AI Rules Manager – Package manager for AI coding assistant rules
I built ARM (AI Rules Manager) to solve a problem that's been bugging me: managing AI rules across projects is broken. If you use Cursor, GitHub Copilot, or Amazon Q, you know how powerful custom rules can be for guiding AI behavior. But right now, everyone just copies `.cursorrules` files around manually. Once copied, they're orphaned – no updates, no version control, no way to know if changes will break your AI's behavior. ARM treats AI rules like npm packages. You can: - Install versioned rulesets: arm install awesome-cursorrules/python - Connect to Git registries like…
In plain words
AI Rules Manager is a package manager for AI coding assistant rules that works with Cursor, GitHub Copilot, and Amazon Q. Instead of manually copying and maintaining `.cursorrules` files across projects, it treats AI rules as versioned dependencies that can be installed, updated, and synced like npm packages. Users can install rulesets from Git registries, keep rules synchronized across projects with semantic versioning, and target multiple AI tools with different configurations. The tool solves the problem of orphaned rule files by enabling centralized management and automatic updates.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
I built ARM (AI Rules Manager) to solve a problem that's been bugging me: managing AI rules across projects is broken. If you use Cursor, GitHub Copilot, or Amazon Q, you know how powerful custom rules can be for guiding AI behavior. But right now, everyone just copies `.cursorrules` files around manually. Once copied, they're orphaned – no updates, no version control, no way to know if changes will break your AI's behavior. ARM treats AI rules like npm packages. You can: - Install versioned rulesets: arm install awesome-cursorrules/python - Connect to Git registries like PatrickJS/awesome-cursorrules - Keep rules synced across projects with semantic versioning - Target multiple AI tools (Cursor, Copilot, Amazon Q) with different layouts The key insight: AI rules should be dependencies, not copy-pasted files. When the awesome-cursorrules repo updates their Python rules, you want to choose when and how to upgrade, just like any other dependency. Quick example: --------------------------- # Connect to a registry arm config registry add awesome-cursorrules https://github.com/PatrickJS/awesome-cursorrules --type git # Install Python rules to Cursor arm config sink add cursor --directories .cursor/rules arm install awesome-cursorrules/python # Later, update when you're ready arm update awesome-cursorrules/python ---------------------------- It creates arm.json and arm-lock.json files (like package.json/package-lock.json) so your whole team gets the same AI behavior. One-liner install: curl -fsSL https://raw.githubusercontent.com/jomadu/ai-rules-manager/ma... | bash GitHub: https://github.com/jomadu/ai-rules-manager Would love feedback from other folks dealing with AI rule management chaos!
Does the same job
all alternatives →
- CACursor AI Rules Directory (Open Source)2024 · cursor.directory · ▲51
While Cursor has already revolutionized coding, you can still configure it to perform even better based on your language and framework. That's why we created Cursor Directory, a collection of the best cursor rules for your framework and language from the community. It's fully open source and you can contribute to it by submitting your own rules. Just copy and add a .cursorrules file to your project root! Let me know what you think!
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- APA package manager for AI plugins2023 · openpm.ai · ▲82
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