Skill From Github logo

Skill From Github

OrganizationPopular
GBSOSS
skill-from-github

Create skills by learning from high-quality GitHub projects

Overview

PublisherGBSOSS
Repositoryskill-from-masters
Skill nameskill-from-github
Stars
1.6K
Forks
160
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by GBSOSS on GitHub. Read the source before you install it.

Installation

Install the Skill From Github AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/GBSOSS/skill-from-masters.git /tmp/skill-from-masters
mkdir -p .claude/skills
cp -r /tmp/skill-from-masters/skills/skill-from-github .claude/skills/skill-from-github
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Skill From Github in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Skill From Github on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Skill From Github is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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:

markdown
## 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:

markdown
## 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

Frequently asked questions

What does the Skill From Github AI skill do?

Create skills by learning from high-quality GitHub projects

Why use Skill From Github on TypingMind?

Because you install it once and use it with any model. Skill From Github is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Skill From Github in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/GBSOSS/skill-from-masters/tree/main/skills/skill-from-github. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Skill From Github?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Skill From Github?

As many as you like. As long as a model supports skills, you can use Skill From Github with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Skill From Github AI skill free?

Yes. It is published on GitHub by GBSOSS under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇