\n \n

AI Features Disabled

\n Add OPENAI_API_KEY to enable AI-powered persona detection, HXC profiles, and smart recommendations. \n PMF scoring works without it.\n

\n {hasResponses && (\n

\n After adding your API key, POST to /reprocess to analyze existing responses.\n

\n )}\n

\n );\n}\n\nfunction PMFScoreCard({\n score,\n label,\n benchmark = 40,\n}: {\n score: number;\n label: string;\n benchmark?: number;\n}) {\n const isGood = score >= benchmark;\n const color = isGood ? \"green\" : score >= benchmark * 0.75 ? \"yellow\" : \"red\";\n const bgColors: Record = {\n green: \"bg-green-50 border-green-200\",\n yellow: \"bg-yellow-50 border-yellow-200\",\n red: \"bg-red-50 border-red-200\",\n };\n const textColors: Record = {\n green: \"text-green-700\",\n yellow: \"text-yellow-700\",\n red: \"text-red-700\",\n };\n\n return (\n

{label}

{score.toFixed(1)}%

\n Benchmark: {benchmark}%{\" \"}\n {isGood ? (\n ✓ Above\n ) : (\n Below\n )}\n

\n );\n}\n\nfunction StatCard({ value, label }: { value: number | string; label: string }) {\n return (\n

{label}

{value}

\n );\n}\n\nfunction ResponseBreakdown({\n very,\n somewhat,\n not,\n total,\n}: {\n very: number;\n somewhat: number;\n not: number;\n total: number;\n}) {\n const veryPct = total > 0 ? (very / total) * 100 : 0;\n const somewhatPct = total > 0 ? (somewhat / total) * 100 : 0;\n const notPct = total > 0 ? (not / total) * 100 : 0;\n\n return (\n

Response Breakdown

\n Very Disappointed\n \n {very} ({veryPct.toFixed(1)}%)\n \n

\n Somewhat Disappointed\n \n {somewhat} ({somewhatPct.toFixed(1)}%)\n \n

\n Not Disappointed\n \n {not} ({notPct.toFixed(1)}%)\n \n

\n );\n}\n\nfunction WordCloud({ words, title }: { words: string[]; title: string }) {\n if (words.length === 0) {\n return (\n

{title}

No data yet

\n );\n }\n\n return (\n

{title}

\n {words.map((word, i) => {\n const sizes = [\"text-lg\", \"text-base\", \"text-sm\"];\n const size = sizes[Math.min(i, sizes.length - 1)];\n return (\n \n {word}\n \n );\n })}\n

\n );\n}\n\nfunction RoadmapSection({\n items,\n title,\n description,\n color,\n}: {\n items: string[];\n title: string;\n description: string;\n color: \"green\" | \"blue\";\n}) {\n const colors = {\n green: {\n bg: \"bg-green-50\",\n border: \"border-green-200\",\n bullet: \"bg-green-500\",\n text: \"text-green-800\",\n },\n blue: {\n bg: \"bg-blue-50\",\n border: \"border-blue-200\",\n bullet: \"bg-blue-500\",\n text: \"text-blue-800\",\n },\n };\n const c = colors[color];\n\n return (\n

{title}

{description}

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

No recommendations yet

\n ) : (\n

\n \n {item}\n

\n )}\n

\n );\n}\n\nfunction ResponseRow({ response }: { response: SurveyResponse }) {\n const colors: Record = {\n very: { bg: \"bg-green-500\", text: \"text-green-700\" },\n somewhat: { bg: \"bg-yellow-500\", text: \"text-yellow-700\" },\n not: { bg: \"bg-gray-400\", text: \"text-gray-500\" },\n };\n const c = colors[response.disappointment];\n const date = new Date(response.timestamp).toLocaleDateString(\"en-US\", {\n month: \"short\",\n day: \"numeric\",\n year: \"numeric\",\n });\n\n return (\n \n \n \n {response.persona || \"Unprocessed\"}\n \n {response.disappointment}\n {date}\n \n );\n}\n\napp.get(\"/dashboard\", async (c) => {\n const responses = await getAllResponses();\n const counts = await getResponseCounts();\n const insights = await getLatestInsights();\n const surveyUrl = new URL(c.req.url).origin + \"/survey\";\n\n // Calculate PMF score from raw data if no insights yet\n const rawPmfScore = counts.total > 0 ? (counts.very / counts.total) * 100 : 0;\n\n // Parse JSON fields from insights\n let topBenefits: string[] = [];\n let topImprovements: string[] = [];\n let doubleDown: string[] = [];\n let addressGaps: string[] = [];\n let personas: string[] = [];\n\n if (insights) {\n try {\n topBenefits = JSON.parse(insights.top_benefits || \"[]\");\n topImprovements = JSON.parse(insights.top_improvements || \"[]\");\n doubleDown = JSON.parse(insights.roadmap_double_down || \"[]\");\n addressGaps = JSON.parse(insights.roadmap_address_gaps || \"[]\");\n personas = JSON.parse(insights.personas_in_segment || \"[]\");\n } catch {\n // Keep defaults\n }\n }\n\n return c.html(\n \n

\n {/* Header */}\n

PMF Survey Dashboard

\n Track your product-market fit using the Superhuman framework\n

\n\n {/* AI Status Banner */}\n 0} />\n\n {/* Survey Link */}\n

Share Your Survey

{surveyUrl}

\n this.textContent = 'Copy Link', 2000)`}\n class=\"px-4 py-2 bg-indigo-600 hover:bg-indigo-700 text-white font-medium rounded-lg transition-colors\"\n >\n Copy Link\n \n

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

\n \n \n \n

No responses yet

\n Share your survey link to start collecting feedback\n

\n \n Preview Survey\n \n

\n ) : (\n <>\n {/* PMF Scores */}\n

\n \n \n \n \n

\n\n {/* Response Breakdown */}\n

\n \n

\n Personas in \"Very Disappointed\" Segment\n

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

\n {hasAIEnabled() \n ? \"No personas identified yet\" \n : \"Add OPENAI_API_KEY for persona detection\"}\n

\n ) : (\n

\n {personas.map((persona) => (\n \n {persona}\n \n ))}\n

\n )}\n

\n These are the personas that appear in your \"very disappointed\" group. The\n segmented PMF score filters to only include these personas.\n

\n\n {/* HXC Profile */}\n {insights?.hxc_profile && (\n

\n High-Expectation Customer (HXC) Profile\n

\n Built from \"very disappointed\" users describing who would benefit most\n

\n {insights.hxc_profile.split(\"\\n\\n\").map((paragraph) => (\n

{paragraph}

\n ))}\n

\n )}\n\n {/* Word Clouds */}\n

\n \n \n

\n\n {/* Roadmap Recommendations */}\n

Roadmap Recommendations

\n Split 50/50 between doubling down on what users love and addressing what holds\n others back\n

\n \n \n

\n\n {/* Responses List */}\n

\n All Responses ({responses.length})\n

\n {responses.map((response) => (\n \n ))}\n

\n \n )}\n\n {/* Footer */}\n

\n Built with the{\" \"}\n \n Superhuman PMF Framework\n \n

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

Response Not Found

\n \n ← Back to Dashboard\n \n

\n ,\n 404,\n );\n }\n\n const colors: Record = {\n very: { bg: \"bg-green-50\", border: \"border-green-200\", text: \"text-green-700\" },\n somewhat: { bg: \"bg-yellow-50\", border: \"border-yellow-200\", text: \"text-yellow-700\" },\n not: { bg: \"bg-gray-50\", border: \"border-gray-200\", text: \"text-gray-600\" },\n };\n const c2 = colors[response.disappointment];\n\n let analysis = null;\n if (response.analysis) {\n try {\n analysis = JSON.parse(response.analysis);\n } catch {\n // Keep null\n }\n }\n\n return c.html(\n \n

\n \n ← Back to Dashboard\n \n\n

{response.persona || \"Unprocessed\"}

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

\n\n {/* Disappointment Level */}\n

\n \n \n {response.disappointment} Disappointed\n \n

\n\n {/* Survey Responses */}\n

\n Survey Responses\n

\n What type of people would benefit most?\n

{response.user_type}

Main benefit received

{response.main_benefit}

How to improve

{response.improvement}

\n {response.email && (\n

{response.email}

\n )}\n

\n\n {/* Analysis */}\n {analysis && (\n

\n Analysis {!hasAIEnabled() && (Basic)}\n

Assigned Persona

{analysis.persona}

\n {analysis.themes?.benefits?.length > 0 && (\n

Benefit Themes

\n {analysis.themes.benefits.map((b: string) => (\n \n {b}\n \n ))}\n

\n )}\n {analysis.themes?.improvements?.length > 0 && (\n

Improvement Themes

\n {analysis.themes.improvements.map((i: string) => (\n \n {i}\n \n ))}\n

\n )}\n {analysis.sentiment_notes && (\n

Sentiment Notes

{analysis.sentiment_notes}

\n )}\n

\n ,\n );\n});\n\nexport default app.fetch;\n",[],[199],{"_103":208,"_96":209,"_160":210,"_162":-5,"_163":145,"_164":211,"_166":167,"_105":212,"_100":213,"_169":193,"_171":214,"_173":22,"_174":-5,"_175":215,"_99":216},"99299eb2-fa7c-11f0-a539-42dde27851f2","db.ts","a019aea8-fa75-11f0-8990-42dde27851f2",20,["D",1769407350079],5,"import sqlite from \"https://esm.town/v/std/sqlite/main.ts\";\n\nconst TABLE_NAME = \"responses\";\nconst INSIGHTS_TABLE = \"insights\";\n\nlet tablesCreated = false;\n\nexport interface SurveyResponse {\n id: number;\n timestamp: number;\n disappointment: \"very\" | \"somewhat\" | \"not\";\n user_type: string;\n main_benefit: string;\n improvement: string;\n email?: string;\n persona?: string;\n analysis?: string;\n}\n\nexport interface Insights {\n id: number;\n timestamp: number;\n pmf_score: number;\n segmented_pmf_score: number;\n total_responses: number;\n very_disappointed_count: number;\n somewhat_disappointed_count: number;\n not_disappointed_count: number;\n hxc_profile: string;\n top_benefits: string;\n top_improvements: string;\n roadmap_double_down: string;\n roadmap_address_gaps: string;\n personas_in_segment: string;\n}\n\nasync function ensureTables(): Promise {\n if (tablesCreated) return;\n \n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${TABLE_NAME} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n timestamp INTEGER NOT NULL,\n disappointment TEXT NOT NULL,\n user_type TEXT NOT NULL,\n main_benefit TEXT NOT NULL,\n improvement TEXT NOT NULL,\n email TEXT,\n persona TEXT,\n analysis TEXT\n )\n `);\n\n await sqlite.execute(`\n CREATE TABLE IF NOT EXISTS ${INSIGHTS_TABLE} (\n id INTEGER PRIMARY KEY AUTOINCREMENT,\n timestamp INTEGER NOT NULL,\n pmf_score REAL NOT NULL,\n segmented_pmf_score REAL NOT NULL,\n total_responses INTEGER NOT NULL,\n very_disappointed_count INTEGER NOT NULL,\n somewhat_disappointed_count INTEGER NOT NULL,\n not_disappointed_count INTEGER NOT NULL,\n hxc_profile TEXT,\n top_benefits TEXT,\n top_improvements TEXT,\n roadmap_double_down TEXT,\n roadmap_address_gaps TEXT,\n personas_in_segment TEXT\n )\n `);\n \n tablesCreated = true;\n}\n\nexport async function storeResponse(data: {\n disappointment: \"very\" | \"somewhat\" | \"not\";\n user_type: string;\n main_benefit: string;\n improvement: string;\n email?: string;\n}): Promise {\n await ensureTables();\n \n const result = await sqlite.execute(\n `INSERT INTO ${TABLE_NAME} (timestamp, disappointment, user_type, main_benefit, improvement, email)\n VALUES (?, ?, ?, ?, ?, ?)`,\n [Date.now(), data.disappointment, data.user_type, data.main_benefit, data.improvement, data.email || null],\n );\n return Number(result.lastInsertRowid);\n}\n\nexport async function updateResponseAnalysis(id: number, persona: string, analysis: string): Promise {\n await ensureTables();\n await sqlite.execute(\n `UPDATE ${TABLE_NAME} SET persona = ?, analysis = ? WHERE id = ?`,\n [persona, analysis, id],\n );\n}\n\nexport async function getAllResponses(): Promise {\n await ensureTables();\n const result = await sqlite.execute(`SELECT * FROM ${TABLE_NAME} ORDER BY timestamp DESC`);\n return rowsToObjects(result) as SurveyResponse[];\n}\n\nexport async function getResponseById(id: number): Promise {\n await ensureTables();\n const result = await sqlite.execute(`SELECT * FROM ${TABLE_NAME} WHERE id = ?`, [id]);\n const rows = rowsToObjects(result);\n return (rows[0] as SurveyResponse) || null;\n}\n\nexport async function getResponsesByDisappointment(level: \"very\" | \"somewhat\" | \"not\"): Promise {\n await ensureTables();\n const result = await sqlite.execute(\n `SELECT * FROM ${TABLE_NAME} WHERE disappointment = ? ORDER BY timestamp DESC`,\n [level],\n );\n return rowsToObjects(result) as SurveyResponse[];\n}\n\nexport async function getResponseCounts(): Promise<{\n total: number;\n very: number;\n somewhat: number;\n not: number;\n}> {\n await ensureTables();\n const result = await sqlite.execute(`\n SELECT \n COUNT(*) as total,\n SUM(CASE WHEN disappointment = 'very' THEN 1 ELSE 0 END) as very,\n SUM(CASE WHEN disappointment = 'somewhat' THEN 1 ELSE 0 END) as somewhat,\n SUM(CASE WHEN disappointment = 'not' THEN 1 ELSE 0 END) as not_count\n FROM ${TABLE_NAME}\n `);\n const rows = rowsToObjects(result);\n const row = rows[0] as any;\n return {\n total: Number(row?.total) || 0,\n very: Number(row?.very) || 0,\n somewhat: Number(row?.somewhat) || 0,\n not: Number(row?.not_count) || 0,\n };\n}\n\nexport async function storeInsights(data: Omit): Promise {\n await ensureTables();\n await sqlite.execute(\n `INSERT INTO ${INSIGHTS_TABLE} \n (timestamp, pmf_score, segmented_pmf_score, total_responses, \n very_disappointed_count, somewhat_disappointed_count, not_disappointed_count,\n hxc_profile, top_benefits, top_improvements, roadmap_double_down, roadmap_address_gaps, personas_in_segment)\n VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)`,\n [\n Date.now(),\n data.pmf_score,\n data.segmented_pmf_score,\n data.total_responses,\n data.very_disappointed_count,\n data.somewhat_disappointed_count,\n data.not_disappointed_count,\n data.hxc_profile,\n data.top_benefits,\n data.top_improvements,\n data.roadmap_double_down,\n data.roadmap_address_gaps,\n data.personas_in_segment,\n ],\n );\n}\n\nexport async function getLatestInsights(): Promise {\n await ensureTables();\n const result = await sqlite.execute(\n `SELECT * FROM ${INSIGHTS_TABLE} ORDER BY timestamp DESC LIMIT 1`,\n );\n const rows = rowsToObjects(result);\n return (rows[0] as Insights) || null;\n}\n\n// Helper to convert rows array to objects\nfunction rowsToObjects(result: { columns: string[]; rows: unknown[][] }): Record[] {\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",[],[209],{"_103":218,"_96":219,"_160":220,"_162":-5,"_163":145,"_164":221,"_166":167,"_105":222,"_100":192,"_169":223,"_171":224,"_173":22,"_174":-5,"_175":225,"_99":226},"4932980c-fa7a-11f0-a99d-42dde27851f2","main.ts","f8e04c22-fa75-11f0-898c-42dde27851f2",16,["D",1769406356849],"http","/** @jsxImportSource npm:hono@4/jsx */\nimport { Hono } from \"npm:hono@4\";\nimport { processNewResponse } from \"./analysis.ts\";\nimport { app as dashboard } from \"./dashboard.tsx\";\nimport { getResponseById, storeResponse } from \"./db.ts\";\nimport { SurveyForm, SurveyThankYou } from \"./survey.tsx\";\n\nconst app = new Hono();\n\n// Configuration - customize this for your product\nconst PRODUCT_NAME = \"Your Product\"; // Change this to your product name\n\n// Survey form\napp.get(\"/survey\", (c) => {\n const submitUrl = new URL(c.req.url).origin + \"/submit\";\n return c.html();\n});\n\n// Survey submission endpoint\napp.post(\"/submit\", async (c) => {\n try {\n const body = await c.req.json();\n\n // Validate required fields\n const { disappointment, user_type, main_benefit, improvement, email } = body;\n\n if (!disappointment || ![\"very\", \"somewhat\", \"not\"].includes(disappointment)) {\n return c.json({ error: \"Invalid disappointment level\" }, 400);\n }\n if (!user_type || typeof user_type !== \"string\") {\n return c.json({ error: \"user_type is required\" }, 400);\n }\n if (!main_benefit || typeof main_benefit !== \"string\") {\n return c.json({ error: \"main_benefit is required\" }, 400);\n }\n if (!improvement || typeof improvement !== \"string\") {\n return c.json({ error: \"improvement is required\" }, 400);\n }\n\n // Store the response (works without AI)\n const id = await storeResponse({\n disappointment,\n user_type,\n main_benefit,\n improvement,\n email: email || undefined,\n });\n\n // Fire-and-forget the AI analysis (optional, won't block)\n const url = new URL(c.req.url);\n fetch(`${url.origin}/process/${id}`, {\n method: \"POST\",\n }).catch(() => {}); // Silently ignore if AI processing fails\n\n return c.json({ ok: true, id });\n } catch (err) {\n console.error(\"Error submitting survey:\", err);\n return c.json({ error: \"Failed to submit survey\" }, 500);\n }\n});\n\n// Background processing endpoint (AI-powered, optional)\napp.post(\"/process/:id\", async (c) => {\n // Skip if no API key - this is optional\n if (!Deno.env.get(\"OPENAI_API_KEY\")) {\n return c.json({ ok: true, skipped: true, reason: \"No OPENAI_API_KEY\" });\n }\n\n const id = parseInt(c.req.param(\"id\"));\n const response = await getResponseById(id);\n\n if (!response) {\n return c.json({ error: \"Response not found\" }, 404);\n }\n\n try {\n await processNewResponse(response);\n return c.json({ ok: true });\n } catch (err) {\n console.error(\"Error processing response:\", err);\n // Don't fail the request - AI is optional\n return c.json({ ok: true, skipped: true, reason: \"AI processing failed\" });\n }\n});\n\n// Manual trigger to reprocess all responses with AI\napp.post(\"/reprocess\", async (c) => {\n if (!Deno.env.get(\"OPENAI_API_KEY\")) {\n return c.json({ error: \"Add OPENAI_API_KEY to enable AI features\" }, 400);\n }\n\n const { reprocessAll } = await import(\"./analysis.ts\");\n try {\n const result = await reprocessAll();\n return c.json({ ok: true, ...result });\n } catch (err) {\n console.error(\"Error reprocessing:\", err);\n return c.json({ error: \"Reprocessing failed\" }, 500);\n }\n});\n\n// Thank you page\napp.get(\"/thanks\", (c) => {\n return c.html();\n});\n\n// Mount the dashboard\napp.route(\"/\", dashboard);\n\n// Root redirects to dashboard\napp.get(\"/\", (c) => {\n return c.redirect(\"/dashboard\");\n});\n\nexport default app.fetch;\n",[],[219],{"_103":228,"_96":229,"_160":230,"_162":-5,"_163":145,"_164":213,"_166":167,"_105":231,"_100":32,"_169":193,"_171":232,"_173":22,"_174":-5,"_175":233,"_99":234},"c5ebcb70-fa75-11f0-8810-42dde27851f2","survey.tsx","c5ebcc6a-fa75-11f0-8810-42dde27851f2",["D",1769404418711],"/** @jsxImportSource npm:hono@4/jsx */\n\ninterface SurveyFormProps {\n productName: string;\n submitUrl: string;\n}\n\nexport function SurveyForm({ productName, submitUrl }: SurveyFormProps) {\n return (\n \n \n \n \n Product Feedback Survey\n \n \n \n

\n Help us improve {productName}\n

\n Your feedback helps us build a better product. This takes about 2 minutes.\n

\n\n

\n {/* Question 1: Disappointment Level */}\n

\n \n \n 1. How would you feel if you could no longer use {productName}?\n \n Required\n \n

\n {[\n { value: \"very\", label: \"Very disappointed\" },\n { value: \"somewhat\", label: \"Somewhat disappointed\" },\n { value: \"not\", label: \"Not disappointed\" },\n ].map((option) => (\n \n \n {option.label}\n \n ))}\n

\n\n {/* Question 2: User Type */}\n

\n \n \n 2. What type of people do you think would most benefit from {productName}?\n \n \n Describe the ideal user in your own words\n \n \n \n \n

\n\n {/* Question 3: Main Benefit */}\n

\n \n \n 3. What is the main benefit you receive from {productName}?\n \n \n What value does it provide that keeps you using it?\n \n \n \n \n

\n\n {/* Question 4: Improvements */}\n

\n \n \n 4. How can we improve {productName} for you?\n \n \n What's missing? What would make it even better?\n \n \n \n \n

\n\n {/* Optional: Email */}\n

\n \n \n Email (optional)\n \n \n If you'd like us to follow up with you\n \n \n \n

\n\n {/* Submit */}\n

\n \n Submit Feedback\n \n

\n\n {/* Success State */}\n

\n \n \n \n

Thank you!

\n Your feedback helps us build a better product for you.\n

\n\n

\n Powered by the{\" \"}\n \n Superhuman PMF Framework\n \n

\n\n {\n e.preventDefault();\n \n const form = e.target;\n const submitBtn = document.getElementById('submit-btn');\n const formData = new FormData(form);\n \n submitBtn.disabled = true;\n submitBtn.textContent = 'Submitting...';\n \n try {\n const response = await fetch('${submitUrl}', {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({\n disappointment: formData.get('disappointment'),\n user_type: formData.get('user_type'),\n main_benefit: formData.get('main_benefit'),\n improvement: formData.get('improvement'),\n email: formData.get('email') || undefined\n })\n });\n \n if (response.ok) {\n form.classList.add('hidden');\n document.getElementById('success-state').classList.remove('hidden');\n } else {\n throw new Error('Submission failed');\n }\n } catch (err) {\n submitBtn.disabled = false;\n submitBtn.textContent = 'Submit Feedback';\n alert('Something went wrong. Please try again.');\n }\n });\n `,\n }}\n />\n \n \n );\n}\n\nexport function SurveyThankYou() {\n return (\n \n \n \n \n Thank You\n \n \n \n

\n \n \n \n

Thank you!

\n Your feedback has been recorded and will help us improve.\n

\n \n \n );\n}\n",[],[229],"files",[157,178,186,197,207,217,227],"counts",{"_239":32,"_240":203,"_241":32,"_242":243,"_246":247},"pulls","branches","forks","envVars",{"_244":32,"_245":32},"count","emptyCount","connections",{"_244":32,"_248":32},"unfilledCount","contents",[251,254,257,260,263,266,269],{"_103":158,"_96":159,"_160":161,"_162":-5,"_163":145,"_164":165,"_166":167,"_105":252,"_100":32,"_169":170,"_171":172,"_173":22,"_174":-5,"_99":253},["D",1769404334403],[159],{"_103":179,"_96":180,"_160":181,"_162":-5,"_163":145,"_164":144,"_166":167,"_105":255,"_100":165,"_169":170,"_171":183,"_173":22,"_174":-5,"_99":256},["D",1769443591308],[180],{"_103":187,"_96":188,"_160":189,"_162":-5,"_163":145,"_164":190,"_166":167,"_105":258,"_100":192,"_169":193,"_171":194,"_173":22,"_174":-5,"_99":259},["D",1769406330805],[188],{"_103":198,"_96":199,"_160":200,"_162":-5,"_163":145,"_164":201,"_166":167,"_105":261,"_100":203,"_169":193,"_171":204,"_173":22,"_174":-5,"_99":262},["D",1769405522703],[199],{"_103":208,"_96":209,"_160":210,"_162":-5,"_163":145,"_164":211,"_166":167,"_105":264,"_100":213,"_169":193,"_171":214,"_173":22,"_174":-5,"_99":265},["D",1769407350079],[209],{"_103":218,"_96":219,"_160":220,"_162":-5,"_163":145,"_164":221,"_166":167,"_105":267,"_100":192,"_169":223,"_171":224,"_173":22,"_174":-5,"_99":268},["D",1769406356849],[219],{"_103":228,"_96":229,"_160":230,"_162":-5,"_163":145,"_164":213,"_166":167,"_105":270,"_100":32,"_169":193,"_171":232,"_173":22,"_174":-5,"_99":271},["D",1769404418711],[229],"upstreamProject","upstreamBranch","emptyEnvVars","isNew","flags",[],"routes/_app.x.$handle.$name.environment-variables",{"_94":95,"_96":97,"_101":280,"_242":285,"_286":22},{"_103":104,"_96":97,"_105":281,"_107":-5,"_108":22,"_109":110,"_111":112,"_113":-5,"_14":114,"_115":-5,"_116":22,"_117":-5,"_118":-5,"_119":32,"_16":120,"_121":122,"_123":124,"_125":126,"_127":126,"_128":129,"_130":129,"_131":129,"_132":126,"_133":126,"_23":282,"_137":283,"_142":284,"_154":22},["D",1769404297336],{"_94":95,"_135":136},{"_94":95,"_139":136,"_14":114,"_140":141},{"_100":144,"_96":44,"_103":145,"_146":104,"_147":-5,"_148":-5,"_149":-5,"_150":-5,"_151":-5,"_152":97,"_153":95},[],"isTeamOrg","actionData","errors"]

dcm31

pmf-survey

Environment variables