I’m excited to announce the release of AIM (AI Agent Instruction Modules) v0.7.0! This project is now available on GitHub and provides a standardized approach to managing AI agent instructions across codebases.

The Problem

Working with AI coding agents like GitHub Copilot, Claude, Cursor, and others is powerful, but each project often needs custom instructions to work effectively. Managing these instructions can be inconsistent—they might be scattered across .claude, .cursorrules, CLAUDE.md, COPILOT.md, or various other locations.

Consider a typical scenario: Your team has 10 repositories. In repository A, you’ve created a .claude file with your coding standards. In repository B, someone used .cursorrules for Cursor. Repository C has a plain text COPILOT.md file. Repository D has nothing. When you update a best practice, you need to manually update all of them. This fragmentation makes it hard to:

• Maintain consistent practices across projects
• Share best practices between teams
• Keep instructions up-to-date across multiple repositories
• Ensure all team members use the same agent guidance

The Solution

AIM is a modular, opt-in collection of instruction modules that work with all major AI coding agents through the standardized agents.md format. The agents.md standard is an open specification for AI agent instructions, supported by GitHub Copilot, Claude, Cursor, Windsurf, and other popular coding agents. By leveraging this standard, AIM ensures your instructions work reliably across all these platforms without vendor lock-in. It provides:

Core Features

• 12+ Instruction Modules: Covering workflows, standards, and best practices
• Language & Tool Specific Modules: PowerShell, Markdown, GitHub CLI, and more
• Repository Management: Release procedures, version control, and contribution guidelines
• Easy Deployment: Simple setup with templates and deployment procedures
• Customizable: Extend with repository-specific instructions while staying synchronized

What AIM Includes

Core Modules

• Agent Workflow - Pre-flight protocol for AI agents to follow
• Shorthand - Guidelines for avoiding abbreviations in code
• Git Workflow - Branching, commits, and pull request conventions
• Testing - Test writing best practices and conventions

Language & Tool Modules

• PowerShell - Cmdlet naming, parameter conventions, and scripting best practices
• Markdown - Documentation formatting and structure guidelines
• README - README maintenance guidelines
• GitHub CLI - Efficient PR and issue management workflows

Repository Management

• Releases - Release management with semantic versioning
• Update - Procedures for keeping downstream repositories current
• Contributing - Workflow for contributing improvements upstream

Quick Start

Head over to the AIM GitHub repository for complete setup instructions. The README includes:

• Automated Deployment - Copy a prompt into your AI agent for fully automated setup
• Manual Alternative - Step-by-step instructions if you prefer to set things up manually
• Updating Instructions - How to keep your instructions synchronized with the latest releases
• Repository Structure - Complete overview of all included modules

The documentation is kept up-to-date with each release, ensuring you always have the latest deployment procedures and prompts.

Who Should Use AIM?

AIM is ideal for:

• Teams managing multiple repositories - Standardize practices across your entire codebase
• Organizations standardizing on AI agents - Ensure consistent behavior regardless of which agent team members use
• Open source projects - Provide clear guidance to contributors working with AI coding assistants
• DevOps and platform teams - Enforce standards and best practices across all downstream projects
• Solo developers - Maintain consistent standards as your projects grow
• Enterprises - Build a foundation for AI agent governance and compliance

Whether you’re starting fresh or migrating from scattered instruction files, AIM provides a proven, tested approach that grows with your needs.

Repository Structure

The project is organized as:

• Root files: AGENTS.md, CHANGELOG.md, README.md, and contribution guidelines
• instructions/ folder: 12+ modular instruction files covering workflows, languages, and tooling
• tests/ folder: Pester tests that validate instruction integrity
• CI/CD: GitHub Actions workflows for continuous validation

For a complete folder listing, see the project repository.

Community Contributions

AIM is open to community contributions! We’re looking for new instruction modules for:

• Languages: Python, TypeScript, Go, Rust, C#, and others
• Frameworks: React, FastAPI, ASP.NET, Django, and more
• Tool Integrations: Docker, Terraform, Kubernetes, and additional tools

Each module should include YAML frontmatter with applyTo patterns and follow the conventions established in existing modules. See CONTRIBUTING.md for detailed guidelines.

Why This Matters

As AI coding agents become more powerful and widely adopted, having consistent, well-documented instructions across your projects becomes critical. AIM eliminates the guesswork and provides a proven, tested foundation that you can build upon.

Whether you’re working alone or with a large team, across one project or dozens, AIM helps ensure your AI agents work effectively within your standards and practices.

Get Started Today

Visit the AIM Repository to get started. The project includes complete documentation, examples, and automated setup procedures.

Happy coding!

P.S. — This blog post was written with the help of AI. As a result, it follows best practices, passes all linting rules, and was completed in a fraction of the time it would have taken manually. Ironic? Perhaps. Fitting? Absolutely.