create-agentsmd

github/awesome-copilot · updated Apr 8, 2026

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$npx skills add https://github.com/github/awesome-copilot --skill create-agentsmd
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summary

Generates standardized AGENTS.md files to help AI coding agents understand and work with your repository.

  • Provides a template-driven approach for creating agent-focused documentation that complements README.md with technical setup, workflow, and testing instructions
  • Covers essential sections including project overview, setup commands, development workflow, testing, code style, build/deployment, and PR guidelines
  • Supports monorepo structures with guidance for creating AGENTS.md files
skill.md

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:

# 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:

# 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.

how to use create-agentsmd

How to use create-agentsmd on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add create-agentsmd
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/github/awesome-copilot --skill create-agentsmd

The skills CLI fetches create-agentsmd from GitHub repository github/awesome-copilot and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/create-agentsmd

Reload or restart Cursor to activate create-agentsmd. Access the skill through slash commands (e.g., /create-agentsmd) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.672 reviews
  • Pratham Ware· Dec 20, 2024

    create-agentsmd reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Charlotte Johnson· Dec 20, 2024

    create-agentsmd reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noah Martinez· Dec 20, 2024

    Keeps context tight: create-agentsmd is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aarav Anderson· Dec 16, 2024

    create-agentsmd is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Olivia Park· Dec 16, 2024

    I recommend create-agentsmd for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Min Huang· Dec 16, 2024

    create-agentsmd has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Charlotte Thompson· Dec 4, 2024

    Keeps context tight: create-agentsmd is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Zara Thompson· Nov 23, 2024

    We added create-agentsmd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Anaya Jain· Nov 19, 2024

    Registry listing for create-agentsmd matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Henry Gonzalez· Nov 11, 2024

    We added create-agentsmd from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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