unknown\",\n idealCustomer: rowObj.ideal_customer === 1,\n });\n }\n } catch (e) {\n // Table doesn't exist yet - that's fine\n }\n\n const ideal = leads.filter((l) => l.idealCustomer);\n const nonIdeal = leads.filter((l) => !l.idealCustomer);\n const totalIdeal = ideal.length;\n\n return c.html(\n \n

RB2B Lead Scorer

\n {leads.length} leads · {totalIdeal} ideal customers\n

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

\n No leads yet. Trigger the webhook to see results here.\n

\n )\n : (\n

\n {ideal.map((lead) => )}\n\n {nonIdeal.length > 0 && (\n

\n \n \n {nonIdeal.length} non-ideal{\" \"}\n {nonIdeal.length === 1 ? \"lead\" : \"leads\"}\n \n ▼\n \n

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

\n )}\n\n {ideal.length === 0 && nonIdeal.length === 0 && (\n

\n No leads yet\n

\n )}\n

\n ,\n );\n});\n\n// View specific run details - uses blob\napp.get(\"/run/:runId\", async (c) => {\n const runId = c.req.param(\"runId\");\n\n const runData = await blob.getJSON(`rb2b-lead-scores/${runId}`);\n\n if (!runData) {\n return c.html(\n \n

Run Not Found

\n The requested run could not be found.\n

\n \n ← Back to dashboard\n \n

\n ,\n 404,\n );\n }\n\n // Get SQLite row if exists\n let sqlRow: Record | null = null;\n try {\n const sqlResult = await sqlite.execute(\n \"SELECT * FROM rb2b_leads_v2 WHERE run_id = ?\",\n [runId],\n );\n if (sqlResult.rows.length > 0) {\n const columns = sqlResult.columns;\n const row = sqlResult.rows[0];\n sqlRow = {};\n columns.forEach((col, idx) => {\n sqlRow![col] = row[idx];\n });\n }\n } catch (e) {\n // Table might not exist\n }\n\n const output = runData.finalOutput ? JSON.parse(runData.finalOutput) : null;\n const input = runData.input || {};\n\n return c.html(\n \n

\n \n ← Back to dashboard\n \n\n

\n {input[\"First Name\"] || sqlRow?.first_name || \"Unknown\"}{\" \"}\n {input[\"Last Name\"] || sqlRow?.last_name || \"\"}\n

\n {input[\"Title\"] || sqlRow?.title || \"Unknown\"} @{\" \"}\n {input[\"Company Name\"] || sqlRow?.company_name || \"Unknown\"}\n

\n {new Date(parseInt(runId)).toLocaleString()}\n

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

\n \n \n {output?.idealCustomer ? \"Ideal Customer\" : \"Not Ideal Customer\"}\n \n

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

\n\n {/* Input Data */}\n

\n Input Data\n

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

{key}

{String(value || \"\")}

\n\n {/* SQL Row if exists */}\n {sqlRow && (\n

\n SQLite Row\n

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

{key}

\n {String(value ?? \"\")}\n

\n )}\n\n {/* Full Blob Data */}\n

\n Full Blob Data (debug)\n

\n            {JSON.stringify(runData, null, 2)}\n

\n \n ,\n );\n});\n\nexport default app.fetch;",["D",1764947592239],{"_36":72,"_38":71,"_39":40,"_41":73,"_43":74,"_45":14,"_46":47,"_30":31},"agent.ts","019aef13-0475-73bd-b8a8-37937ff115f7","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-5.1-2025-11-13\",\n tools: [webSearchTool()],\n instructions: PROMPT,\n});\n\nexport async function runAgent(data) {\n const runId = Date.now();\n\n const result = await run(agent, JSON.stringify(data));\n\n // Full debug to blob\n await blob.setJSON(`rb2b-lead-scores/${runId}`, {\n timestamp: runId,\n input: data,\n fullResult: result,\n finalOutput: result.finalOutput,\n });\n\n const output = JSON.parse(result.finalOutput);\n await storeLead(runId, data, output);\n\n console.log(`/rb2b-lead-scores/${runId}`);\n console.log(result.finalOutput);\n\n return output;\n}",["D",1764947592239],{"_36":77,"_38":76,"_39":27,"_41":78,"_43":79,"_45":14,"_46":47,"_30":31},"README.md","019aef13-0475-73bd-b8a8-30e1b7528a82","# RB2B Lead Filter\n\nConnect this val to RB2B for an AI-powered digest of your most qualified leads.\n\n\n\n## Getting started\n\n1. Click **Remix**\n2. Set `OPENAI_API_KEY` in this val's environment variables\n3. Copy the HTTP endpoint for [`main.ts`](./main.ts) into\n https://app.rb2b.com/integrations/webhook\n4. Customize [`PROMPT.txt`](./PROMPT.txt) with instructions for how to properly\n research if a lead represents an ideal customer, and anything you want the\n agent to include in its reasoning. (Don't change how it structures its final\n response).\n5. That's it! The owner of this val will now receive a daily email of only your\n most qualified RB2B leads at 8am PST.\n\n## How it works\n\n- Once you've added your val's HTTP endpoint to\n https://app.rb2b.com/integrations/webhook, RB2B will begin forwarding every\n new lead to this val.\n- When a new lead comes in from RB2B, it is forwarded along with the\n instructions in [`PROMPT.txt`](./PROMPT.txt) to an OpenAI agent. The agent\n uses its reasoning and web search tool to determine if the lead represents an\n `idealCustomer` and explains its `reasoning`.\n- The RB2B data and agent results are saved in the `rb2b_leads_v2` sqlite table,\n and the agent's entire run history is saved in blob storage.\n- The [`main.ts`](./main.ts) dashboard shows a history of all runs, ideal\n customers first. Clicking any lead will take you to its `runId` page, where\n you can view the agent's reasoning as well as all sqlite and blob data from\n the entire process (this is what is included when an `idealCustomer` is added\n to the email digest):\n\n\n\n- [`digest.ts`](./digest.ts) runs every day at 8am PST by default.\n- Feel free to change the timing and frequency of the [`digest.ts`](./digest.ts)\n cron. It always checks when it was last run and sends every new\n `idealCustomer` to the owner of this val (and any additional email addresses\n included in the `recipients` array).",["D",1764947592239],{"_36":82,"_38":81,"_39":27,"_41":83,"_43":84,"_45":14,"_46":47,"_30":31},"PROMPT.txt","019aef13-0475-73bd-b8a8-2d95735de41a","You are an assistant to the CEO of Val Town.\n\nVal Town is like Zapier for people who know how to code, a tool for writing code and getting it running in the cloud,\nparticularly useful for lightweight automations in technical teams.\n\nI'm sending you data about website visitors and it's your job to exhuastively research the person by visiting their \nlinks, finding their personal and company sites, blogs they've written, etc to determine if they are in Val Town's \nideal customer profile.\n\nVal Town's ideal customer profile:\n\n1. Founder\n2. B2B SaaS Startup\n3. Seed-stage (approximately)\n4. They know how to code\n\nReturn your final response in JSON only with the following schema:\n\n{\n idealCustomer: boolean;\n reasoning: string;\n}",["D",1764947592239],"id","ea59b7ee-d1ec-11f0-9552-42dde27851f2","rb2b",["D",1764947592239],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","Find ICP customers who visit our 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Diff · v1