create-agents-md

siviter-xyz/dot-agent · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/siviter-xyz/dot-agent --skill create-agents-md
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summary

Guide for creating AGENTS.md files for project-specific inline rules.

skill.md

Create AGENTS.md

Guide for creating AGENTS.md files for project-specific inline rules.

When to Use AGENTS.md

  • Small, project-specific instructions that should be committed in the repo
  • Folder-scoped rules for specific directories
  • Package-specific instructions in monorepos
  • Test-specific guidance in test directories

When NOT to Use AGENTS.md

  • Reusable knowledge across projects → Use skills
  • Large documentation → Use skills with references
  • Complex workflows → Use skills with scripts

AGENTS.md Structure

AGENTS.md is a simple markdown file without metadata:

# Project Instructions

## Code Style

- Use TypeScript for all new files
- Prefer functional components in React
- Use snake_case for database columns

## Architecture

- Follow the repository pattern
- Keep business logic in service layers

Location

  • Project root: AGENTS.md – Primary, inline instructions and references for the whole project (commands, tech stack, testing, code style, architecture, safety boundaries).
  • Subdirectories: subdirectory/AGENTS.md – Folder- or package-scoped instructions when local behavior meaningfully diverges from the root (e.g., a specific package, service, or test tree).
  • Nested support: Agents typically combine instructions from the closest AGENTS.md with parent ones; keep root general and use nested AGENTS.md only where you truly need more specific rules.

Best Practices

  • Keep AGENTS.md files small and focused
  • Use for project-specific conventions
  • Prefer short, concrete references over long prose:
    • Link to project docs, specs, and runbooks
    • Point to example files or directories (e.g., see src/api/users.ts for canonical pattern)
    • Include the most important commands with exact CLI invocations
  • Reference existing code examples when possible
  • Update as project evolves

References

For detailed best practices, see references/best-practices.md.

how to use create-agents-md

How to use create-agents-md 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-agents-md
2

Execute installation command

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

$npx skills add https://github.com/siviter-xyz/dot-agent --skill create-agents-md

The skills CLI fetches create-agents-md from GitHub repository siviter-xyz/dot-agent 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-agents-md

Reload or restart Cursor to activate create-agents-md. Access the skill through slash commands (e.g., /create-agents-md) 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

4.660 reviews
  • Jin Jain· Dec 28, 2024

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

  • Diya Sharma· Dec 24, 2024

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

  • Li Rao· Dec 24, 2024

    Solid pick for teams standardizing on skills: create-agents-md is focused, and the summary matches what you get after install.

  • Tariq Garcia· Dec 16, 2024

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

  • Chaitanya Patil· Dec 8, 2024

    Useful defaults in create-agents-md — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Piyush G· Nov 27, 2024

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

  • Diya Zhang· Nov 19, 2024

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

  • Tariq Reddy· Nov 15, 2024

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

  • Diya Li· Nov 7, 2024

    Useful defaults in create-agents-md — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Diya Thomas· Oct 26, 2024

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

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