ai-rulez

Write AI assistant rules once. Generate configs for 18 different tools.

Every AI coding tool wants its own config format. Claude needs CLAUDE.md, Cursor wants .cursor/rules/, Copilot expects .github/copilot-instructions.md. Keeping them in sync is tedious and error-prone.

ai-rulez solves this: define rules and context in .ai-rulez/, run generate, and get native configs for all your tools.

npx ai-rulez@latest init && npx ai-rulez@latest generate

Documentation

What You Get

• 18 preset generators: Claude, Cursor, Windsurf, Copilot, Gemini, Cline, Continue.dev, Amp, Junie, Codex, OpenCode, and custom presets
• Commands system: Define slash commands once, use them across tools that support it
• Context compression: 34% size reduction with smart whitespace optimization
• Remote includes: Pull shared rules from git repos (company standards, team configs)
• Profile system: Generate different configs for backend/frontend/QA teams
• MCP server: Let AI assistants manage their own rules via Model Context Protocol
• Type-safe schemas: JSON Schema validation for all config files

Quick Start

# No install required
npx ai-rulez@latest init "My Project"
npx ai-rulez@latest generate

This creates:

.ai-rulez/
├── config.yaml       # Which tools to generate for
├── rules/            # Guidelines AI must follow
├── context/          # Project background info
├── skills/           # Specialized AI roles
├── agents/           # Agent-specific prompts
└── commands/         # Slash commands

And generates native configs for each tool you specify.

Configuration

# .ai-rulez/config.yaml
version: "3.0"
name: "My Project"

presets:
  - claude
  - cursor
  - copilot
  - windsurf

# Optional: team-specific profiles
profiles:
  backend: [backend, database]
  frontend: [frontend, ui]

# Optional: share rules across repos
includes:
  - name: company-standards
    source: https://github.com/company/ai-rules.git
    ref: main

Content Structure

Rules - What AI must do:

---
priority: critical
---
# Security Standards
- Never commit credentials
- Use environment variables for secrets
- Sanitize all user input

Context - What AI should know:

---
priority: high
---
# Architecture
This is a microservices app:
- API Gateway (Go, port 8080)
- Auth Service (Go, port 8081)
- PostgreSQL 15

Commands - Slash commands across tools:

---
name: review
aliases: [r, pr-review]
targets: [claude, cursor, continue-dev]
---
# Code Review
Review the current PR for:
1. Logic errors
2. Security issues
3. Performance problems

Installation

No install required:

npx ai-rulez@latest <command>
# or
uvx ai-rulez <command>

Global install:

# Homebrew
brew install goldziher/tap/ai-rulez

# npm
npm install -g ai-rulez

# pip
pip install ai-rulez

# Go
go install github.com/Goldziher/ai-rulez/cmd@latest

CLI Reference

# Initialize project
ai-rulez init "Project Name"
ai-rulez init --domains backend,frontend,qa

# Generate configs
ai-rulez generate
ai-rulez generate --profile backend
ai-rulez generate --dry-run

# Content management
ai-rulez add rule security-standards --priority critical
ai-rulez add context api-docs
ai-rulez add skill database-expert
ai-rulez add command review-pr

ai-rulez list rules
ai-rulez remove rule outdated-rule

# Validation
ai-rulez validate

# MCP server (for AI assistants)
npx ai-rulez@latest mcp

# Migrate from V2
ai-rulez migrate v3

Remote Includes

Share rules across repositories:

includes:
  # HTTPS
  - name: company-standards
    source: https://github.com/company/ai-rules.git
    ref: main
    include: [rules, context]
    merge_strategy: local-override

  # SSH
  - name: shared-configs
    source: git@github.com:org/shared-ai-rulez.git
    ref: v2.0.0
    include: [rules, skills]

  # Local path
  - name: local-standards
    source: ../shared-rules
    include: [rules]

Private repos use AI_RULEZ_GIT_TOKEN environment variable or --token flag.

Generated Output

Running ai-rulez generate creates:

Preset	Output
Claude	CLAUDE.md + .claude/skills/ + .claude/agents/
Cursor	.cursor/rules/*.mdc
Windsurf	.windsurf/*.md
Copilot	.github/copilot-instructions.md
Gemini	.gemini/config.yaml
Continue.dev	.continue/prompts/ai_rulez_prompts.yaml
Cline	.cline/rules/*.md
Custom	Any path with markdown, JSON, or directory output

Use Cases

Monorepo: Generate configs for multiple packages

ai-rulez generate --recursive

Team profiles: Different rules for different teams

ai-rulez generate --profile backend
ai-rulez generate --profile frontend

CI validation: Ensure configs stay in sync

ai-rulez validate && ai-rulez generate --dry-run

Import existing configs: Migrate from tool-specific files

ai-rulez init --from auto
ai-rulez init --from .cursorrules,CLAUDE.md

MCP Server

Let AI assistants manage rules directly:

# .ai-rulez/mcp.yaml
version: "3.0"
mcp_servers:
  - name: ai-rulez
    command: npx
    args: ["-y", "ai-rulez@latest", "mcp"]
    transport: stdio
    enabled: true

The MCP server exposes CRUD operations, validation, and generation to AI assistants.

Compression

Reduce context size for token-constrained tools:

compression:
  level: standard  # none, minimal, standard, aggressive

At standard level, output is ~34% smaller through whitespace optimization and duplicate removal.

Documentation

• Configuration Reference
• Domains & Profiles
• Remote Includes
• MCP Server
• Schema Validation
• Migration Guide

Contributing

Contributions welcome. See CONTRIBUTING.md.

License

MIT