HN 표시: Vela Coach – Granola 성적표를 읽는 오픈 소스 코치

A reading of you, from your last 30 meetings. Vela Coach reads your real Granola meeting transcripts and writes a single, dense character reading of the operator they reveal — situated against academic frameworks for personality, communication, and leadership. The kind of thing a $500/hour coach would write after binging 90 days of your calendar. Live: coach.vela.partners · License: MIT · Status: alpha - Sign in with Granola — OAuth 2.0 + PKCE, no API keys to copy. - Bring your own AI — pick OpenAI, Anthropic, or Google Gemini and paste your own API key once. It lives in your browser's localStorage; we never see it persisted on our side. You pay your provider directly. - Pick meetings — last 30 days by default, or a custom range. - Sharpen the read — up to three quick questions if the model is unsure about an MBTI dimension. Skippable. - Read — a single scrollable page synthesizing: - MBTI (Myers–Briggs) with per-letter confidence + evidence quotes - OCEAN / Big Five (Costa & McCrae 1992; Barrick & Mount 1991) - Communication style — directness, hedging rate, listening ratio, specificity - Leadership style (Goleman 1998) - Situational signature — how you flex across investor / team / customer counterparties - Re-read — analysis can be re-run as you accumulate new meetings; readings auto-save to your browser. - Export — download your reading as HTML (self-contained, mirrors the live UI) or Markdown (LLM-friendly). - Tokens, your AI provider key, founder profile, and readings live in your browser's localStorage. We have no database. The Cloud Run container is stateless. - Transcripts pass through our server in-memory only — Granola → server → your chosen AI provider → your browser. Nothing is written to disk on our infra. Logs hold counts and HTTP status codes; never content, never keys. - Bring your own AI. OpenAI/Anthropic/Gemini billing flows through your account, with your data-use terms — not ours. - No analytics, no cookies, no third-party scripts. /reset wipes everything Coach has written to your device. Full details in PRIVACY.md. git clone https://github.com/vela-engineering/coach.git cd coach npm install npm run dev -- -p 4070 Open http://localhost:4070, sign in with Granola, then pick an AI provider and paste your API key. Get a key from: - OpenAI: https://platform.openai.com/api-keys ( sk-… ) - Anthropic: https://console.anthropic.com/settings/keys ( sk-ant-… ) - Google Gemini: https://aistudio.google.com/apikey ( AIza… ) That's it — no .env file required for local dev. The repo's open-source OAuth client is pre-registered for localhost:4070 . - Framework: Next.js 16 (App Router) + TypeScript - Styling: Tailwind CSS v4 + Framer Motion - AI: any of OpenAI ( gpt-5.5 ), Anthropic (claude-opus-4-7 ), or Google Gemini (gemini-3.1-pro-preview ) via dynamic-imported provider adapters insrc/lib/llm/ - Data: Granola public REST API ( public-api.granola.ai/v1 ) - Auth: Granola MCP OAuth ( mcp-auth.granola.ai ) — RFC 7591 dynamic client registration - Tests: Vitest, 330+ tests over src/__tests__/ src/ ├── app/ │ ├── api/ │ │ ├── auth/token/ # OAuth token exchange proxy (no logs of payload) │ │ ├── character/ # Streaming Character Reading endpoint │ │ ├── chat/ # Coaching follow-up chat │ │ ├── llm/verify/ # One-shot key probe before saving │ │ ├── meetings/ # Granola REST proxy │ │ └── repo-stats/ # GitHub stars (cached server-side) │ ├── auth/callback/ # OAuth redirect handler │ └── reset/ # Wipe-localStorage page (with confirm) ├── components/ │ ├── Onboarding.tsx # Cover → privacy → AI provider → sign in │ ├── ProviderSetup.tsx # Pick provider + paste key + verify │ ├── FounderIntake.tsx # Founder profile (pre-filled on returning) │ ├── SharpenRead.tsx # MBTI follow-up questions │ ├── CharacterReading.tsx # The reading page │ ├── CoachView.tsx # Header + reading shell + export menu │ ├── ConfirmDialog.tsx # Reusable destructive-action modal │ └── ... └── lib/ ├── llm/ # Provider abstraction │ ├── types.ts # LLMClient, LLMProvider, LLMUsage │ ├── index.ts # getLLMClient(provider, key) factory │ ├── gemini.ts # @google/genai adapter │ ├── openai.ts # openai adapter │ └── anthropic.ts # @anthropic-ai/sdk adapter ├── apiKey.ts # Per-provider keys in localStorage ├── character.ts # Analysis engine (provider-agnostic) ├── grounding.ts # Web search (Gemini only — graceful no-op for others) ├── granolaRest.ts # Granola REST client ├── relationshipMetrics.ts ├── exportHtml.ts # Self-contained HTML export ├── sessionFile.ts # Markdown export + parse ├── reset.ts # Single source of truth for "wipe all data" ├── mbti.ts # Pure MBTI helpers ├── phase.ts # Phase state machine ├── founderProfile.ts # localStorage profile └── sessions.ts # localStorage session store npm test # vitest run, 330+ tests npm run test:watch # Register a new Granola OAuth client for your prod redirect URI: curl -sS -X POST https://mcp-auth.granola.ai/oauth2/register \ -H "Content-Type: application/json" \ -d '{ "client_name": "Your Coach (production)", "redirect_uris": ["https://your-domain/auth/callback"], "grant_types": ["authorization_code", "refresh_token"], "response_types": ["code"], "token_endpoint_auth_method": "none", "scope": "openid email profile offline_access" }' # → returns { "client_id": "client_xxx" } # Build via Cloud Build with that client_id baked in: gcloud builds submit --config cloudbuild.yaml \ --substitutions=_IMAGE=us-central1-docker.pkg.dev/$PROJECT_ID/cloud-run-source-deploy/coach:latest,_NEXT_PUBLIC_GRANOLA_CLIENT_ID=client_xxx # Roll out to Cloud Run — note: NO server-side LLM key needed (BYOK): gcloud run deploy coach \ --image=us-central1-docker.pkg.dev/$PROJECT_ID/cloud-run-source-deploy/coach:latest \ --region=us-central1 --allow-unauthenticated --memory=1Gi --timeout=900 \ --set-env-vars=NEXT_PUBLIC_GRANOLA_CLIENT_ID=client_xxx The client_id is public by design (PKCE OAuth, no client secret). See SECURITY.md for the trust model and PRIVACY.md for what does + doesn't touch the server. Dark, intimate, editorial. Inspired by what a private executive coaching session feels like: - Palette — Void black ( #08080a ) + warm amber candlelight (#d4a04a ) - Typography — Newsreader serif italic for personality, Outfit sans for body - Details — Ambient glow, grain texture, dotted-underline citation links - Voice — Second person, citation-grounded, never hedges when evidence is strong Issues, PRs, and discussions welcome. See CONTRIBUTING.md for setup, conventions, and what we don't accept. For security issues, see SECURITY.md. For conduct, CODE_OF_CONDUCT.md. Coach's prose draws explicitly from a small canon. Each claim in the reading footnotes its source: - Costa & McCrae (1992) — Revised NEO Personality Inventory - Barrick & Mount (1991) — The Big Five Personality Dimensions and Job Performance - McCrae & Costa (1989) — Reinterpreting the Myers-Briggs Type Indicator from the Five-Factor Model - Furnham (1996) — The Big Five vs the Big Four - Goleman (1998) — What Makes a Leader? - Pennebaker (2011) — The Secret Life of Pronouns - Leary (1957) — Interpersonal Diagnosis of Personality - Edmondson (1999) — Psychological Safety and Learning Behavior in Work Teams - Schein (2009) — Helping - Granovetter (1973) — The Strength of Weak Ties MIT — © 2026 Vela Engineering.