Generate or update a comprehensive README.md file for GitHub repositories following best practices.
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionreadme-generatorExecute the skills CLI command in your project's root directory to begin installation:
Fetches readme-generator from dmccreary/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate readme-generator. Access via /readme-generator in your agent's command palette.
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 environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Generate or update a comprehensive README.md file for GitHub repositories following best practices.
This skill automates the creation of professional, well-structured README.md files for GitHub repositories. It generates all essential sections including badges for technologies used, project overview, site metrics, getting started instructions, project structure, and contact information. The skill is particularly optimized for MkDocs-based intelligent textbook projects but can be adapted for any repository type.
Use this skill when:
Before generating the README, gather information about the repository:
.git/config or the working directorymkdocs.yml if it exists to extract:
/docs directoryUser Dialog Triggers:
Create badges for all relevant technologies and platforms. Use shields.io format for consistency.
Badge Order:
Badge Templates:
[](https://www.mkdocs.org/)
[](https://squidfunk.github.io/mkdocs-material/)
[](SITE_URL)
[](REPO_URL)
[](https://claude.ai/code)
[](https://github.com/dmccreary/claude-skills)
Check for these additional badges:
[](https://p5js.org/)[](https://www.python.org/)[](https://developer.mozilla.org/en-US/docs/Web/JavaScript)Look for license information in:
LICENSE file in rootdocs/license.mdmkdocs.yml (copyright field)Default to Creative Commons BY-NC-SA 4.0 if not specified:
[](https://creativecommons.org/licenses/by-nc-sa/4.0/)
Other common licenses:
[](https://opensource.org/licenses/MIT)[](https://opensource.org/licenses/Apache-2.0)[](https://www.gnu.org/licenses/gpl-3.0)After badges, add a prominent link to the live website (if deployed):
## View the Live Site
Visit the interactive textbook at: [https://username.github.io/repo-name](https://username.github.io/repo-name)
Create a compelling 1-3 paragraph overview that answers:
Guidelines:
Example for Intelligent Textbook:
## Overview
This is an interactive, AI-generated intelligent textbook on [TOPIC] designed for [AUDIENCE]. Built using MkDocs with the Material theme, it incorporates learning graphs, concept dependencies, interactive MicroSims (p5.js simulations), and AI-assisted content generation.
The textbook follows Bloom's Taxonomy (2001 revision) for learning outcomes and uses concept dependency graphs to ensure proper prerequisite sequencing. All content is generated and curated using Claude AI skills, making it a Level 2+ intelligent textbook with interactive elements.
Whether you're a student learning [TOPIC] for the first time or an educator looking for structured course materials, this textbook provides comprehensive coverage with hands-on interactive elements that make complex concepts accessible and engaging.
Gather and display project metrics to show completeness and scope.
Run Python script to collect metrics:
Call scripts/collect-site-metrics.py (or create it if needed) to gather:
Learning Graph Metrics (from docs/learning-graph/):
Content Metrics:
docs/chapters/).md files in docs/)Interactive Elements:
docs/sims/)quiz.md)Educational Resources:
docs/glossary.md)docs/faq.md)docs/references.md)Media Assets:
.png, .jpg, .svg files)Format as a table:
## Site Status and Metrics
| Metric | Count |
|--------|-------|
| Concepts in Learning Graph | 200 |
| Chapters | 13 |
| Markdown Files | 87 |
| Total Words | 45,230 |
| MicroSims | 12 |
| Glossary Terms | 187 |
| FAQ Questions | 42 |
| Quiz Questions | 156 |
| Images | 34 |
| References | 28 |
**Completion Status:** Approximately 85% complete (content generation phase)
Book-Specific Metrics:
For specialized textbooks, add domain-specific metrics:
Provide clear instructions for using and customizing the project.
Standard sections:
Example:
## Getting Started
### Clone the Repository
```bash
git clone https://github.com/username/repo-name.git
cd repo-name
This project uses MkDocs with the Material theme:
pip install mkdocs
pip install mkdocs-material
Build the site:
mkdocs build
Serve locally for development (with live reload):
mkdocs serve
Open your browser to http://localhost:8000
mkdocs gh-deploy
This will build the site and push it to the gh-pages branch.
Navigation:
Interactive MicroSims:
Customization:
docs/ to modify contentmkdocs.yml to change site structuredocs/sims/docs/css/extra.css
### Step 8: Document Repository Structure
Create an ASCII tree diagram showing the repository structure with explanatory comments.
**Use this approach:**
- Don't list every single file
- Show representative examples
- Add comments explaining each major directory
- Keep it concise (10-20 lines)
**Example:**
```markdown
## Repository Structure
repo-name/ ├── docs/ # MkDocs documentation source │ ├── chapters/ # Chapter content │ │ ├── 01-intro/ │ │ │ ├── index.md # Chapter markdown │ │ │ └── quiz.md # Chapter quiz │ │ └── 02-concepts/ │ ├── sims/ # Interactive p5.js MicroSims │ │ ├── graph-viewer/ │ │ │ ├── main.html # Standalone simulation │ │ │ └── index.md # Documentation │ ├── learning-graph/ # Learning graph data and analysis │ │ ├── learning-graph.csv # Concept dependencies │ │ ├── learning-graph.json # vis-network format │ │ └── quality-metrics.md # Quality analysis │ ├── glossary.md # ISO 11179-compliant definitions │ ├── faq.md # Frequently asked questions │ └── references.md # Curated references ├── skills/ # Claude AI skills (if present) │ └── [skill-name]/ │ ├── SKILL.md # Skill definition │ └── *.py # Supporting scripts ├── mkdocs.yml # MkDocs configuration └── README.md # This file
Direct users to the GitHub Issues page:
## Reporting Issues
Found a bug, typo, or have a suggestion for improvement? Please report it:
[GitHub Issues](https://github.com/username/repo-name/issues)
When reporting issues, please include:
- Description of the problem or suggestion
- Steps to reproduce (for bugs)
- Expected vs actual behavior
- Screenshots (if applicable)
- Browser/environment details (for MicroSims)
Reinforce licensing terms and attribution requirements:
## License
This work is licensed under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](https://creativecommons.org/licenses/by-nc-sa/4.0/).
**You are free to:**
- Share — copy and redistribute the material
- Adapt — remix, transform, and build upon the material
**Under the following terms:**
- **Attribution** — Give appropriate credit with a link to the original
- **NonCommercial** — No commercial use without permission
- **ShareAlike** — Distribute contributions under the same license
See [✓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
Steps
- 1Install product management skill
- 2Start with user story generation for known feature
- 3Progress to competitive analysis: research 2-3 competitors
- 4Use for roadmap prioritization: apply RICE/ICE scoring
- 5Draft stakeholder communications and refine based on feedback
- 6Build template library for recurring PM tasks
- 7Share 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
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
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4.5★★★★★42 reviews- SShikha Mishra★★★★★Dec 16, 2024
readme-generator has been reliable in day-to-day use. Documentation quality is above average for community skills.
- JJames Rahman★★★★★Dec 12, 2024
We added readme-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- EEvelyn Bhatia★★★★★Dec 8, 2024
Solid pick for teams standardizing on skills: readme-generator is focused, and the summary matches what you get after install.
- YYusuf Sanchez★★★★★Dec 4, 2024
readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- EEvelyn Harris★★★★★Nov 27, 2024
Registry listing for readme-generator matched our evaluation — installs cleanly and behaves as described in the markdown.
- EEvelyn Liu★★★★★Nov 23, 2024
We added readme-generator from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- NNia Smith★★★★★Oct 18, 2024
readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- EEvelyn Taylor★★★★★Oct 14, 2024
Solid pick for teams standardizing on skills: readme-generator is focused, and the summary matches what you get after install.
- KKaira Khan★★★★★Sep 13, 2024
readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- OOshnikdeep★★★★★Sep 5, 2024
readme-generator reduced setup friction for our internal harness; good balance of opinion and flexibility.
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