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taniwhaai/arai

by Various

AI coding rules that actually work. Enforce instruction files via hooks — CLAUDE.md, .cursorrules, copilot-instructions, and more.

T

MCP

taniwhaai/arai

Added 1 June 2026

#ai-guardrails #claude-code #cli #code-quality #copilot #cursor-rules #developer-tools #grok

Overview

A Rust-based tool that enforces AI coding instruction files across multiple assistants using pre-commit hooks. It manages rules for CLAUDE.md, .cursorrules, copilot-instructions and similar files to ensure consistent behavior.

Best for

Best for
Developers who want consistent AI coding rules across Claude, Cursor, and Copilot

Use cases

  • Standardize AI assistant instructions across a team
  • Enforce project-specific coding rules via hooks
  • Sync rule files for Claude, Cursor, and GitHub Copilot

How to use

Install

curl -sSf https://arai.taniwha.ai/install | sh

Tools exposed

  • tree-sitter

Tested with

Claude Code, Grok TUI, Cursor, Windsurf, GitHub Copilot

Notes

A Rust-based tool that enforces AI coding instruction files across multiple assistants using pre-commit hooks. It manages rules for CLAUDE.md, .cursorrules, copilot-instructions and similar files to ensure consistent behavior.

5 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.

Use cases

  • Standardize AI assistant instructions across a team
  • Enforce project-specific coding rules via hooks
  • Sync rule files for Claude, Cursor, and GitHub Copilot

Pros

  • Lightweight Rust binary with no heavy dependencies
  • Centralizes rule management for multiple AI tools
  • Uses standard pre-commit hooks for easy integration

Cons

  • Very early-stage project with only 5 GitHub stars
  • Limited documentation or community support
  • Requires manual setup of hook scripts

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Lightweight Rust binary with no heavy dependencies
  • Centralizes rule management for multiple AI tools
  • Uses standard pre-commit hooks for easy integration

Cons

  • Very early-stage project with only 5 GitHub stars
  • Limited documentation or community support
  • Requires manual setup of hook scripts
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