SK

skill-from-github

Learns from GitHub projects to create new skills for your development workflow.

Install

mkdir -p .claude/skills/skill-from-github && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/1761" && unzip -o skill.zip -d .claude/skills/skill-from-github && rm skill.zip

Installs to .claude/skills/skill-from-github

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Create skills by learning from high-quality GitHub projects
59 charsno explicit “when” trigger
Intermediate

Key capabilities

  • Search GitHub for high-quality projects
  • Analyze project READMEs and source code
  • Extract core algorithms and best practices
  • Summarize project concepts for skill creation
  • Propose new skills based on open-source knowledge

How it works

It searches GitHub for projects meeting quality criteria, analyzes their implementation, and synthesizes the knowledge into a new skill.

Inputs & outputs

You give it
Task description or problem statement
You get back
Analysis of GitHub projects and proposed skill implementation

When to use skill-from-github

  • Finding open source tools for a specific task
  • Evaluating quality of third-party libraries
  • Integrating new functionality based on popular projects

About this skill

Skill from GitHub

When users want to accomplish something, search GitHub for quality projects that solve the problem, understand them deeply, then create a skill based on that knowledge.

When to Use

When users describe a task and you want to find existing tools/projects to learn from:

  • "I want to be able to convert markdown to PDF"
  • "Help me analyze sentiment in customer reviews"
  • "I need to generate API documentation from code"

Workflow

Step 1: Understand User Intent

Clarify what the user wants to achieve:

  • What is the input?
  • What is the expected output?
  • Any constraints (language, framework, etc.)?

Step 2: Search GitHub

Search for projects that solve this problem:

{task keywords} language:{preferred} stars:>100 sort:stars

Search tips:

  • Start broad, then narrow down
  • Try different keyword combinations
  • Include "cli", "tool", "library" if relevant

Quality filters (must meet ALL):

  • Stars > 100 (community validated)
  • Updated within last 12 months (actively maintained)
  • Has README with clear documentation
  • Has actual code (not just awesome-list)

Step 3: Present Options to User

Show top 3-5 candidates:

## Found X projects that can help

### Option 1: [project-name](github-url)
- Stars: xxx | Last updated: xxx
- What it does: one-line description
- Why it's good: specific strength

### Option 2: ...

Which one should I dive into? Or should I search differently?

Wait for user confirmation before proceeding.

Step 4: Deep Dive into Selected Project

Once user selects a project, thoroughly understand it:

  1. Read README - Understand purpose, features, usage
  2. Read core source files - Understand how it works
  3. Check examples - See real usage patterns
  4. Note dependencies - What it relies on
  5. Identify key concepts - The mental model behind it

Extract:

  • Core algorithm/approach
  • Input/output formats
  • Error handling patterns
  • Best practices encoded in the code

Step 5: Summarize Understanding

Present what you learned to user:

## Understanding [project-name]

### Core Approach
How it solves the problem...

### Key Techniques
1. ...
2. ...

### Limitations
- ...

### What I'll encode in the skill
- ...

Does this look right? Should I proceed to create the skill?

Wait for user confirmation.

Step 6: Create Skill via skill-creator

Hand off to skill-creator with:

  1. Clear purpose - What the skill does
  2. Methodology - The approach learned from the project
  3. Step-by-step process - Concrete instructions
  4. Quality criteria - What good output looks like
  5. Common pitfalls - What to avoid (learned from project issues/docs)

Important: The skill should encode the knowledge from the project, not just wrap the tool. The skill should work even without the original project installed.

Example

User: "I want to write better commit messages"

Step 2 - Search:

commit message convention stars:>100 sort:stars

Step 3 - Present:

## Found 4 projects

### Option 1: conventional-commits/conventionalcommits.org (4.2k ⭐)
- Specification for human and machine readable commit messages
- Why: Industry standard, used by Angular, Vue, etc.

### Option 2: commitizen/cz-cli (15k ⭐)
- CLI tool for creating conventional commits
- Why: Battle-tested, lots of adapters

### Option 3: carloscuesta/gitmoji (14k ⭐)
- Emoji guide for commit messages
- Why: Visual, fun approach

Which one interests you?

User: "Let's go with conventional commits"

Step 4 - Deep dive:

  • Read the specification
  • Understand types (feat, fix, docs, etc.)
  • Learn about scopes, breaking changes
  • Study real-world examples

Step 5 - Summarize:

## Understanding Conventional Commits

### Core Approach
Structured format: <type>(<scope>): <description>

### Key Types
- feat: new feature
- fix: bug fix
- docs: documentation
- ...

### Benefits Learned
- Automated changelog generation
- Semantic versioning
- Clear history

Ready to create a commit message skill based on this?

Step 6 - Create skill with these principles encoded

Important Notes

  1. Always get user confirmation - At step 3 (project selection) and step 5 (before creating)
  2. Prefer learning over wrapping - Encode the knowledge, not just "run this tool"
  3. Check license - Mention if project has restrictive license
  4. Credit the source - Include attribution in generated skill
  5. Quality over speed - Take time to truly understand the project

What This Skill is NOT

  • NOT a package installer
  • NOT a tool wrapper
  • It's about learning from the best projects and encoding that knowledge into a reusable skill

When not to use it

  • When the user needs a direct tool wrapper rather than learning
  • When no relevant open-source projects exist

Prerequisites

User confirmation for project selectionUser confirmation before skill creation

Limitations

  • Dependent on availability of high-quality GitHub projects
  • Requires user interaction for confirmation
  • Does not automatically install packages

How it compares

It focuses on learning and encoding knowledge from open-source projects rather than simply wrapping existing tools.

Compared to similar skills

skill-from-github side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
skill-from-github (this skill)76moNo flagsIntermediate
cartographer36moReviewIntermediate
cass02moCautionIntermediate
ai-patterns05moReviewBeginner

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