[{"_1":2,"_3":-5,"_4":-5},"loaderData",{"_5":6,"_7":8},"actionData","errors","root",{"_101":102,"_103":104},"routes/embed.x.$handle.$name.$",{"_9":10,"_11":12,"_13":14,"_15":16,"_17":18,"_19":20,"_21":-5},"handle","samy","name","bison-reply-agent","path","callprep.ts","project",{"_22":45,"_11":12,"_33":46,"_47":-5,"_48":42,"_49":50,"_51":50,"_52":-5,"_53":-5,"_54":55,"_56":-5,"_57":42,"_58":-5,"_59":-5,"_60":61,"_62":63,"_64":-5,"_65":-5,"_66":-5,"_67":-5,"_68":69,"_70":69,"_71":72,"_73":72,"_74":72,"_75":69,"_76":69,"_77":78,"_79":80,"_81":82,"_83":42},"file",{"_22":23,"_11":14,"_24":25,"_26":-5,"_27":28,"_29":30,"_31":32,"_33":34,"_35":36,"_37":38,"_39":40,"_41":42,"_43":-5,"_13":44},"permalink","https://www.val.town/x/samy/bison-reply-agent/code/callprep.ts","extension","id","17104274-9f3d-499b-a47f-cbcf8f8c8e00","fileId","e1685a74-86e5-11f1-b50c-1607ee4eb77e","parentId","branchId","54481d2d-a3f3-4dfa-ab51-1abb2a0d7de9","branchVersion",91,"latest",true,"createdAt",["D",1784944420416],"version",1,"fileType","script","content","// Call-prep alert for EVERY interested reply (2026-07-23). Sam calls all\n// positive replies now, so the notification is his call-prep sheet: best\n// number to dial (labeled personal vs office), the decisionmaker (extracted\n// name when the replier IS one, otherwise researched off the practice\n// website), reply time in PT, offer, their message, and their timezone.\n// Everything degrades to a labeled fallback - the alert must never be lost.\n// No sqlite/email imports here: webhook.ts sends and logs; this file only\n// builds, so it stays offline-testable and under Val.town's 80k file cap.\nimport type { Analysis } from \"./analysis.ts\";\nimport {\n claudeExtract,\n leadVar,\n normalizePhone,\n stripHtml,\n websiteFromLead,\n websiteIntel,\n} from \"./crm.ts\";\n\n// ---------- decisionmaker research (one site fetch chain + one Claude call) ----------\n\ntype Decisionmaker = { name: string; role: string };\n\n// Flat fields on purpose: a nested array here made the model occasionally\n// return the whole payload as a JSON string in one property.\nconst DM_TOOL = {\n name: \"submit_decisionmakers\",\n description: \"Submit the likely decisionmakers found for this dental practice.\",\n input_schema: {\n type: \"object\",\n properties: {\n dm1_name: { type: \"string\", description: \"Most likely decisionmaker's full name, 'Dr.'-prefixed when a doctor. Omit if none found - never invent.\" },\n dm1_role: { type: \"string\", description: \"Their short lowercase role, e.g. 'principal dentist', 'office manager'\" },\n dm2_name: { type: \"string\", description: \"Second candidate's full name, only when the site clearly names one\" },\n dm2_role: { type: \"string\", description: \"Second candidate's short lowercase role\" },\n evidence: { type: \"string\", description: \"One short sentence on where the names came from\" },\n },\n required: [\"evidence\"],\n },\n};\n\nasync function fetchPage(url: string): Promise {\n const resp = await fetch(url, {\n headers: { \"User-Agent\": \"Mozilla/5.0 (compatible; LuminaBot)\" },\n signal: AbortSignal.timeout(8_000),\n });\n if (!resp.ok) throw new Error(`fetch ${url} -> ${resp.status}`);\n return (await resp.text()).slice(0, 300_000);\n}\n\n// Team/about/doctor pages usually hold the names the homepage doesn't.\nfunction teamLinks(homeHtml: string, site: string): string[] {\n const base = new URL(site);\n const seen = new Set();\n for (const m of homeHtml.matchAll(/href=[\"']([^\"'#?]+)[\"']/gi)) {\n let u: URL;\n try {\n u = new URL(m[1], base);\n } catch {\n continue;\n }\n if (u.host !== base.host) continue;\n if (/\\.(png|jpe?g|gif|svg|ico|css|js|xml|pdf|webp)$/i.test(u.pathname)) continue;\n if (!/about|team|staff|meet|doctor|dentist|provider|our-practice|who-we-are/i.test(u.pathname)) continue;\n seen.add(u.href);\n if (seen.size >= 2) break;\n }\n return [...seen];\n}\n\nconst dmCache = new Map>();\n\nfunction researchDecisionmakers(site: string | null, hints: string): Promise<{ people: Decisionmaker[]; evidence?: string } | null> {\n if (!site) return Promise.resolve(null);\n if (!dmCache.has(site)) {\n if (dmCache.size > 100) dmCache.clear();\n dmCache.set(\n site,\n (async () => {\n const homeHtml = await fetchPage(site);\n const subpages = await Promise.all(\n teamLinks(homeHtml, site).map((u) => fetchPage(u).catch(() => \"\")),\n );\n const text = [\n `HOMEPAGE (${site}):\\n${stripHtml(homeHtml).slice(0, 4000)}`,\n ...subpages.filter(Boolean).map((h, i) => `SUBPAGE ${i + 1}:\\n${stripHtml(h).slice(0, 3000)}`),\n ].join(\"\\n\\n\");\n const out = await claudeExtract(\n \"Identify who most likely DECIDES on marketing spend at this dental practice: \" +\n \"the principal/owner dentist, office manager, practice manager, or operations manager. \" +\n \"Use the website text plus the context clues. Return up to 2 real named people \" +\n \"(most likely first) - never invent names, and skip generic staff (front desk, hygienists, associates).\",\n `${hints}\\n\\n${text}`,\n DM_TOOL,\n );\n const junk = /^(unknown|none|n\\/a|not (provided|found|named))$/i;\n const people: Decisionmaker[] = [\n { name: String(out.dm1_name ?? \"\").trim(), role: String(out.dm1_role ?? \"\").trim() },\n { name: String(out.dm2_name ?? \"\").trim(), role: String(out.dm2_role ?? \"\").trim() },\n ].filter((p) => p.name && p.role && !junk.test(p.name));\n return { people, evidence: out.evidence };\n })().catch((e) => {\n console.error(\"decisionmaker research failed:\", e);\n dmCache.delete(site); // don't cache transient failures\n return null;\n }),\n );\n }\n return dmCache.get(site)!;\n}\n\n// ---------- practice discovery (web search, for leads with no website) ----------\n// BookYourData-style leads are dentists' PERSONAL emails: no website var, no\n// office domain to derive one from. But they carry name + practice + street\n// address, which is enough for one web-search call to find the official site\n// (and often the office email/phone). The found site then feeds the normal\n// intel + decisionmaker pipeline.\n\nexport type DiscoveredPractice = {\n website?: string;\n office_email?: string;\n office_phone?: string;\n practice_name?: string;\n confidence?: string;\n evidence?: string;\n};\n\n// Flat fields on purpose - same sonnet nested-payload gotcha as DM_TOOL.\nconst PRACTICE_TOOL = {\n name: \"submit_practice\",\n description: \"Submit what you found about this dentist's practice. Omit any field you could not verify - never invent.\",\n input_schema: {\n type: \"object\",\n properties: {\n website: { type: \"string\", description: \"Official practice website URL, only if confident it is THIS dentist's practice (name + city/state match)\" },\n office_email: { type: \"string\", description: \"The practice's office/front-desk email if seen (e.g. on their website or a listing)\" },\n office_phone: { type: \"string\", description: \"The practice's office phone number if seen\" },\n practice_name: { type: \"string\", description: \"Official practice name\" },\n confidence: { type: \"string\", enum: [\"high\", \"medium\", \"low\"], description: \"How sure you are this is the right practice\" },\n evidence: { type: \"string\", description: \"One short sentence on how you matched it\" },\n },\n required: [\"evidence\"],\n },\n};\n\nconst discoveryCache = new Map>();\n\nexport function discoverPractice(lead: any, analysis: Analysis): Promise {\n const key = String(lead?.email ?? \"\").toLowerCase();\n if (!key) return Promise.resolve(null);\n if (!discoveryCache.has(key)) {\n if (discoveryCache.size > 100) discoveryCache.clear();\n discoveryCache.set(\n key,\n runDiscovery(lead, analysis).catch((e) => {\n console.error(\"practice discovery failed:\", e);\n discoveryCache.delete(key); // don't cache transient failures\n return null;\n }),\n );\n }\n return discoveryCache.get(key)!;\n}\n\nasync function runDiscovery(lead: any, analysis: Analysis): Promise {\n const facts = [\n `Dentist: ${analysis.prospect_full_name ?? lead.first_name ?? \"?\"}${lead.last_name ? ` ${lead.last_name}` : \"\"}`,\n `Company field on the lead: ${lead.company ?? \"?\"} (often the dentist's own name, sometimes the practice name)`,\n `Practice name if known: ${analysis.clinic_name ?? \"?\"}`,\n `Address: ${[leadVar(lead, \"address\"), leadVar(lead, \"city\"), leadVar(lead, \"state\")].filter(Boolean).join(\", \") || \"?\"}`,\n `Their personal email: ${lead.email ?? \"?\"} (the handle sometimes hints at the practice name)`,\n ].join(\"\\n\");\n const tools = [\n { type: \"web_search_20260209\", name: \"web_search\", max_uses: 3 },\n { type: \"web_fetch_20260209\", name: \"web_fetch\", max_uses: 2 },\n PRACTICE_TOOL,\n ];\n const messages: any[] = [{\n role: \"user\",\n content: `Find the OFFICIAL website of this US dentist's practice, plus the office email and office phone if you can (their contact page usually has both).\\n\\n${facts}\\n\\nSearch for the dentist by name with their city/state (and the address if needed). Verify the site actually belongs to THIS dentist - the name and location must match; dentists share names. When done, call submit_practice with what you verified. If you cannot find their practice, call submit_practice with just evidence explaining why.`,\n }];\n // Server tools run in a server-side loop that can pause; resend to resume.\n // Hard overall deadline: this runs BEFORE the reply is drafted and sent, so\n // it must never eat the val's run budget - a lost discovery just degrades\n // the alert.\n const deadline = Date.now() + 150_000;\n for (let round = 0; round < 3; round++) {\n const remaining = deadline - Date.now();\n if (remaining < 10_000) return null;\n const resp = await fetch(\"https://api.anthropic.com/v1/messages\", {\n method: \"POST\",\n headers: {\n \"x-api-key\": Deno.env.get(\"ANTHROPIC_API_KEY\") ?? \"\",\n \"anthropic-version\": \"2023-06-01\",\n \"content-type\": \"application/json\",\n },\n body: JSON.stringify({ model: \"claude-sonnet-5\", max_tokens: 3000, tools, messages }),\n signal: AbortSignal.timeout(Math.min(130_000, remaining)),\n });\n if (!resp.ok) throw new Error(`anthropic ${resp.status}: ${await resp.text()}`);\n const data = await resp.json();\n const submit = (data.content ?? []).find(\n (b: any) => b.type === \"tool_use\" && b.name === \"submit_practice\",\n );\n if (submit) {\n const out = submit.input ?? {};\n const clean = (v: any) => {\n const s = String(v ?? \"\").trim();\n return s && !/^(unknown|none|n\\/a|not found)$/i.test(s) ? s : undefined;\n };\n const website = clean(out.website);\n return {\n website: website && !website.startsWith(\"http\") ? `https://${website}` : website,\n office_email: clean(out.office_email)?.toLowerCase(),\n office_phone: clean(out.office_phone),\n practice_name: clean(out.practice_name),\n confidence: clean(out.confidence),\n evidence: clean(out.evidence),\n };\n }\n if (data.stop_reason === \"pause_turn\") {\n messages.push({ role: \"assistant\", content: data.content });\n continue;\n }\n return null; // ended without submitting - treat as not found\n }\n return null;\n}\n\n// ---------- formatting helpers ----------\n\nexport function fmtPhone(raw: string): string {\n const d = normalizePhone(raw);\n return d ? `(${d.slice(0, 3)}) ${d.slice(3, 6)}-${d.slice(6)}` : String(raw).trim();\n}\n\n// Sam's call-script format: \"Dr. \" for doctors, first name otherwise.\nexport function scriptName(name: string): string {\n const tokens = name.trim().replace(/,.*$/, \"\").split(/\\s+/).filter(Boolean);\n if (!tokens.length) return name.trim();\n if (/^dr\\.?$/i.test(tokens[0])) {\n return `Dr. ${tokens[tokens.length - 1] === tokens[0] ? name.trim() : tokens[tokens.length - 1]}`;\n }\n return tokens[0];\n}\n\n// Reply time in Sam's timezone: time, date, day of week.\nexport function whenInPT(iso?: string): string {\n const d = iso && !isNaN(Date.parse(iso)) ? new Date(iso) : new Date();\n const time = d.toLocaleString(\"en-US\", {\n timeZone: \"America/Los_Angeles\", hour: \"numeric\", minute: \"2-digit\", timeZoneName: \"short\",\n });\n const date = d.toLocaleString(\"en-US\", {\n timeZone: \"America/Los_Angeles\", weekday: \"long\", month: \"long\", day: \"numeric\", year: \"numeric\",\n });\n return `${time} - ${date}`;\n}\n\nfunction localClock(tz: string): string | null {\n try {\n return new Date().toLocaleString(\"en-US\", { timeZone: tz, hour: \"numeric\", minute: \"2-digit\" });\n } catch {\n return null; // model handed back a non-IANA string\n }\n}\n\n// Their message without the quoted thread under it (fall back to the full\n// text if stripping would leave nothing).\nexport function freshMessage(reply: any): string {\n const full = String(reply?.text_body ?? stripHtml(String(reply?.html_body ?? \"\"))).trim();\n // Gmail wraps the \"On ... wrote:\" attribution across lines - match lazily\n // across newlines up to the first \"wrote:\" at an end of line.\n let cut = full.replace(/^\\s*On [\\s\\S]{0,300}?wrote:\\s*$[\\s\\S]*/m, \"\");\n cut = cut.split(\"\\n\").filter((l) => !l.startsWith(\">\")).join(\"\\n\").trim();\n return cut.length >= 2 ? cut : full;\n}\n\n// ---------- the alert ----------\n\nexport type CallPrepInput = {\n analysis: Analysis;\n lead: any;\n reply: any;\n leadLabel: string;\n senderEmail?: string;\n senderName?: string;\n};\n\nexport async function buildCallPrep(input: CallPrepInput): Promise<{ subject: string; text: string; detail: string }> {\n const { analysis, lead, reply, leadLabel } = input;\n const siteOnFile = websiteFromLead(lead);\n // No website on file = a personal-email lead (the BookYourData lists) - go\n // find the practice on the web from name + address before building the sheet.\n const discovered = siteOnFile ? null : await discoverPractice(lead, analysis).catch(() => null);\n const site = siteOnFile ?? discovered?.website ?? null;\n const siteNote = siteOnFile || !site ? \"\" : \" (found via web search - verify)\";\n // Cached from the CRM sync moments earlier when the site is on file.\n const intel = site ? await websiteIntel(lead, site).catch(() => null) : null;\n const sitePhones = intel?.phones ?? [];\n const leadMobile = leadVar(lead, \"phone\");\n const leadMobileDigits = normalizePhone(leadMobile);\n\n // Best number: their own number from the reply beats anything; a match\n // against the website's line(s) is the strongest personal-vs-office signal,\n // the model's signature read backs it up; website office line is the fallback.\n const replyDigits = normalizePhone(analysis.phone_number ?? \"\");\n let phoneLine: string;\n let phoneKind: string;\n if (analysis.phone_number) {\n if (replyDigits && sitePhones.includes(replyDigits)) {\n phoneKind = \"office\";\n phoneLine = `${fmtPhone(analysis.phone_number)} - OFFICE (same number as their website)`;\n } else if (replyDigits && sitePhones.length) {\n phoneKind = \"personal\";\n phoneLine = `${fmtPhone(analysis.phone_number)} - PERSONAL/DIRECT (differs from their website's ${sitePhones.map(fmtPhone).join(\", \")})`;\n } else if (analysis.phone_number_type && analysis.phone_number_type !== \"unknown\") {\n phoneKind = analysis.phone_number_type;\n phoneLine = `${fmtPhone(analysis.phone_number)} - ${analysis.phone_number_type.toUpperCase()}` +\n (analysis.phone_number_evidence ? ` (${analysis.phone_number_evidence})` : \" (from their reply)\");\n } else {\n phoneKind = \"unknown type\";\n phoneLine = `${fmtPhone(analysis.phone_number)} - from their reply, type unknown (nothing on their website to compare)`;\n }\n if (leadMobileDigits && leadMobileDigits !== replyDigits) {\n phoneLine += ` (also on file: ${fmtPhone(leadMobile)}, mobile from our lead list)`;\n }\n } else if (leadMobileDigits) {\n phoneKind = \"mobile (lead list)\";\n phoneLine = `${fmtPhone(leadMobile)} - MOBILE from our lead list (no number in their reply)`;\n const office = sitePhones[0] ?? (discovered?.office_phone ? normalizePhone(discovered.office_phone) : \"\");\n if (office && office !== leadMobileDigits) {\n phoneLine += ` (office: ${fmtPhone(office)}${sitePhones[0] ? \"\" : \" - via web search, verify\"})`;\n }\n } else if (sitePhones.length) {\n phoneKind = \"office (website)\";\n phoneLine = `${fmtPhone(sitePhones[0])} - OFFICE line from their website${siteNote} (no number in their reply)`;\n } else if (discovered?.office_phone) {\n phoneKind = \"office (web search)\";\n phoneLine = `${fmtPhone(discovered.office_phone)} - OFFICE, found via web search (verify)`;\n } else {\n phoneKind = \"none\";\n phoneLine = `none found - no number in their reply or on their website${site ? \"\" : \" (no website found)\"}`;\n }\n\n // Decisionmaker: use the replier's name when the model judged them to BE\n // one; otherwise research the website for two candidates.\n const replierName = analysis.prospect_full_name ?? analysis.prospect_first_name;\n const dmLines: string[] = [];\n let dmDetail: string;\n const leadName = String(lead.first_name ?? \"\").trim();\n // Personal-email lists (BookYourData) put the dentist's own name on the\n // lead - the inbox owner IS the decisionmaker, no research needed.\n const leadIsDentist = !siteOnFile && /^dr\\.?\\s/i.test(leadName);\n if (replierName && analysis.replier_is_decisionmaker === true) {\n dmLines.push(`Decisionmaker: ${scriptName(replierName)} (replied themselves${analysis.prospect_full_name ? ` - ${analysis.prospect_full_name}` : \"\"})`);\n dmDetail = `dm=${scriptName(replierName)}`;\n } else if (leadIsDentist && !replierName) {\n dmLines.push(`Decisionmaker: ${scriptName(leadName)}${lead.company ? ` (${lead.company})` : \"\"} - this lead is the dentist's personal email, so you're likely talking to them directly`);\n dmDetail = `dm=${scriptName(leadName)} (lead record)`;\n } else {\n const hints = [\n `Practice: ${analysis.clinic_name ?? lead.company ?? leadVar(lead, \"clinic\") ?? \"?\"}`,\n `Location: ${[leadVar(lead, \"city\"), leadVar(lead, \"state\")].filter(Boolean).join(\", \") || \"?\"}`,\n `Lead label: ${leadLabel}`,\n `The reply came from: ${reply.from_name ?? \"?\"} <${reply.from_email_address ?? \"?\"}>` +\n (replierName ? ` - signed \"${replierName}\", who reads as staff rather than the decisionmaker` : \" - no personal name found\"),\n `Their reply (for signature clues): ${freshMessage(reply).slice(0, 600)}`,\n ].join(\"\\n\");\n const research = await researchDecisionmakers(site, hints);\n if (research?.people.length) {\n research.people.forEach((p, i) => dmLines.push(`Decisionmaker #${i + 1}: ${p.name}, ${p.role}`));\n if (research.people.length === 1) dmLines.push(`(only one clear candidate on their site)`);\n if (research.evidence) dmLines.push(`(source: ${research.evidence})`);\n dmDetail = `dm researched: ${research.people.map((p) => p.name).join(\" / \")}`;\n } else if (leadIsDentist) {\n dmLines.push(`Decisionmaker: ${scriptName(leadName)}${lead.company ? ` (${lead.company})` : \"\"} - this lead is the dentist's personal email, so you're likely talking to them directly`);\n dmDetail = `dm=${scriptName(leadName)} (lead record)`;\n } else {\n dmLines.push(`Decisionmaker: unknown - couldn't find one on their website${site ? ` (${site})` : \" (no website found)\"}`);\n dmDetail = \"dm unknown\";\n }\n if (replierName) dmLines.push(`(reply was signed by ${replierName} - reads as staff, not the decisionmaker)`);\n }\n\n // Office email: scraped from the site when we have one, else whatever web\n // search surfaced. The lead/reply addresses themselves don't count.\n const ownEmails = new Set(\n [lead.email, reply.from_email_address].filter(Boolean).map((s: any) => String(s).toLowerCase()),\n );\n let siteHost = \"\";\n try {\n siteHost = site ? new URL(site).hostname.replace(/^www\\./, \"\") : \"\";\n } catch { /* malformed site string */ }\n const scrapedAll = (intel?.emails ?? []).filter((e) => !ownEmails.has(e));\n // A page can carry the web designer's or a vendor's address - the practice's\n // own domain wins when present.\n const sameDomain = siteHost ? scrapedAll.filter((e) => e.endsWith(`@${siteHost}`)) : [];\n const scraped = sameDomain.length ? sameDomain : scrapedAll;\n const searched = discovered?.office_email && !ownEmails.has(discovered.office_email) ? [discovered.office_email] : [];\n let officeEmailLine: string | null = null;\n if (scraped.length) {\n officeEmailLine = `Office email: ${scraped.slice(0, 2).join(\", \")} (from their website${siteNote})`;\n } else if (searched.length) {\n officeEmailLine = `Office email: ${searched[0]} (found via web search - verify)`;\n } else if (!siteOnFile) {\n officeEmailLine = `Office email: none found`;\n }\n\n const offer = analysis.original_offer ||\n [leadVar(lead, \"treatment number\"), leadVar(lead, \"treatment type\"), leadVar(lead, \"treatment suffix\")]\n .filter(Boolean).join(\" \") || \"(unknown - check the thread in Bison)\";\n\n const fromLine = `${reply.from_name ?? \"\"} <${reply.from_email_address ?? lead.email ?? \"?\"}>`.trim() +\n (reply.from_email_address && lead.email && reply.from_email_address.toLowerCase() !== lead.email.toLowerCase()\n ? ` (lead email: ${lead.email})`\n : \"\");\n\n const tz = analysis.timezone ?? intel?.timezone;\n const clock = tz ? localClock(tz) : null;\n const tzLine = tz\n ? `${tz}${clock ? ` - their local time right now: ${clock}` : \"\"}`\n : \"unknown\";\n\n const text = [\n `CALL PREP`,\n `Best number: ${phoneLine}`,\n ...(officeEmailLine ? [officeEmailLine] : []),\n ...dmLines,\n `Replied: ${whenInPT(reply.date_received ?? reply.created_at)}`,\n `Offer: ${offer}`,\n ``,\n `THEIR MESSAGE`,\n `-------------`,\n freshMessage(reply),\n ``,\n `Subject line: ${String(reply.email_subject ?? \"\").replace(/^\\s*((re|fwd?|fw)\\s*:\\s*)+/i, \"\").trim() || \"?\"}`,\n `Sender email: ${fromLine}`,\n `Their timezone: ${tzLine}`,\n ``,\n `CONTEXT`,\n `Clinic: ${intel?.clinicName ?? discovered?.practice_name ?? analysis.clinic_name ?? lead.company ?? \"?\"}`,\n `Website: ${site ? site + siteNote : \"none found\"}`,\n ...(discovered?.evidence ? [`(web search match: ${discovered.evidence}${discovered.confidence ? `, confidence ${discovered.confidence}` : \"\"})`] : []),\n `Location: ${[leadVar(lead, \"city\"), leadVar(lead, \"state\")].filter(Boolean).join(\", \") || \"?\"}`,\n `Our sender: ${input.senderEmail ?? \"?\"} (persona: ${input.senderName ?? \"?\"})`,\n ``,\n `The AI is still handling the email reply as usual - this is your heads-up to call.`,\n ].join(\"\\n\");\n\n return {\n subject: `Interested - call prep: ${leadLabel}`,\n text,\n detail: `phone=${analysis.phone_number ?? (leadMobileDigits ? `lead:${leadMobileDigits}` : sitePhones[0] ? `site:${sitePhones[0]}` : \"none\")} (${phoneKind}); ${dmDetail}; site=${siteOnFile ? \"on file\" : discovered?.website ? \"discovered\" : \"none\"}`,\n };\n}\n","deleted",false,"label",[14],"e3dafc71-738c-40fe-ab70-9c5ae76a5d02",["D",1783490909384],"deletedAt","legacyEnvVars","privacy","public","httpPrivacy","description","imageUrl","userId","352b7b81-2d40-4ef8-babc-d1dd56767822","pinnedFileId","pinPreview","pinMigrated","screenshotVersion","likeCount",0,"orgId","019f404e-e73e-709b-8be4-84c9207a4140","tursoName","tursoHostname","tursoMeasuredAt","pinned","userPerm","r","valPerm","blobPerm","rw","emailPerm","sqlitePerm","projectPerm","telemetryPerm","user",{"_9":10,"_100":95},"org",{"_9":10,"_94":95,"_96":95,"_54":55,"_97":98,"_99":42},"branch",{"_35":84,"_11":85,"_22":28,"_86":45,"_87":-5,"_88":-5,"_89":-5,"_90":-5,"_91":-5,"_92":12,"_93":10},"isOwned",97,"main","projectId","forkedBranchId","forkedBranchVersion","forkedProjectPrivacy","forkedProjectId","forkedProjectOrgId","projectName","userHandle","displayName","","avatar","tier","free","canRestrictVals","profileImageUrl","ctx",{"_77":-5,"_134":135,"_136":137,"_138":139,"_140":42,"_141":42,"_142":42,"_143":32,"_144":-5,"_145":-7,"_146":-7,"_147":61,"_148":42,"_149":42,"_150":-5,"_151":42,"_152":42,"_153":42,"_154":-5},"ENV",{"_105":106,"_107":108,"_109":85,"_110":111,"_112":113,"_114":115,"_116":117,"_118":119,"_120":121,"_122":123,"_124":125,"_126":127,"_128":129,"_130":131,"_132":133},"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","orgs",[],"preferencesKeybindings","default","preferencesTheme","light","preferencesFixers","preferencesCopilot","preferencesSelectionAi","preferencesCloseBrackets","preferencesChatPanelState","preferencesDprint","preferencesDenofmt","notificationCount","flagDenols","isBusinessOrgMember","businessOrgHandle","isBusinessOrgAdmin","isHigherTownieTier","navCollapsed","currentOrgId"]