Mattnebr AI Assistant Foundry Spec To Repo

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:

Stack inference rules (when user doesn't specify):

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

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:

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

Source: mattnebr/ai-assistant-foundry — distributed by TomeVault.