assafelovic

assafelovic / skyll

Public

A tool for AI agents to discover and learn skills autonomously

skyll.app claude-skill mcp skills
214
20
100% credibility
Found Feb 02, 2026 at 13 stars 16x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

Skyll is a search tool that enables AI assistants to discover, retrieve, and use specialized instruction guides from public collections in real time.

How It Works

1
🌐 Discover Skyll

You hear about Skyll from a friend or online and visit the friendly demo page to see what it's about.

2
🔍 Search for help

You type in what your AI needs to learn, like 'react performance tips' or 'better testing', and hit search.

3
⭐ See perfect matches

A list of top instruction guides pops up, ranked by popularity and fit, with previews so you instantly spot the best ones.

4
📖 Explore a guide

Click any guide to read its full instructions, see extra tips, and check how many people use it.

5
Put it to work
📋
Copy & paste

Copy the instructions into your AI chat and watch it follow them step by step.

🔗
Connect once

Link Skyll to your AI tool with a simple setting, then it finds and uses guides on its own forever.

🚀 AI levels up

Your AI now handles the task perfectly, like a pro, saving you time and frustration every time.

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Star Growth

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AI-Generated Review

What is skyll?

Skyll is a Python REST API and MCP server that lets AI agents search multiple sources like skills.sh for SKILL.md files, fetch full content from GitHub repos, and get structured JSON for runtime context injection. It solves the pre-installation hassle—agents discover relevant skills on demand via natural language queries, with relevance ranking, deduplication, and aggressive caching to handle GitHub rate limits. Use the pip-installable client for LangChain or LangGraph agents, or hook into MCP for Claude/Cursor.

Why is it gaining traction?

Unlike static skill lists, Skyll enables autonomous discovery with scored results blending popularity, query match, and content quality—agents pick the best without human picks. The hosted API and MCP endpoint mean zero setup for quick wins, plus self-hosting for privacy. Developers dig the fresh GitHub pulls ensuring latest skills, plus extras like reference docs fetching.

Who should use this?

AI agent builders integrating LangChain tool agents, LangGraph workflows, OpenAI agents, or Ollama tool agents needing dynamic skills for tasks like React perf tuning or testing flows. Perfect for Cursor/Claude Desktop users via MCP, or anyone scripting multi-tool agents that adapt to user queries without manual skill kits.

Verdict

Grab it if you're prototyping agentic apps—solid docs and interactive demo make onboarding fast, despite 180 stars and 1.0% credibility signaling early days. Maturity lags on tests and scale, but the core loop works reliably for dev experiments.

(198 words)

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