readme-generator

dmccreary/claude-skills · updated Apr 8, 2026

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$npx skills add https://github.com/dmccreary/claude-skills --skill readme-generator
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summary

Generate or update a comprehensive README.md file for GitHub repositories following best practices.

skill.md

README Generator

Generate or update a comprehensive README.md file for GitHub repositories following best practices.

Purpose

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.

When to Use This Skill

Use this skill when:

  • Starting a new GitHub repository that needs a README.md
  • Updating an existing README.md to follow best practices
  • After significant project changes that should be documented
  • Before publishing or sharing a repository
  • When migrating from another documentation system
  • After adding new technologies or dependencies

Workflow

Step 1: Analyze Repository Context

Before generating the README, gather information about the repository:

  1. Check if README.md already exists in the root directory
  2. Identify the repository name from .git/config or the working directory
  3. Read mkdocs.yml if it exists to extract:
    • Site name
    • Site description
    • Site URL (for GitHub Pages link)
    • Repository URL
  4. Check for documentation in /docs directory
  5. Identify technologies used (look for package.json, requirements.txt, mkdocs.yml, etc.)

User Dialog Triggers:

  • If README.md exists: Ask "README.md already exists. Would you like to update it or create a backup first?"
  • If repository URL not found: Ask "What is the GitHub repository URL? (e.g., https://github.com/username/repo-name)"
  • If site URL not configured: Ask "Is this site deployed to GitHub Pages? If yes, what's the URL?"

Step 2: Generate Badges

Create badges for all relevant technologies and platforms. Use shields.io format for consistency.

Badge Order:

  1. MkDocs (if mkdocs.yml exists)
  2. MkDocs Material (if theme is Material)
  3. GitHub Pages live badge (if site is deployed)
  4. Claude Code badge
  5. Claude Skills badge (if .claude/skills or skills/ directory exists)
  6. License badge
  7. Additional technology badges (Python, JavaScript, p5.js, etc.)

Badge Templates:

[![MkDocs](https://img.shields.io/badge/Made%20with-MkDocs-526CFE?logo=materialformkdocs)](https://www.mkdocs.org/)
[![Material for MkDocs](https://img.shields.io/badge/Material%20for%20MkDocs-526CFE?logo=materialformkdocs)](https://squidfunk.github.io/mkdocs-material/)
[![GitHub Pages](https://img.shields.io/badge/View%20on-GitHub%20Pages-blue?logo=github)](SITE_URL)
[![GitHub](https://img.shields.io/badge/GitHub-OWNER%2FREPO-blue?logo=github)](REPO_URL)
[![Claude Code](https://img.shields.io/badge/Built%20with-Claude%20Code-DA7857?logo=anthropic)](https://claude.ai/code)
[![Claude Skills](https://img.shields.io/badge/Uses-Claude%20Skills-DA7857?logo=anthropic)](https://github.com/dmccreary/claude-skills)

Check for these additional badges:

  • p5.js: [![p5.js](https://img.shields.io/badge/p5.js-ED225D?logo=p5.js&logoColor=white)](https://p5js.org/)
  • Python: [![Python](https://img.shields.io/badge/Python-3776AB?logo=python&logoColor=white)](https://www.python.org/)
  • JavaScript: [![JavaScript](https://img.shields.io/badge/JavaScript-F7DF1E?logo=javascript&logoColor=black)](https://developer.mozilla.org/en-US/docs/Web/JavaScript)

Step 3: Add License Badge

Look for license information in:

  1. LICENSE file in root
  2. docs/license.md
  3. mkdocs.yml (copyright field)

Default to Creative Commons BY-NC-SA 4.0 if not specified:

[![License: CC BY-NC-SA 4.0](https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg)](https://creativecommons.org/licenses/by-nc-sa/4.0/)

Other common licenses:

  • MIT: [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
  • Apache 2.0: [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
  • GPL-3.0: [![License: GPL v3](https://img.shields.io/badge/License-GPLv3-blue.svg)](https://www.gnu.org/licenses/gpl-3.0)

Step 4: Create Website Link Section

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)

Step 5: Write Overview/Short Description

Create a compelling 1-3 paragraph overview that answers:

  • What is this project?
  • Who is it for?
  • Why is it valuable?
  • What makes it unique or special?

Guidelines:

  • Keep it concise but engaging
  • Use active voice
  • Highlight key features or benefits
  • Mention the educational framework if applicable
  • For textbooks: mention target audience (grade level, prerequisites)

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.

Step 6: Add Site Status and Metrics

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:

  1. Learning Graph Metrics (from docs/learning-graph/):

    • Number of concepts in concept graph
    • Quality score
    • Taxonomy distribution
  2. Content Metrics:

    • Number of chapters (count directories in docs/chapters/)
    • Number of markdown files (.md files in docs/)
    • Total word count (sum of all markdown files)
    • Number of code blocks
    • Number of lists and tables
  3. Interactive Elements:

    • Number of MicroSims (directories in docs/sims/)
    • Number of quizzes (files named quiz.md)
    • Total quiz questions (count in quiz files)
  4. Educational Resources:

    • Number of glossary terms (in docs/glossary.md)
    • Number of FAQ questions (in docs/faq.md)
    • Number of references (in docs/references.md)
  5. Media Assets:

    • Number of images (.png, .jpg, .svg files)
    • Number of diagrams (Mermaid, vis-network)

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:

  • Circuits textbook: Number of circuit diagrams, simulations
  • History textbook: Number of timelines, maps, primary source documents
  • Programming textbook: Number of code examples, exercises, projects
  • Math textbook: Number of equations, proofs, worked examples

Step 7: Add Getting Started Section

Provide clear instructions for using and customizing the project.

Standard sections:

  1. Prerequisites (if any)
  2. Clone the Repository
  3. Installation (if dependencies needed)
  4. Building the Site
  5. Local Development
  6. Deployment

Example:

## Getting Started

### Clone the Repository

```bash
git clone https://github.com/username/repo-name.git
cd repo-name

Install Dependencies

This project uses MkDocs with the Material theme:

pip install mkdocs
pip install mkdocs-material

Build and Serve Locally

Build the site:

mkdocs build

Serve locally for development (with live reload):

mkdocs serve

Open your browser to http://localhost:8000

Deploy to GitHub Pages

mkdocs gh-deploy

This will build the site and push it to the gh-pages branch.

Using the Book

Navigation:

  • Use the left sidebar to browse chapters
  • Click on the search icon to search all content
  • Each chapter includes quizzes and practice exercises

Interactive MicroSims:

  • Found in the "MicroSims" section
  • Each simulation runs standalone in your browser
  • Adjust parameters with sliders and controls

Customization:

  • Edit markdown files in docs/ to modify content
  • Modify mkdocs.yml to change site structure
  • Add your own MicroSims in docs/sims/
  • Customize theme in 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

Step 9: Add Issue Reporting Section

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)

Step 10: Add License Information

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 [
how to use readme-generator

How to use readme-generator 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 readme-generator
2

Execute installation command

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

$npx skills add https://github.com/dmccreary/claude-skills --skill readme-generator

The skills CLI fetches readme-generator from GitHub repository dmccreary/claude-skills 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/readme-generator

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

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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

4.542 reviews
  • Shikha Mishra· Dec 16, 2024

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

  • James Rahman· Dec 12, 2024

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

  • Evelyn Bhatia· Dec 8, 2024

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

  • Yusuf Sanchez· Dec 4, 2024

    readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Evelyn Harris· Nov 27, 2024

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

  • Evelyn Liu· Nov 23, 2024

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

  • Nia Smith· Oct 18, 2024

    readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Evelyn Taylor· Oct 14, 2024

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

  • Kaira Khan· Sep 13, 2024

    readme-generator fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Oshnikdeep· Sep 5, 2024

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

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