RuleForge

Auto-generate AI coding assistant rules from your codebase.

RuleForge scans your project — languages, frameworks, linters, test setup, CI config — and generates ready-to-use rule files for Claude Code (CLAUDE.md), Cursor (.cursorrules), and GitHub Copilot (.github/copilot-instructions.md).

Stop writing these files by hand. Let your codebase speak for itself.

Why?

Every AI coding assistant works better with project-specific context. But most developers either:

• Skip writing rules entirely (leaving performance on the table)
• Copy-paste generic templates that don't match their actual stack
• Spend 30+ minutes hand-crafting rules that go stale

RuleForge generates accurate, stack-aware rules in seconds by actually reading your project config.

What It Detects

Language counts respect .gitignore, so generated bundles and local artifacts do not skew the detected stack.

Installation

pip install ruleforge

Quick Start

# Scan your project to see what's detected
ruleforge scan .

# Generate all rule files (CLAUDE.md, .cursorrules, copilot-instructions)
ruleforge generate .

# Generate only CLAUDE.md
ruleforge generate . -f claude

# Preview without writing anything
ruleforge preview .

# Audit existing assistant rules for missing guidance
ruleforge audit .

# Fail CI if the rules are too thin
ruleforge audit . --min-score 80

# Overwrite existing files
ruleforge generate . --overwrite

# Output to a different directory
ruleforge generate . -o /tmp/rules

Example Output

Running ruleforge generate on a FastAPI project produces a CLAUDE.md like:

# my-api

This is a Python project.
Key frameworks: FastAPI, Pydantic, SQLAlchemy.

## Project Structure

Source directories: `src/`, `tests/`
Entry points: `main.py`
Package manager: poetry

## Coding Conventions

- Linter: ruff
- Formatter: ruff
- Testing: pytest
- Python: >=3.11
- CI: GitHub Actions

## Guidelines

- Use type hints for function signatures.
- Run `ruff check` and `ruff format` before committing.
- Write tests with pytest. Put test files in the `tests/` directory.
- Use Pydantic models for request/response schemas.
- The project uses Docker. Keep Dockerfile up to date with dependencies.

## Do NOT

- Do not modify generated files or lock files manually.
- Do not add dependencies without mentioning it.
- Do not change the project structure without asking first.
- Do not skip CI checks or disable linting rules.
- Do not commit files matching gitignore patterns.

Supported Output Formats

Rule Audits

RuleForge can also check rule files you already wrote. It looks for the parts that usually make AI coding agents useful in a real repository:

• project context and detected stack
• concrete test, lint, typecheck, or build commands
• editing boundaries and generated-file warnings
• secret / token / .env handling
• git, PR, CI, and review workflow
• assistant behavior expectations

ruleforge audit .
ruleforge audit . --format json
ruleforge audit . --min-score 80

This is useful for CI or for checking whether a hand-written AGENTS.md, CLAUDE.md, .cursorrules, or Copilot instructions file is specific enough to trust.

Python API

from ruleforge import analyze_project, generate_rules
from ruleforge.generator import write_rules

# Analyze
profile = analyze_project("./my-project")
print(profile.languages)    # {'Python': 42, 'TypeScript': 15}
print(profile.frameworks)   # ['FastAPI', 'React']

# Generate
rules = generate_rules(profile, formats=["claude", "cursor"])
for rule in rules:
    print(rule.filename, len(rule.content))

# Write to disk
write_rules(rules, "./my-project")

Limitations

• Detection is based on config files and file extensions — it doesn't analyze code semantics
• Generated rules are a solid starting point, not a finished product. You should review and customize them for your project's specific conventions
• Framework detection depends on dependency declarations (pyproject.toml, package.json, etc.)

Contributing

Contributions welcome! Especially for:

• New language/framework detection (see analyzer.py)
• Better rule templates (see generator.py)
• Support for more AI assistant formats

git clone https://github.com/he-yufeng/RuleForge.git
cd RuleForge
pip install -e ".[dev]"
pytest

License

MIT