agents-md
Creates or revises AGENTS.md files based on code evidence. Ensures instructions are correct without altering original intent.
What it does
This tool helps create or improve a file called AGENTS.md. This file contains instructions for an AI agent on how to make correct changes in a programming project, using information from the project itself.
When to use it
- ✓When you want to create a new AGENTS.md file.
- ✓When existing instructions in AGENTS.md are outdated.
- ✓When you want to ensure agent instructions follow project rules.
Example of what to ask your AI
“Create an AGENTS.md for this project, focusing on build and test instructions.”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
The tool reads the project's files to understand how it works. Then, it writes or adjusts AGENTS.md based on this information, ensuring the instructions are accurate and useful for the AI agent.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add sickn33/agentic-awesome-skills --skill agents-mdOr download just the file:
curl -L https://raw.githubusercontent.com/sickn33/agentic-awesome-skills/main/plugins/agentic-awesome-skills-claude/skills/agents-md/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Maintain AGENTS.md from repository evidence
Overview
Create or improve agent instructions that help a coding agent change the repository correctly without rediscovering its workflow. Base every repository-specific command, path, and rule on evidence in the current checkout.
Prefer a focused diff over a wholesale rewrite. There is no universal line limit, required section list, symlink layout, or commit-attribution policy; follow the repository's own needs and maintainer intent.
When to Use
- The user asks to create, update, shorten, or audit
AGENTS.md. - A monorepo needs root instructions plus narrower package-level overrides.
- Existing agent instructions contain stale commands, duplicated policy, or unsupported claims.
- The user wants to reconcile
AGENTS.mdwithCLAUDE.md,.github/copilot-instructions.md, or other repository instruction files.
Use @agents-generator instead when the task specifically calls for its
packaged generation modes, assets, or backup workflow. Use this skill when a
maintainer-readable, evidence-first edit is the primary goal.
How It Works
1. Preserve existing intent
Before writing, read every instruction file that applies to the target path,
including existing AGENTS.md files and relevant tool-specific files such as
CLAUDE.md, GEMINI.md, .github/copilot-instructions.md, and
.github/instructions/*.instructions.md.
- Improve an existing
AGENTS.mdin place when possible. - Preserve accurate maintainer-authored rules and repository-specific policy.
- Do not replace another tool's instruction file with a symlink unless the user requests it and repository evidence shows identical content is desired.
- Do not silently choose between conflicting instructions. Follow the higher-priority applicable rule, or ask when the intended policy cannot be established from the repository.
2. Build a bounded evidence map
Inspect only enough of the repository to establish how work is actually done:
- Read the project overview and contribution guidance, such as
README*,CONTRIBUTING*, and relevant docs. - Read manifests, lockfiles, workspace files, task runners, and build config to identify supported tools and exact commands.
- Read CI workflows to learn required checks. Do not assume every CI or deployment job is safe or appropriate to run locally.
- Inspect representative source and test files for naming, layout, and test conventions.
- Identify generated files, migrations, vendored code, large fixtures, secrets boundaries, and production-only operations.
Prefer rg --files and rg for discovery when available. Track the source of
each non-obvious command or rule so unsupported claims do not enter the final
file.
3. Choose the instruction scope
Use the root AGENTS.md for repository-wide guidance. Add or revise a nested
AGENTS.md only when a subtree has materially different commands,
architecture, conventions, or safety boundaries.
Keep shared rules at the root and only differences in nested files. For tools that implement the public AGENTS.md convention, apply root/ancestor guidance and narrower subtree instructions according to the target host's precedence. The nearest file does not silently erase unrelated ancestor rules. Do not copy the full root file into every package.
4. Write high-signal guidance
Choose headings that fit the repository instead of forcing a fixed template. Include the following only when supported by evidence:
- Repository map: the few directories and boundaries an agent must know.
- Setup and commands: exact install, development, build, lint, type-check, and test commands, with the working directory when it is not obvious.
- Focused validation: targeted checks for a small change and broader checks required before handoff.
- Change rules: generated-file ownership, migrations, schemas, APIs, dependencies, and cross-package coordination.
- Safety boundaries: secrets, production data, destructive commands, deployments, and operations that require explicit authorization.
- Contribution rules: repository-specific naming, formatting, commit, or pull-request requirements that affect implementation or handoff.
Write direct, testable statements. Prefer:
- From the repository root, run `npm test -- path/to/file.test.ts` for a focused test.
over:
- Make sure tests pass and follow best practices.
…
FAQ
What is an AGENTS.md?
It's a file containing specific instructions for an AI agent, telling it how to interact with and make changes to a programming project.
Why is it important to have an updated AGENTS.md?
An updated AGENTS.md ensures the AI agent follows the project's correct rules and commands, preventing errors and rework.
Does this tool replace the programmer's work?
No, it helps create clear instructions so an AI agent can assist the programmer by following project guidelines.
Details
Original description by the author
Create, revise, or audit AGENTS.md files from repository evidence, verified commands, and correctly scoped instructions without overwriting maintainer intent.
Popularity
- GitHub stars
- 48k
- Ranking position
- #2076
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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