Spec to repo
Unified skill library for Claude, Codex, Cursor, Antigravity & AI agents — 2,658 skills across 15 domains
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What its author says it does
Copied from the file, not written here
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.
SKILL.md
11.0 KB, ~2.6k tokens by cl100k_base, as published. Nobody here has run it
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:
- Select template — Match to a stack template from
references/stack-templates.md - Define file tree — List every file that will be created
- Map features to files — Each feature gets at minimum one file/component
- Design database schema — If applicable, define tables/collections with fields and types
- Identify dependencies — List every package with version constraints
- 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: implementorpassplaceholders. - 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.examplewith 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.ymlwith: install, lint (if linter in deps), test, build. - .gitignore. Stack-appropriate ignores (node_modules, pycache, .env, build artifacts).
File generation order:
- Manifest (package.json / requirements.txt / go.mod)
- Config files (.env.example, .gitignore, CI)
- Database schema / migrations
- Core business logic
- API routes / endpoints
- UI components (if applicable)
- Tests
- 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.examplelists every env var used in code -
.gitignorecovers 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:
# 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:
- MVP — Core feature only, working end-to-end
- Auth — Add authentication if requested
- Polish — Error handling, validation, loading states
- 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
Gives 0 of the 12 instructions most plan spec skills give in ~2.6k tokens
Counted across 1,099 of the 1,860 authors here whose files we hold, read 2026-08-07
- ask one question at a timein 51 of 1099
- Break plans into vertical slicesin 29 of 1099, across 11 files
- Publish issues in dependency orderin 27 of 1099, across 9 files
- Iterate until user approves the breakdownin 25 of 1099, across 7 files
- Explore the repository to understand the codebase statein 24 of 1099, across 7 files
- Use domain glossary vocabularyin 23 of 1099, across 5 files
- Apply correct triage labels to published issuesin 23 of 1099, across 5 files
- prefer AFK slices over HITLin 22 of 1099, across 7 files
- write a specification before writing any codein 22 of 1099, across 14 files
- Write failing tests before implementation codein 22 of 1099, across 20 files
- ask clarifying questions until requirements are concretein 21 of 1099, across 13 files
- Respect existing architecture decision recordsin 20 of 1099, across 5 files
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.