Skill Grep
npx claudepluginhub littledinoc/skill-grepSmart skill search engine for agents — discover reusable skills and workflows instantly.
Share bugs, ideas, or general feedback.
Navigate the skill universe — Stop reinventing the wheel, start discovering.
A smart skill search engine for agents — discover reusable skills and workflows instantly.
🌐 Try the Web Version: skills.megatechai.com. Search skills directly in your browser!
Finding the right skill shouldn't be harder than building it yourself.
When you need a capability, you shouldn't have to:
Skill Compass searches across sources using multi-field retrieval and returns ranked recommendations with quality signals (e.g., GitHub stars), so you can quickly find the best option.
1. You: "I need a skill for CI/CD automation"
2. Skill Compass:
├── Builds structured query from your intent
├── Calls search API with query fields
├── (Optional) Asks one clarification question if needed
└── Returns 1-3 ranked recommendations
3. You: Select the best match
└── Skill Compass learns from your feedback
| Feature | Description |
|---|---|
| Smart Retrieval | Jointly searches over name, description, and usage context for better relevance |
| Quality Signals | Shows relevance + GitHub stars |
| Clarification Loop | Asks one targeted question if results are ambiguous |
| Feedback Telemetry | Continuously improves ranking |
You can register this repository as a Claude Code Plugin marketplace by running the following command in Claude Code:
/plugin marketplace add LittleDinoC/skill-compass
/plugin install skill-compass@skill-compass
npx skills add https://github.com/LittleDinoC/skill-compass --skill skill-compass
You can download the specific skill folder and place it in your skills directory.
# Navigate to your skills directory (e.g., for OpenClaw)
cd ~/.openclaw/skills
# Extract only the specific skill folder
npx degit LittleDinoC/skill-compass/skills/skill-compass skill-compass
Note: This installs only the skill-compass package without cloning the entire repository history.
The skill activates automatically when you ask your agent to discover, find, or search for skills.
Simple search:
You: "Find me a skill for git commit conventions"
Skill Compass:
> Searching for skills...
Recommendations:
1. conventional-commits (github/awesome-copilot, 26.8k repo stars ⭐)
Best for: Structured commit message generation following Conventional Commits specification.
This skill guides you through creating standardized, descriptive commit messages with a structured XML format. It includes instructions, examples, and validation to ensure your commits follow the Conventional Commits specification.
2. git-commit (github/awesome-copilot, 26.8k repo stars ⭐)
Best for: Complete commit workflow with intelligent staging
A more comprehensive option that handles the full git commit workflow: auto-detecting type and scope from changes, generating conventional commit messages from diff, interactive commits with overrides, and intelligent file staging for logical grouping.
Search with clarification:
You: "I need a skill for testing"
Skill Compass:
> I found several testing skills, but they serve different purposes. What type of testing do you need?
1. Test-Driven Development (TDD) — Write tests first, then implement code to make them pass
2. Test Generation — Generate comprehensive tests for existing code (multi-language)
3. Language-Specific Testing — Focused testing for specific languages (Python, C++, etc.)
You: "End-to-end testing"
Skill Compass:
> Refined search...
Recommendations:
1. e2e-testing-patterns (wshobson/agents, 32.3k repo stars ⭐)
- Fit: Master E2E testing with Playwright and Cypress, flaky test debugging, CI/CD integration.
| Scenario | Behavior |
|---|---|
| Clear intent | Returns top recommendations immediately |
| Ambiguous results | Asks exactly one clarification question |
| No results | Prompts for refined intent |
| User verdict | Sends feedback for ranking improvement |
Skill Compass is the practical extension of our paper Multi-Field Tool Retrieval. While the paper proposes a framework for retrieving tools across multiple metadata fields, this project brings those insights into a functional search engine for AI agents.
If you find this work helpful for your research or projects, please cite our paper: