Free AGENTS.md Generator

What is an AGENTS.md File?

An AGENTS.md file is an open, vendor-neutral Markdown specification placed in the root of a software repository to provide operational context for autonomous AI coding agents. While a human-oriented README.md explains marketing benefits and installation steps for developers, an AGENTS.md file provides structured guidelines specifically tailored for machine comprehension.

Stewarded by the open Agentic AI Foundation, the specification outlines deterministic build commands, testing instructions, directory layouts, coding conventions, and operational boundaries. By codifying repository context in a single file, engineering teams eliminate guesswork and prevent AI coding agents from generating hallucinated scripts or altering unauthorized modules.

All processing in this tool happens directly in your browser using client-side JavaScript. No project names, code snippets, or configuration secrets leave your computer, ensuring complete data privacy for commercial and open-source projects alike.

Why AI Coding Agents Need an AGENTS.md Specification

Autonomous AI agents such as Cursor, Claude Code, Aider, and GitHub Copilot are increasingly tasked with multi-step development tickets, refactoring, and bug fixing. However, when an agent lands in an unfamiliar codebase, it faces three critical challenges:

• Command Ambiguity: Projects use diverse package managers (pnpm, uv, cargo) and scripts. Without guidance, agents may run destructive package upgrades or run the wrong test suite.
• Architectural Blind Spots: Modern monorepos and microservices feature complex folder hierarchies. AGENTS.md provides an explicit directory map so agents locate entry points instantly.
• Missing Guardrails: Without clear boundaries, agents might hardcode secrets, delete unit tests to make a build pass, or introduce formatting that violates company style guides.

By generating a comprehensive AGENTS.md file, you establish a reliable source of truth that empowers agents to execute tasks autonomously while strictly observing your development policies. Pair this with our AI Agent Prompt Generator and Token Counter to optimize your repository prompt budgets.

Key Components of an Effective AGENTS.md File

A production-ready AGENTS.md specification balances thorough context with token efficiency. The most critical sections include:

• Project Overview & Tech Stack: A concise definition of the application architecture, runtime version, database layer, and primary package manager.
• Essential Commands Table: Copy-pasteable terminal commands for installation, local development servers, production builds, test runs, and static linting.
• Codebase Directory Structure: An annotated folder tree highlighting primary modules, API routes, reusable UI components, and test directories.
• Coding Standards & Conventions: Architectural paradigms, typing discipline (e.g., strict TypeScript), naming patterns, and error handling protocols.
• Testing & Verification Policies: Mandatory test commands, mocking expectations, minimum coverage thresholds, and pre-commit verification steps.
• Agent Guardrails & Boundaries: Strict lists of prohibited actions (e.g., never commit secrets, never modify production database schemas without confirmation).

How to Use This AGENTS.md Generator (Step-by-Step)

Generating a complete specification for your repository takes less than two minutes:

• Choose a Preset or Blank Template: Select an existing stack preset (such as Next.js, FastAPI, Node.js Express, Go, or Rust) from the top dropdown to load realistic commands, or fill out fields manually.
• Select Your Output Format: Choose between the open AGENTS.md specification, Anthropic CLAUDE.md, Cursor .cursorrules, or GitHub Copilot format.
• Customize Commands and Directory Map: Review and update the installation, build, lint, and test scripts to match your package.json, Makefile, or pyproject.toml.
• Set Agent Boundaries and Guardrails: Specify any files the agent must not modify, required test coverage thresholds, and mandatory verification checks.
• Check Your Readiness Score & Export: Confirm your Agent Readiness Score exceeds 80%, then click Copy or Download to save the file to your repository root.

Best Practices for Writing AI Agent Guardrails

Writing effective guardrails requires moving beyond vague instructions like "write clean code". Follow these five battle-tested rules when configuring your AGENTS.md file:

• Specify Verification Commands: Always instruct the agent to run your specific test and lint commands before declaring a ticket complete. For example: "Run pnpm test:run and pnpm lint prior to concluding work."
• Enforce Secrets Hygiene: Explicitly forbid committing hardcoded secrets, API tokens, or environment credentials into version control.
• Protect Critical Assets: List off-limits files such as production migration histories, deployment credentials, or third-party vendored packages.
• Limit Scope Creep: Instruct the agent to keep file diffs minimal and avoid refactoring adjacent components unrelated to the prompt ticket.
• Balance Token Usage: Keep instructions under 1,500 tokens. Use our AI Agent Workflow Builder and AI Agent Risk Scorer to design secure agent pipelines.

Frequently Asked Questions (FAQs)

What is an AGENTS.md file and what is it used for?

An AGENTS.md file is a vendor-neutral Markdown specification placed at the root of a code repository. It acts as an operational README specifically written for autonomous AI coding agents, providing concise context on tech stacks, build commands, testing instructions, directory layouts, and behavioral guardrails so agents can navigate codebases without guessing.

How does AGENTS.md differ from CLAUDE.md and .cursorrules?

AGENTS.md is an open, vendor-neutral standard stewarded by the Agentic AI Foundation and supported across diverse coding assistants. In contrast, CLAUDE.md is tailored specifically for Anthropic's Claude Code CLI, and .cursorrules is used primarily by the Cursor IDE. This generator allows you to scaffold for the open AGENTS.md standard or export directly to CLAUDE.md and .cursorrules formats.

Does my code or repository data leave the browser?

No. All generation, formatting, scoring, and file exports happen 100% locally in your browser via client-side JavaScript. No project data, code snippets, or configuration values are transmitted to external servers.

Can I use multiple AGENTS.md files in a monorepo?

Yes. The AGENTS.md specification supports hierarchical placement. You can maintain a root AGENTS.md for global repository conventions, and place package-specific AGENTS.md files inside individual subdirectories (such as packages/api or apps/web) to provide localized commands and instructions for sub-projects.

What are the most important sections to include in AGENTS.md?

The most critical sections are: (1) Exact build, test, and lint commands, (2) Technology stack and package manager, (3) Key directory map and entry points, (4) Coding style and testing policies, and (5) Strict agent guardrails detailing prohibited actions and required pre-completion checks.

How long should an AGENTS.md file be?

An effective AGENTS.md file should be lean and focused, typically between 300 and 1,200 words (approximately 500 to 2,000 LLM tokens). Overly verbose documentation wastes context window capacity and can dilute agent attention away from essential operational constraints.

Should AGENTS.md be committed to version control?

Yes. AGENTS.md is designed to be committed to your Git repository alongside your codebase. This ensures all team members and AI coding assistants share identical operational guidance, and changes to build commands or architecture can be tracked through normal pull requests.

Which AI coding agents and tools support AGENTS.md?

AGENTS.md is recognized by an expanding ecosystem of tools, including Cursor, Aider, GitHub Copilot, Gemini CLI, Claude Code (via imports), Devin, Windsurf, and custom autonomous agent pipelines implementing the Agentic AI Foundation specification.