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Readme

ai-rulez ⚡

AI-powered development governance. One config to rule them all.

The Complete AI Development Platform

AI-Rulez is the definitive platform for AI-powered development governance. Beyond just generating configuration files, it provides real-time rule enforcement, automated code quality assurance, and intelligent governance across your entire development workflow.

🚀 Two Powerful Capabilities

1. Universal Configuration Management - Write once, deploy everywhere 2. AI-Powered Rule Enforcement - Real-time governance with automated fixes

Why AI-Rulez?

Modern development teams need more than just configuration management:

⚠️ The Problem

Configuration Hell: Each AI tool needs its own format (.cursorrules, CLAUDE.md, .windsurfrules, etc.)
Rule Enforcement Gap: No way to automatically validate that code follows your standards
Team Inconsistency: Different developers get different AI guidance
Manual Quality Control: Time-consuming code reviews for basic rule violations
Reactive Governance: Finding issues after they're already committed

✨ The Solution

AI-Rulez provides proactive development governance with a single ai-rulez.yaml that:

Generates configurations for every AI tool automatically
Enforces rules in real-time using AI agents (Claude, Gemini, etc.)
Applies automatic fixes for code quality issues
Integrates with your workflow (Git hooks, CI/CD, pre-commit)
Scales across teams with consistent standards

AI-Rulez Configuration Demo
📝 Configuration Management (via npx ai-rulez)

AI-Rulez Enforcement Demo
🤖 AI-Powered Rule Enforcement (via uvx ai-rulez@latest)

📖 Read the Full Documentation

🚀 Core Capabilities

1. 📋 Universal Configuration Management

Write once, deploy everywhere with intelligent AI-powered project analysis:

# AI analyzes your codebase and generates tailored config
npx ai-rulez init "My Project" --preset popular

Features:

AI Project Analysis: Automatically detects your tech stack, patterns, and conventions
Universal Output Generation: One YAML → all AI tool formats (CLAUDE.md, .cursorrules, .windsurfrules, etc.)
Smart Gitignore Management: Automatically excludes generated files from version control
MCP Integration: Auto-configure MCP servers across CLI tools (Claude, Gemini, etc.)
Team Collaboration: Remote includes, local overrides, monorepo support

2. 🤖 AI-Powered Rule Enforcement

Real-time governance with automated fixes using multiple AI agents:

# Check for violations with AI analysis
uvx ai-rulez@latest enforce --agent claude

# Automatically apply fixes
uvx ai-rulez@latest enforce --agent claude --fix

# Multi-agent review workflow
uvx ai-rulez@latest enforce --agent gemini --review --review-agent claude

Features:

Multi-Agent Support: Claude, Gemini, AMP, Cursor, Codex, Continue.dev, Junie
Automated Fixes: AI suggests and applies code improvements
Review Workflows: Iterative improvement with quality thresholds
Multiple Output Formats: Table, JSON, CSV, summary reports
CI/CD Integration: Git hooks, pre-commit, workflow automation
Quality Scoring: 0-100% compliance with configurable thresholds

How It Works

AI-Rulez operates as a comprehensive AI development governance platform:

📝 Configuration Phase: Your ai-rulez.yml serves as the single source of truth
🏗️ Generation Phase: Automatically creates native files for every AI tool
🔍 Enforcement Phase: AI agents continuously validate code against your rules
🛠️ Fix Phase: Automatic corrections and improvements applied in real-time
📊 Reporting Phase: Detailed compliance reports and quality metrics

Think of it as CI/CD for code quality - proactive governance instead of reactive fixes.

Example: `ai-rulez.yml`

$schema: https://github.com/Goldziher/ai-rulez/schema/ai-rules-v2.schema.json

metadata:
  name: "My SaaS Platform"
  version: "2.0.0"

# Use presets for common configurations
presets:
  - "popular"  # Includes Claude, Cursor, Windsurf, Copilot, and Gemini

rules:
  - name: "Go Code Standards"
    priority: high
    content: "Follow standard Go project layout (cmd/, internal/, pkg/). Use meaningful package names and export only what is necessary."

sections:
  - name: "Project Structure"
    priority: critical
    content: |
      - `cmd/`: Main application entry point
      - `internal/`: Private application code (business logic, data access)
      - `pkg/`: Public-facing libraries

agents:
  - name: "go-developer"
    description: "Go language expert for core development"
    system_prompt: "You are an expert Go developer. Your key responsibilities include writing idiomatic Go, using proper error handling, and creating comprehensive tests."

# MCP servers for direct AI tool integration
mcp_servers:
  - name: "ai-rulez"
    command: "npx"
    args: ["-y", "ai-rulez@latest", "mcp"]
    description: "AI-Rulez MCP server for configuration management"

Run ai-rulez generate → get all your configuration files, perfectly synchronized.

⚡ Quick Start

📋 Configuration Management

# 1. AI-powered project analysis and setup
npx ai-rulez@latest init "My Project" --preset popular

# 2. Generate all AI tool configuration files
npx ai-rulez@latest generate

# 3. Your AI tools now have comprehensive, project-specific context!

🤖 AI-Powered Rule Enforcement

# 1. Check for rule violations
uvx ai-rulez@latest enforce --agent claude --format table

# 2. Get detailed analysis and suggestions
uvx ai-rulez@latest enforce --agent claude --format json

# 3. Apply automatic fixes
uvx ai-rulez@latest enforce --agent claude --fix

# 4. Set up review workflow
uvx ai-rulez@latest enforce --agent claude --review --review-iterations 2

That's it! You now have both intelligent configuration management AND real-time rule enforcement powered by AI.

🗂️ .gitignore Management

AI-Rulez manages your .gitignore to keep generated files out of version control.

Automatic updates:

# During init (enabled by default)
ai-rulez init --preset claude

# During generate (optional)
ai-rulez generate --update-gitignore

# Disable if needed
ai-rulez init --preset popular --no-gitignore

What gets ignored:

Generated markdown files (CLAUDE.md, GEMINI.md, AGENTS.md)
AI tool directories (.claude/, .cursor/, .windsurf/, .clinerules/, etc.)
Config files (.mcp.json, .gemini/settings.json)

All entries are added under # AI Rules generated files without duplicates.

Best practice: Commit ai-rulez.yaml and .gitignore, but not the generated AI configuration files.

🤖 AI-Powered Rule Enforcement

The killer feature that sets AI-Rulez apart: real-time rule enforcement using AI agents. No more manual code reviews for basic violations—let AI catch and fix issues automatically.

✨ Key Benefits

Proactive Quality Control: Catch issues before they reach production
Multi-Agent Support: Claude, Gemini, AMP, Cursor, Codex—use the best AI for each task
Automatic Fixes: AI doesn't just find problems, it solves them
Workflow Integration: Git hooks, CI/CD, pre-commit—enforcement everywhere
Team Consistency: Same standards for everyone, from junior to senior devs

🎯 Real-World Use Cases

# Prevent console.log in production builds
ai-rulez enforce --agent claude --only-rules "no-console-output" --fix

# Ensure all functions have proper error handling
ai-rulez enforce --agent gemini --level strict --format json

# Multi-agent review for critical code changes
ai-rulez enforce --agent claude --review --review-agent gemini --review-threshold 95

# Automated fixes in CI/CD pipeline
ai-rulez enforce --agent claude --fix --format csv --output violations.csv

📊 Output Formats & Integration

Format	Use Case	Command
Table	Human-readable terminal output	`--format table`
JSON	API integration, detailed analysis	`--format json --pretty`
CSV	Data analysis, reporting	`--format csv --output report.csv`
Summary	Quick overview with scores	`--format summary`

🔄 Advanced Workflows

Review Pipeline: Multi-agent validation with quality gates

ai-rulez enforce --agent claude --review --review-iterations 3 --review-threshold 85

Fix & Verify: Apply fixes and validate improvements

ai-rulez enforce --agent gemini --fix --review --require-improvement

Team Standards: Consistent enforcement across the entire codebase

ai-rulez enforce --include-files "src/**/*.{js,ts,py}" --level strict --agent claude

Prefer manual setup?

# Basic initialization without AI assistance
ai-rulez init "My Project" --preset popular --no-agent

# Add your project-specific context
ai-rulez add rule "Tech Stack" --priority critical --content "This project uses Go and PostgreSQL."

# Generate files
ai-rulez generate

MCP Server Integration

ai-rulez provides seamless Model Context Protocol (MCP) integration, automatically configuring both file-based and CLI-based AI tools with your MCP servers.

Automatic CLI Configuration

When you run ai-rulez generate, MCP servers are automatically configured for available CLI tools:

ai-rulez generate
# ✅ Generated 3 file(s) successfully
# ✅ Configured claude MCP server: ai-rulez
# ✅ Configured gemini MCP server: database-tools

Supported CLI tools:

Claude CLI: claude mcp add with full env/transport support
Gemini CLI: gemini mcp add with automatic configuration

Hybrid Configuration

ai-rulez supports both CLI and file-based configurations simultaneously:

mcp_servers:
  - name: "database-tools"
    command: "uvx"
    args: ["mcp-server-postgres"]
    env:
      DATABASE_URL: "postgresql://localhost/mydb"
    targets: 
      - "@claude-cli"        # Configure Claude CLI
      - "@gemini-cli"        # Configure Gemini CLI  
      - ".cursor/mcp.json"   # Generate Cursor config file

This single configuration:

✅ Executes claude mcp add commands
✅ Executes gemini mcp add commands
✅ Generates .cursor/mcp.json file

Control Options

Default behavior (recommended):

ai-rulez generate
# Configures all available CLI tools + generates files

Disable CLI configuration when needed:

ai-rulez generate --no-configure-cli-mcp
# Only generates files, skips CLI tool configuration

Target specific tools:

mcp_servers:
  - name: "github-integration"
    command: "npx"
    args: ["@modelcontextprotocol/server-github"]
    targets: ["@claude-cli"]  # Only configure Claude CLI

Built-in MCP Server

ai-rulez includes its own MCP server for configuration management:

# Start the ai-rulez MCP server
ai-rulez mcp

# Or configure it automatically via your ai-rulez.yaml
mcp_servers:
  - name: "ai-rulez"
    command: "npx"
    args: ["-y", "ai-rulez@latest", "mcp"]
    description: "Configuration management server"

AI-Powered Rule Enforcement

AI-Rulez provides real-time rule enforcement using AI agents to automatically detect violations and apply fixes across your codebase.

AI-Rulez Enforcement Demo

Basic Enforcement

# Check for violations (read-only by default)
ai-rulez enforce

# Automatically apply fixes
ai-rulez enforce --fix

# Use specific AI agent
ai-rulez enforce --agent gemini --fix

Advanced Enforcement Options

# Enforce with specific level
ai-rulez enforce --level strict --agent claude

# Review workflow with iterative improvement
ai-rulez enforce --review --review-iterations 3 --review-threshold 85

# Multi-agent review (different agents for enforcement vs review)
ai-rulez enforce --agent gemini --review --review-agent claude

# Target specific files and rules
ai-rulez enforce --include-files "src/**/*.js" --only-rules "no-console-output"

# Output formats for automation
ai-rulez enforce --format json --output violations.json
ai-rulez enforce --format csv --output report.csv

Supported AI Agents

AI-Rulez integrates with all major AI coding assistants:

Claude (claude) - Anthropic's AI assistant
Gemini (gemini) - Google's AI model
Cursor (cursor) - AI-powered code editor
AMP (amp) - Sourcegraph's AI assistant
Codex (codex) - OpenAI's code model
Continue.dev (continue-dev) - Open-source coding assistant
Junie (junie) - JetBrains AI assistant

Enforcement Levels

warn: Log violations but don't fail (default)
error: Fail on violations but don't auto-fix
fix: Automatically apply suggested fixes
strict: Fail immediately on any violation

Integration with Git Hooks

Add enforcement to your Git workflow:

# .lefthook.yml
pre-commit:
  commands:
    ai-rulez-enforce:
      run: ai-rulez enforce --level error --agent gemini
      stage_fixed: true

# Or with pre-commit hooks
# .pre-commit-config.yaml
repos:
  - repo: local
    hooks:
      - id: ai-rulez-enforce
        name: AI-Rulez Enforcement
        entry: ai-rulez enforce --level error
        language: system
        pass_filenames: false

Review Workflow

The review system provides iterative code improvement:

# Enable review with quality scoring
ai-rulez enforce --review --review-threshold 80

# Multiple review iterations
ai-rulez enforce --review --review-iterations 5

# Auto-approve after reaching threshold
ai-rulez enforce --review --review-auto-approve

# Require improvement between iterations
ai-rulez enforce --review --require-improvement

The AI reviewer analyzes:

✅ Code quality and adherence to rules
✅ Suggested fixes and their appropriateness
✅ Overall improvement between iterations
✅ Compliance with project standards

📦 Installation

Choose your installation method based on your primary use case:

🚀 Quick Start (No Installation)

For Configuration Management (project setup, file generation):

# Node.js - Best for web/JS projects
npx ai-rulez@latest init "My Project" --preset popular
npx ai-rulez@latest generate

For Rule Enforcement (AI-powered validation):

# Python - Latest features, fastest updates
uvx ai-rulez@latest enforce --agent claude --fix
uvx ai-rulez@latest enforce --agent gemini --review

For Go Projects:

go run github.com/Goldziher/ai-rulez/cmd@latest init

🔧 Global Installation

For teams and frequent usage:

Homebrew (Recommended for macOS/Linux)

brew install goldziher/tap/ai-rulez
ai-rulez init "My Project"
ai-rulez enforce --agent claude

npm (Best for Node.js teams)

npm install -g ai-rulez

pip (Best for Python teams)

pip install ai-rulez

Go (For Go developers)

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

Pre-commit Hooks

You can use ai-rulez with pre-commit to automatically validate and generate your AI configuration files.

Add the following to your .pre-commit-config.yaml:

repos:
  - repo: https://github.com/Goldziher/ai-rulez
    rev: v2.2.1
    hooks:
      - id: ai-rulez-validate
      - id: ai-rulez-generate

Documentation

Quick Start Guide
Full CLI Reference
Configuration Guide
Migration Guide - Upgrading from v1.x to v2.0

Contributing

Contributions are welcome! Please see the Contributing Guide to get started.

ai-rulez

Package Exports

Readme

ai-rulez ⚡

The Complete AI Development Platform

🚀 Two Powerful Capabilities

Why AI-Rulez?

⚠️ The Problem

✨ The Solution

📖 Read the Full Documentation

🚀 Core Capabilities

1. 📋 Universal Configuration Management

2. 🤖 AI-Powered Rule Enforcement

How It Works

Example: ai-rulez.yml

⚡ Quick Start

📋 Configuration Management

🤖 AI-Powered Rule Enforcement

🗂️ .gitignore Management

🤖 AI-Powered Rule Enforcement

✨ Key Benefits

🎯 Real-World Use Cases

📊 Output Formats & Integration

🔄 Advanced Workflows

MCP Server Integration

Automatic CLI Configuration

Hybrid Configuration

Control Options

Built-in MCP Server

AI-Powered Rule Enforcement

Basic Enforcement

Advanced Enforcement Options

Supported AI Agents

Enforcement Levels

Integration with Git Hooks

Review Workflow

📦 Installation

🚀 Quick Start (No Installation)

🔧 Global Installation

Pre-commit Hooks

Documentation

Contributing

Example: `ai-rulez.yml`