Repo Metadata

Repository Metadata Generator

Generate engaging GitHub repository descriptions and topics by analyzing project intent, purpose, and features. Create metadata that improves discoverability and accurately represents what a project does.

Overview

This skill analyzes a project's codebase, documentation, and configuration to understand its purpose, then generates:

1. An optimized repository description (default, no configuration needed)
2. Relevant topics/labels for discoverability
3. Optionally applies changes via gh CLI (when user confirms)

GitHub Metadata Constraints

All generated metadata must meet GitHub's requirements:

Description:

• Maximum: 350 characters
• Should be concise, engaging, and searchable
• No markdown or special formatting
• Include key functionality and value proposition

Topics:

• Maximum: 20 topics per repository
• Each topic: lowercase, hyphenated, no spaces
• Maximum 50 characters per topic
• Should include: language, framework, domain, features

Workflow

Step 1: Check for Configuration

Look for optional settings file at .claude/github-social.local.md.

If file exists, check for metadata preferences:

• description_style: concise | detailed | technical
• topic_count: Number of topics to suggest (default: 10)
• include_language: Whether to include primary language as topic
• include_framework: Whether to include frameworks as topics

If no config exists, proceed with defaults.

Step 2: Analyze Project

Gather project context by reading available files:

Primary sources (check in order):

1. README.md - Project description, features, purpose
2. package.json / Cargo.toml / pyproject.toml / go.mod - Name, description, keywords
3. CLAUDE.md - Project context and guidelines
4. Source code structure - Primary language, frameworks

Extract these elements:

• Project name: Official name
• Purpose: What problem does it solve? (1-2 sentences)
• Key features: Top 3-5 capabilities
• Technology: Primary language and frameworks
• Domain: What field/industry? (DevTools, AI, Web, etc.)
• Target audience: Who uses this?
• Unique value: What makes it different?

Step 3: Generate Description

Craft an engaging description that:

1. Leads with value - What does it do for the user?
2. Includes key features - Top 2-3 capabilities
3. Uses active voice - Direct, engaging language
4. Stays within 350 chars - Concise but complete
5. Avoids jargon - Accessible to broader audience

Description patterns by project type:

Library/Package:

[Action verb] [what it does] for [language/platform]. Features [key capability 1], [key capability 2], and [key capability 3].

CLI Tool:

[Action verb] [what problem it solves] from the command line. [Key benefit or feature].

Framework:

[Adjective] [type] framework for building [what]. [Key differentiator].

Application:

[What it is] that [what it does]. [Key benefit for users].

Step 4: Generate Topics

Select relevant topics from these categories:

Language/Runtime (1-2 topics):

• Primary language: python, typescript, rust, go
• Runtime: nodejs, deno, bun

Framework/Library (1-3 topics):

• Web: react, vue, nextjs, fastapi
• Data: pandas, numpy, pytorch
• CLI: cli, command-line, terminal

Domain (2-4 topics):

• devtools, developer-tools, automation
• machine-learning, ai, data-science
• web-development, frontend, backend
• database, api, infrastructure

Features (2-4 topics):

• open-source, cross-platform
• testing, documentation, monitoring
• Feature-specific: image-generation, code-review

Quality/Style (1-2 topics):

• lightweight, fast, minimal
• production-ready, enterprise

Topic formatting rules:

• All lowercase
• Hyphens for multi-word: machine-learning not machine_learning
• No special characters
• Max 50 chars per topic

Step 5: Output or Apply

Default (output only):

Display the generated metadata:

## Generated Repository Metadata

### Description (X characters)
[Generated description]

### Topics (X topics)
[topic-1] [topic-2] [topic-3] ...

### To Apply Manually
1. Go to repository Settings → General
2. Update "Description" field
3. Add topics under "Topics"

### To Apply via CLI
gh repo edit --description "[description]"
gh repo edit --add-topic topic-1 --add-topic topic-2 ...

Apply mode (when user confirms):

If user says "apply", "update", or "yes, update the repo":

# Update description
gh repo edit --description "[generated description]"

# Add topics (one at a time)
gh repo edit --add-topic topic-1
gh repo edit --add-topic topic-2
# ... for each topic

Verify changes:

gh repo view --json description,repositoryTopics

Report success or errors.

Description Writing Guidelines

Do:

• Start with a strong action verb
• Focus on user benefit
• Include searchable keywords naturally
• Be specific about what it does
• Keep it scannable

Don't:

• Start with "A" or "This is"
• Use passive voice
• Include version numbers
• Use excessive punctuation
• Make unsubstantiated claims ("best", "fastest")

Examples by quality:

Poor:

This is a tool for working with images. It can do many things.

Good:

Generate social preview images for GitHub repos by analyzing project intent. Supports DALL-E, Stable Diffusion, and manual prompts.

Poor:

A Python library.

Good:

Fast, type-safe HTTP client for Python with automatic retries, connection pooling, and OpenAPI integration.

Topic Selection Strategy

For maximum discoverability:

1. Include the obvious - Language, primary framework
2. Add the domain - What category of tool is this?
3. Feature keywords - What can users search for?
4. Ecosystem tags - Related tools/standards
5. Audience tags - Who is this for?

Example topic sets:

Python CLI tool:

python cli command-line terminal devtools automation pip hacktoberfest

React component library:

react typescript components ui-library frontend web npm design-system

Machine learning project:

python machine-learning deep-learning pytorch neural-network ai data-science

DevOps tool:

devops kubernetes docker infrastructure automation ci-cd cloud-native golang

Error Handling

No README or project files found: Ask user to describe the project, then proceed with that information.

gh CLI not available: Output metadata only with manual instructions.

gh repo edit fails:

1. Report the error
2. Check if user has repo admin access
3. Suggest manual update via GitHub UI

Repository not found: Verify user is in a git repo with GitHub remote.

Examples

Example 1: CLI Tool

Project analysis:

• Name: github-social
• Purpose: Generate social preview images
• Tech: Claude Code plugin
• Features: DALL-E support, multiple styles, zero-config

Generated description:

Generate social preview images for GitHub repositories by analyzing project intent. Supports DALL-E, Stable Diffusion, and manual prompt generation.

(148 characters)

Generated topics:

github claude-code plugin social-preview image-generation dalle openai devtools automation open-source

Example 2: Python Library

Project analysis:

• Name: fasthttp
• Purpose: HTTP client library
• Tech: Python, async
• Features: Fast, typed, retries

Generated description:

Async HTTP client for Python with automatic retries, connection pooling, and full type hints. Built for performance and developer experience.

(142 characters)

Generated topics:

python http-client async asyncio requests api web typed networking pip

Additional Resources

Reference Files

• references/description-patterns.md - Detailed description templates by project type
• references/topic-taxonomy.md - Comprehensive topic categories and examples

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