Which Tools Read AGENTS.md?

The emergence of standardized project documentation for artificial intelligence has led many developers to wonder which tools read AGENTS.md. This file serves as a dedicated instruction manual for autonomous agents, providing them with project context, architectural rules, and specific constraints that might not be obvious from the source code alone. By adopting a standard file format like AGENTS.md, teams can ensure that different AI assistants behave consistently regardless of the specific interface or IDE being used.

The Purpose of AGENTS.md in Modern Development

Documentation has traditionally been written for humans. Readme files, wikis, and inline comments explain the why and how of a codebase to other developers. However, as AI agents become more integrated into the development lifecycle, there is a clear need for documentation optimized for machine consumption.

The AGENTS.md file acts as a bridge. It typically contains high level goals, preferred library patterns, and explicit "do not" rules. When an agent initializes within a directory, it looks for this file to understand its boundaries. This prevents the agent from refactoring a legacy module that should remain untouched or from introducing a new dependency that violates the project architecture.

Current Landscape of AGENTS.md Support

Support for AGENTS.md is growing among tools that prioritize agentic workflows. Because the format is relatively new, implementation varies between full native support and secondary recognition through general context windows.

CLI Based Agents

Command line interfaces are currently the primary adopters of this standard. Tools like Claude Code are designed to be environment aware. When you launch a CLI agent in a repository, the first thing it often does is index the file structure. If an AGENTS.md file is present, the agent incorporates those instructions into its system prompt or initial context.

This approach is highly effective because it requires no manual configuration. The agent simply discovers the file and adjusts its behavior accordingly. This makes AGENTS.md a portable configuration that stays with the repository, ensuring every contributor using a compatible CLI agent receives the same level of assistance.

Desktop Workspaces and IDEs

Traditional IDEs usually rely on plugins to handle AI context. These plugins may or may not look for specific markdown files beyond the standard README.md. However, a new category of developer tools is emerging that treats agents as first class citizens.

Deska represents this new approach. It functions as an infinite canvas where you can run multiple agents like Claude Code, Codex CLI, and OpenCode side by side. Since Deska is designed around the idea of coding agents, it provides the necessary environment for these agents to access local files including AGENTS.md. Because Deska is local-first, the interaction between the agent and your documentation happens entirely on your machine.

Comparison of Tool Approaches

How to Structure Your AGENTS.md

To ensure the highest compatibility with tools that read AGENTS.md, the file should be structured logically. AI agents process markdown headers efficiently, so using a clear hierarchy is essential.

• Project Identity: A brief description of what the software does.
• Tech Stack: Specific versions of languages and frameworks to avoid hallucinated syntax.
• Architectural Rules: Patterns the agent must follow, such as "use functional components only" or "all database queries must use the existing repository pattern."
• Tooling Constraints: Instructions on which commands are safe to run and which should be avoided.
• Communication Style: How the agent should report progress or ask for clarification.

Leveraging Deska for Agent Orchestration

Deska provides a unique environment for testing how different agents interpret your AGENTS.md instructions. On the canvas, you can open multiple terminals as panels and run different agents simultaneously. This allows you to compare how Claude Code might interpret a rule versus how another CLI tool handles the same instruction.

One of the strengths of Deska is the ability to maintain agent threads alongside your code and terminals. If you find that an agent is consistently ignoring a rule in your AGENTS.md, you can update the file in the built-in Monaco editor and immediately restart the agent session to see the changes take effect.

The Ask Deska assistant also benefits from this local context. It can help you organize your workspace or find specific files that your agents need to modify. By keeping everything in a single, zoomable interface, you reduce the cognitive load of switching between the terminal and the editor.

Security and Privacy in Local Environments

When using agents that read local files, security is a primary concern. Many developers are hesitant to upload their entire codebase to cloud services. This is why tools that prioritize privacy and local execution are gaining traction.

Deska ensures that your code and AGENTS.md files remain on your hardware. Even when using the mobile app to monitor your work, the connection is established through a secure relay that pairs devices directly without exposing ports. This means you can give your agents full access to your project documentation without worrying about data leakage to a third party platform.

Frequently Asked Questions

Does GitHub Copilot read AGENTS.md?

GitHub Copilot primarily uses the files you have open in your editor and the general repository structure to gather context. While it may index AGENTS.md as part of its background processing, it does not currently treat it as a formal set of system instructions in the same way dedicated agentic CLI tools do.

Can I use AGENTS.md for custom prompts?

Yes. You can use AGENTS.md to store complex prompts that you frequently use with different models. By pointing an agent to this file, you save time and ensure that your prompts are version controlled alongside your source code.

What is the difference between README.md and AGENTS.md?

A README.md is designed for human onboarding and general project overview. An AGENTS.md is specifically for AI behavior. It often contains more technical constraints, specific file paths to ignore, and explicit instructions on how the AI should write code or execute terminal commands.

Getting Started with Agentic Workflows

Adopting AGENTS.md is a low effort, high reward step toward better AI integration. It allows you to define the "rules of the road" for any assistant you bring into your project. Whether you are running a single CLI agent or orchestrating a complex multi agent setup, having a central source of truth for AI behavior is invaluable.

If you are looking for a workspace that natively supports these workflows with a local-first philosophy, consider trying Deska. You can download the app for Mac, Windows, or Linux to start building your own infinite canvas of agents and tools. Experiment with different configurations on the canvas and see how a well defined AGENTS.md can transform your development speed.