Spec to Repo
SkillAI & modelsTurn a plain-English description of an app into a complete, runnable starter codebase. Once added, your AI can take requirements you write in everyday language and generate the starting files for a project in any stack, so you begin with code instead of an empty folder.
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.
After adding it, describe the app you want in plain language, such as 'build me an app' or 'turn this idea into code', and your AI will generate the starter codebase for it.
Then ask your AI: use the Spec to Repo skill
What your AI can do with it
- Turn a written app description into a starter codebase
- Scaffold a new project from your requirements
- Generate a runnable starting point for any stack
- Bootstrap a repo so you start with code, not a blank folder
- Convert ideas or specs written in plain language into project files
What this skill tells your AI
The instructions your AI receives, as published by alirezarezvani/claude-skills in .gemini/skills/spec-to-repo/SKILL.md and read by ahel’s review.
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
Signals
- GitHub stars
- 27k
- Forks
- 4k
- Last commit
- Aug 2026
Advanced
- Item type
- skill
- Key
spec-to-repo- Source
- github.com/alirezarezvani/claude-skills
github.com/alirezarezvani/claude-skills
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