--- name: spec-to-repo description: "Use when the user says 'build me an app', 'create a project from this spec', 'scaffold a new repo', 'generate a starter', 'turn this idea into code', 'bootstrap a project', 'I have requirements and need a codebase', or provides a natural-language project specification and expects a complete, runnable repository. Stack-agnostic: Next.js, FastAPI, Rails, Go, Rust, Flutter, and more." --- # Spec to Repo Turn a natural-language project specification into a complete, runnable starter repository. Not a template filler — a spec interpreter that generates real, working code for any stack. ## When to Use - User provides a text description of an app and wants code - User has a PRD, requirements doc, or feature list and needs a codebase - User says "build me an app that...", "scaffold this", "bootstrap a project" - User wants a working starter repo, not just a file tree **Not this skill** when the user wants a SaaS app with Stripe + Auth specifically — use `product-team/saas-scaffolder` instead. ## Core Workflow ### Phase 1 — Parse & Interpret Read the spec. Extract these fields silently: | Field | Source | Required | |-------|--------|----------| | App name | Explicit or infer from description | yes | | Description | First sentence of spec | yes | | Features | Bullet points or sentences describing behavior | yes | | Tech stack | Explicit ("use FastAPI") or infer from context | yes | | Auth | "login", "users", "accounts", "roles" | if mentioned | | Database | "store", "save", "persist", "records", "schema" | if mentioned | | API surface | "endpoint", "API", "REST", "GraphQL" | if mentioned | | Deploy target | "Vercel", "Docker", "AWS", "Railway" | if mentioned | **Stack inference rules** (when user doesn't specify): | Signal | Inferred stack | |--------|---------------| | "web app", "dashboard", "SaaS" | Next.js + TypeScript | | "API", "backend", "microservice" | FastAPI (Python) or Express (Node) | | "mobile app" | Flutter or React Native | | "CLI tool" | Go or Python | | "data pipeline" | Python | | "high performance", "systems" | Rust or Go | After parsing, present a structured interpretation back to the user: ``` ## Spec Interpretation **App:** [name] **Stack:** [framework + language] **Features:** 1. [feature] 2. [feature] **Database:** [yes/no — engine] **Auth:** [yes/no — method] **Deploy:** [target] Does this match your intent? Any corrections before I generate? ``` Flag ambiguities. Ask **at most 3** clarifying questions. If the user says "just build it", proceed with best-guess defaults. ### Phase 2 — Architecture Design the project before writing any files: 1. **Select template** — Match to a stack template from `references/stack-templates.md` 2. **Define file tree** — List every file that will be created 3. **Map features to files** — Each feature gets at minimum one file/component 4. **Design database schema** — If applicable, define tables/collections with fields and types 5. **Identify dependencies** — List every package with version constraints 6. **Plan API routes** — If applicable, list every endpoint with method, path, request/response shape Present the file tree to the user before generating: ``` project-name/ ├── README.md ├── .env.example ├── .gitignore ├── .github/workflows/ci.yml ├── package.json / requirements.txt / go.mod ├── src/ │ ├── ... ├── tests/ │ ├── ... └── ... ``` ### Phase 3 — Generate Write every file. Rules: - **Real code, not stubs.** Every function has a real implementation. No `// TODO: implement` or `pass` placeholders. - **Syntactically valid.** Every file must parse without errors in its language. - **Imports match dependencies.** Every import must correspond to a package in the manifest (package.json, requirements.txt, go.mod, etc.). - **Types included.** TypeScript projects use types. Python projects use type hints. Go projects use typed structs. - **Environment variables.** Generate `.env.example` with every required variable, commented with purpose. - **README.md.** Include: project description, prerequisites, setup steps (clone, install, configure env, run), and available scripts/commands. - **CI config.** Generate `.github/workflows/ci.yml` with: install, lint (if linter in deps), test, build. - **.gitignore.** Stack-appropriate ignores (node_modules, __pycache__, .env, build artifacts). **File generation order:** 1. Manifest (package.json / requirements.txt / go.mod) 2. Config files (.env.example, .gitignore, CI) 3. Database schema / migrations 4. Core business logic 5. API routes / endpoints 6. UI components (if applicable) 7. Tests 8. README.md ### Phase 4 — Validate After generation, run through this checklist: - [ ] Every imported package exists in the manifest - [ ] Every file referenced by an import exists in the tree - [ ] `.env.example` lists every env var used in code - [ ] `.gitignore` covers build artifacts and secrets - [ ] README has setup instructions that actually work - [ ] No hardcoded secrets, API keys, or passwords - [ ] At least one test file exists - [ ] Build/start command is documented and would work Run `scripts/validate_project.py` against the generated directory to catch common issues. ## Examples ### Example 1: Task Management API **Input spec:** > "Build me a task management API. Users can create, list, update, and delete tasks. Tasks have a title, description, status (todo/in-progress/done), and due date. Use FastAPI with SQLite. Add basic auth with API keys." **Output file tree:** ``` task-api/ ├── README.md ├── .env.example # API_KEY, DATABASE_URL ├── .gitignore ├── .github/workflows/ci.yml ├── requirements.txt # fastapi, uvicorn, sqlalchemy, pytest ├── main.py # FastAPI app, CORS, lifespan ├── models.py # SQLAlchemy Task model ├── schemas.py # Pydantic request/response schemas ├── database.py # SQLite engine + session ├── auth.py # API key middleware ├── routers/ │ └── tasks.py # CRUD endpoints └── tests/ └── test_tasks.py # Smoke tests for each endpoint ``` ### Example 2: Recipe Sharing Web App **Input spec:** > "I want a recipe sharing website. Users sign up, post recipes with ingredients and steps, browse other recipes, and save favorites. Use Next.js with Tailwind. Store data in PostgreSQL." **Output file tree:** ``` recipe-share/ ├── README.md ├── .env.example # DATABASE_URL, NEXTAUTH_SECRET, NEXTAUTH_URL ├── .gitignore ├── .github/workflows/ci.yml ├── package.json # next, react, tailwindcss, prisma, next-auth ├── tailwind.config.ts ├── tsconfig.json ├── next.config.ts ├── prisma/ │ └── schema.prisma # User, Recipe, Ingredient, Favorite models ├── src/ │ ├── app/ │ │ ├── layout.tsx │ │ ├── page.tsx # Homepage — recipe feed │ │ ├── recipes/ │ │ │ ├── page.tsx # Browse recipes │ │ │ ├── [id]/page.tsx # Recipe detail │ │ │ └── new/page.tsx # Create recipe form │ │ └── api/ │ │ ├── auth/[...nextauth]/route.ts │ │ └── recipes/route.ts │ ├── components/ │ │ ├── RecipeCard.tsx │ │ ├── RecipeForm.tsx │ │ └── Navbar.tsx │ └── lib/ │ ├── prisma.ts │ └── auth.ts └── tests/ └── recipes.test.ts ``` ### Example 3: CLI Expense Tracker **Input spec:** > "Python CLI tool for tracking expenses. Commands: add, list, summary, export-csv. Store in a local SQLite file. No external API." **Output file tree:** ``` expense-tracker/ ├── README.md ├── .gitignore ├── .github/workflows/ci.yml ├── pyproject.toml ├── src/ │ └── expense_tracker/ │ ├── __init__.py │ ├── cli.py # argparse commands │ ├── database.py # SQLite operations │ ├── models.py # Expense dataclass │ └── formatters.py # Table + CSV output └── tests/ └── test_cli.py ``` ## Anti-Patterns | Anti-pattern | Fix | |---|---| | **Placeholder code** — `// TODO: implement`, `pass`, empty function bodies | Every function has a real implementation. If complex, implement a working simplified version. | | **Stack override** — picking Next.js when the user said Flask | Always honor explicit tech preferences. Only infer when the user doesn't specify. | | **Missing .gitignore** — committing node_modules or .env | Generate stack-appropriate .gitignore as one of the first files. | | **Phantom imports** — importing packages not in the manifest | Cross-check every import against package.json / requirements.txt before finishing. | | **Over-engineering MVP** — adding Redis caching, rate limiting, WebSockets to a v1 | Build the minimum that works. The user can iterate. | | **Ignoring stated preferences** — user says "PostgreSQL" and you generate MongoDB | Parse the spec carefully. Explicit preferences are non-negotiable. | | **Missing env vars** — code reads `process.env.X` but `.env.example` doesn't list it | Every env var used in code must appear in `.env.example` with a comment. | | **No tests** — shipping a repo with zero test files | At minimum: one smoke test per API endpoint or one test per core function. | | **Hallucinated APIs** — generating code that calls library methods that don't exist | Stick to well-documented, stable APIs. When unsure, use the simplest approach. | ## Validation Script ### `scripts/validate_project.py` Checks a generated project directory for common issues: ```bash # Validate a generated project python3 scripts/validate_project.py /path/to/generated-project # JSON output python3 scripts/validate_project.py /path/to/generated-project --format json ``` Checks performed: - README.md exists and is non-empty - .gitignore exists - .env.example exists (if code references env vars) - Package manifest exists (package.json, requirements.txt, go.mod, Cargo.toml, pubspec.yaml) - No .env file committed (secrets leak) - At least one test file exists - No TODO/FIXME placeholders in generated code ## Progressive Enhancement For complex specs, generate in stages: 1. **MVP** — Core feature only, working end-to-end 2. **Auth** — Add authentication if requested 3. **Polish** — Error handling, validation, loading states 4. **Deploy** — Docker, CI, deploy config Ask the user after MVP: "Core is working. Want me to add auth/polish/deploy next, or iterate on what's here?" ## Cross-References - Related: `product-team/saas-scaffolder` — SaaS-specific scaffolding (Next.js + Stripe + Auth) - Related: `engineering/spec-driven-workflow` — spec-first development methodology - Related: `engineering/database-designer` — database schema design patterns - Related: `engineering-team/senior-fullstack` — full-stack implementation patterns