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Create Agentsmd

OrganizationPopular
github
create-agentsmd

Prompt for generating an AGENTS.md file for a repository

Overview

Publishergithub
Repositoryawesome-copilot
Skill namecreate-agentsmd
Stars
39.6K
Forks
5K
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by github on GitHub. Read the source before you install it.

Installation

Install the Create Agentsmd AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/github/awesome-copilot/tree/main/skills/create-agentsmd
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/github/awesome-copilot.git /tmp/awesome-copilot
mkdir -p .claude/skills
cp -r /tmp/awesome-copilot/skills/create-agentsmd .claude/skills/create-agentsmd
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Agentsmd in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Create Agentsmd on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Create Agentsmd is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Create high‑quality AGENTS.md file

You are a code agent. Your task is to create a complete, accurate AGENTS.md at the root of this repository that follows the public guidance at https://agents.md/.

AGENTS.md is an open format designed to provide coding agents with the context and instructions they need to work effectively on a project.

What is AGENTS.md?

AGENTS.md is a Markdown file that serves as a "README for agents" - a dedicated, predictable place to provide context and instructions to help AI coding agents work on your project. It complements README.md by containing detailed technical context that coding agents need but might clutter a human-focused README.

Key Principles

  • Agent-focused: Contains detailed technical instructions for automated tools
  • Complements README.md: Doesn't replace human documentation but adds agent-specific context
  • Standardized location: Placed at repository root (or subproject roots for monorepos)
  • Open format: Uses standard Markdown with flexible structure
  • Ecosystem compatibility: Works across 20+ different AI coding tools and agents

File Structure and Content Guidelines

1. Required Setup

  • Create the file as AGENTS.md in the repository root
  • Use standard Markdown formatting
  • No required fields - flexible structure based on project needs

2. Essential Sections to Include

Project Overview
  • Brief description of what the project does
  • Architecture overview if complex
  • Key technologies and frameworks used
Setup Commands
  • Installation instructions
  • Environment setup steps
  • Dependency management commands
  • Database setup if applicable
Development Workflow
  • How to start development server
  • Build commands
  • Watch/hot-reload setup
  • Package manager specifics (npm, pnpm, yarn, etc.)
Testing Instructions
  • How to run tests (unit, integration, e2e)
  • Test file locations and naming conventions
  • Coverage requirements
  • Specific test patterns or frameworks used
  • How to run subset of tests or focus on specific areas
Code Style Guidelines
  • Language-specific conventions
  • Linting and formatting rules
  • File organization patterns
  • Naming conventions
  • Import/export patterns
Build and Deployment
  • Build commands and outputs
  • Environment configurations
  • Deployment steps and requirements
  • CI/CD pipeline information

3. Optional but Recommended Sections

Security Considerations
  • Security testing requirements
  • Secrets management
  • Authentication patterns
  • Permission models
Monorepo Instructions (if applicable)
  • How to work with multiple packages
  • Cross-package dependencies
  • Selective building/testing
  • Package-specific commands
Pull Request Guidelines
  • Title format requirements
  • Required checks before submission
  • Review process
  • Commit message conventions
Debugging and Troubleshooting
  • Common issues and solutions
  • Logging patterns
  • Debug configuration
  • Performance considerations

Example Template

Use this as a starting template and customize based on the specific project:

markdown
# AGENTS.md

## Project Overview

[Brief description of the project, its purpose, and key technologies]

## Setup Commands

- Install dependencies: `[package manager] install`
- Start development server: `[command]`
- Build for production: `[command]`

## Development Workflow

- [Development server startup instructions]
- [Hot reload/watch mode information]
- [Environment variable setup]

## Testing Instructions

- Run all tests: `[command]`
- Run unit tests: `[command]`
- Run integration tests: `[command]`
- Test coverage: `[command]`
- [Specific testing patterns or requirements]

## Code Style

- [Language and framework conventions]
- [Linting rules and commands]
- [Formatting requirements]
- [File organization patterns]

## Build and Deployment

- [Build process details]
- [Output directories]
- [Environment-specific builds]
- [Deployment commands]

## Pull Request Guidelines

- Title format: [component] Brief description
- Required checks: `[lint command]`, `[test command]`
- [Review requirements]

## Additional Notes

- [Any project-specific context]
- [Common gotchas or troubleshooting tips]
- [Performance considerations]

Working Example from agents.md

Here's a real example from the agents.md website:

markdown
# Sample AGENTS.md file

## Dev environment tips

- Use `pnpm dlx turbo run where <project_name>` to jump to a package instead of scanning with `ls`.
- Run `pnpm install --filter <project_name>` to add the package to your workspace so Vite, ESLint, and TypeScript can see it.
- Use `pnpm create vite@latest <project_name> -- --template react-ts` to spin up a new React + Vite package with TypeScript checks ready.
- Check the name field inside each package's package.json to confirm the right name—skip the top-level one.

## Testing instructions

- Find the CI plan in the .github/workflows folder.
- Run `pnpm turbo run test --filter <project_name>` to run every check defined for that package.
- From the package root you can just call `pnpm test`. The commit should pass all tests before you merge.
- To focus on one step, add the Vitest pattern: `pnpm vitest run -t "<test name>"`.
- Fix any test or type errors until the whole suite is green.
- After moving files or changing imports, run `pnpm lint --filter <project_name>` to be sure ESLint and TypeScript rules still pass.
- Add or update tests for the code you change, even if nobody asked.

## PR instructions

- Title format: [<project_name>] <Title>
- Always run `pnpm lint` and `pnpm test` before committing.

Implementation Steps

  1. Analyze the project structure to understand:

    • Programming languages and frameworks used
    • Package managers and build tools
    • Testing frameworks
    • Project architecture (monorepo, single package, etc.)
  2. Identify key workflows by examining:

    • package.json scripts
    • Makefile or other build files
    • CI/CD configuration files
    • Documentation files
  3. Create comprehensive sections covering:

    • All essential setup and development commands
    • Testing strategies and commands
    • Code style and conventions
    • Build and deployment processes
  4. Include specific, actionable commands that agents can execute directly

  5. Test the instructions by ensuring all commands work as documented

  6. Keep it focused on what agents need to know, not general project information

Best Practices

  • Be specific: Include exact commands, not vague descriptions
  • Use code blocks: Wrap commands in backticks for clarity
  • Include context: Explain why certain steps are needed
  • Stay current: Update as the project evolves
  • Test commands: Ensure all listed commands actually work
  • Consider nested files: For monorepos, create AGENTS.md files in subprojects as needed

Monorepo Considerations

For large monorepos:

  • Place a main AGENTS.md at the repository root
  • Create additional AGENTS.md files in subproject directories
  • The closest AGENTS.md file takes precedence for any given location
  • Include navigation tips between packages/projects

Final Notes

  • AGENTS.md works with 20+ AI coding tools including Cursor, Aider, Gemini CLI, and many others
  • The format is intentionally flexible - adapt it to your project's needs
  • Focus on actionable instructions that help agents understand and work with your codebase
  • This is living documentation - update it as your project evolves

When creating the AGENTS.md file, prioritize clarity, completeness, and actionability. The goal is to give any coding agent enough context to effectively contribute to the project without requiring additional human guidance.

Frequently asked questions

What does the Create Agentsmd AI skill do?

Prompt for generating an AGENTS.md file for a repository

Why use Create Agentsmd on TypingMind?

Because you install it once and use it with any model. Create Agentsmd is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Create Agentsmd in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/github/awesome-copilot/tree/main/skills/create-agentsmd. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Create Agentsmd?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Create Agentsmd?

As many as you like. As long as a model supports skills, you can use Create Agentsmd with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Create Agentsmd AI skill free?

Yes. It is published on GitHub by github under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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