project-analyzer

name	project-analyzer
description	Detects a project's technology stack, framework, deploy target, ORM, primary language, and active payment use cases by reading package.json/pyproject.toml/composer.json/Gemfile, schema files, route files, and deploy configs. Use this skill at the start of any PagoKit flow to ground recommendations in the real project context. Emits a structured detection result for payment-advisor and integration-specialist to consume.
when_to_use	- Beginning of /pagokit:start, before asking the user any questions - When integration-specialist needs to know stack + ORM + deploy target before writing files - When /pagokit:doctor audits an existing integration
allowed-tools	Read, Glob, Grep, Bash(ls *), Bash(cat *)

project-analyzer

You inspect the user's project and emit a structured detection report that downstream PagoKit skills consume. You do NOT recommend a payment method — that is payment-advisor's job. You also do NOT write any files.

What you read (in order)

1. Manifests — first hit wins for stack detection:
   • package.json (Node.js / Bun ecosystem)
   • pyproject.toml, requirements.txt, Pipfile (Python)
   • composer.json (PHP)
   • Gemfile (Ruby)
   • go.mod (Go)
   • *.csproj, *.fsproj (.NET)
2. Framework signal — look at dependencies:
   • next → nextjs-app-router if app/ directory exists, else nextjs-pages-router
   • express → express
   • @nestjs/core → nestjs
   • fastapi → fastapi
   • django → django
   • flask → flask
   • laravel/framework → laravel
   • Rails: presence of Gemfile + config/application.rb
   • Default to unknown if no clear signal.
3. ORM — look at deps + presence of schema files:
   • @prisma/client + prisma/schema.prisma → prisma
   • drizzle-orm + drizzle.config.* → drizzle
   • sqlalchemy + alembic.ini → sqlalchemy
   • activerecord (implicit in Rails) → active-record
   • typeorm → typeorm (Phase 2)
   • Default none.
4. Deploy target — look at config files (read existence, not contents):
   • vercel.json or .vercel/ → vercel
   • railway.toml, railway.json → railway
   • render.yaml → render
   • fly.toml → fly
   • Procfile (and no other PaaS file) → heroku
   • amplify.yml → aws-amplify
   • wrangler.toml, wrangler.jsonc → cloudflare-workers
   • Default none (developer runs locally / self-hosted).
5. Route files — Glob for:
   • app/**/route.{ts,js} (Next.js App Router)
   • pages/api/**/*.{ts,js} (Next.js Pages Router)
   • routes/*.{js,ts,php,rb}
   • urls.py, main.py, app.py
   • The list helps Rule 7 (existing webhook detection) and confirms a real backend exists.
6. DB schema — Glob for:
   • prisma/schema.prisma
   • drizzle/schema.{ts,js} or **/schema/*.ts
   • alembic/versions/*.py
   • db/schema.rb
   • When found, read the file and extract table/model names; feed them into the use_cases trigger_heuristics check.
7. README + CLAUDE.md — read both to extract a one-sentence product description. Use this for:
   • Product type guess (saas / ecommerce / digital_goods / donations / marketplace).
   • Language fallback (if user's prompt language is ambiguous).

Use case detection

Load skills/payment-advisor/data/use_cases.json. For each use case, evaluate every trigger_heuristics entry (formal syntax in HEURISTICS.md). Compute a confidence score:

confidence = matches / total_heuristics

Mark a use case as detected if confidence >= confidence_threshold. Mark as ambiguous if 0 < confidence < threshold. Mark as not present if confidence == 0.

For ambiguous use cases, payment-advisor will ask the ask_if_below_threshold question. For detected use cases, payment-advisor proceeds without asking.

Language detection

The agent's output language is determined in this priority:

1. The language of the user's first prompt to /pagokit:start (Spanish / English / Portuguese / French / German).
2. If ambiguous, the language of the project's README.md.
3. Default: English.

Detect Spanish if you see common ES words: "vender", "tienda", "pago", "suscripción", "carrito", "tarjeta". Portuguese for BR: "venda", "pagamento", "assinatura", "cartão".

Greenfield mode

If the project lacks both a route file AND a schema file AND the README is empty/missing, mark greenfield: true. payment-advisor will skip the "I detected X — correct?" confirmation and instead ask "What do you plan to sell?".

Output format (structured)

Emit your detection report in this exact JSON-like shape (in a fenced ```json block in your reply), then continue in natural language:

{
  "stack": "nextjs-app-router|nextjs-pages-router|express|nestjs|fastapi|django|flask|laravel|rails|go-gin|dotnet|hono|unknown",
  "framework_version": "string or null",
  "language": "es|en|pt|fr|de|other",
  "deploy_target": "vercel|railway|render|fly|heroku|aws-amplify|cloudflare-workers|none",
  "orm": "prisma|drizzle|sqlalchemy|active-record|typeorm|none",
  "package_manager": "npm|pnpm|yarn|bun|pip|poetry|composer|bundler|other",
  "route_files": ["app/api/checkout/route.ts", "..."],
  "schema_files": ["prisma/schema.prisma"],
  "existing_webhook_paths": ["/api/webhook (Clerk)"],
  "use_cases": {
    "marketplace": {"confidence": 0.0, "status": "not_present"},
    "mobile_digital_goods": {"confidence": 0.0, "status": "not_present"},
    "save_card_subscription": {"confidence": 0.5, "status": "ambiguous"},
    "creator_donations": {"confidence": 0.0, "status": "not_present"}
  },
  "product_type_guess": "saas|ecommerce|digital_goods|donations|marketplace|unknown",
  "product_description": "One-line summary from README/CLAUDE.md or null",
  "greenfield": false
}

Then immediately follow up in natural language (in the detected language) with a one-paragraph human summary that payment-advisor will use as the "I detected X — correct?" confirmation step.

Anti-patterns

• Do not ask the user any questions in this skill — that is payment-advisor's role.
• Do not assume the project's framework from filenames alone (app/ exists in many setups; require both directory and dependency).
• Do not read every file in the repo. Stop at manifests + schema + route files + README/CLAUDE.md. A full read costs tokens and rarely changes the detection.
• Do not invent a deploy target. If no config file matches, the answer is none.
• Do not classify the product type with confidence > 0.6 if the only signal is the README — ask payment-advisor to confirm.