LibraryAI and agent development
MagicSkills
Manage one shared skill pool and expose tailored collections to multiple agents.
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- Updated Jul 14, 2026
MIT
Manage one shared skill pool and expose tailored collections to multiple agents.
MagicSkills keeps reusable `SKILL.md` directories in one local pool and lets users compose named subsets for different agents or workflows. Runtimes that read `AGENTS.md` can receive a synchronized skill section, while agent frameworks can use the same collection through a command-line or Python tool interface. It is aimed at multi-agent projects that want to avoid copying and drifting skill folders, and requires Python 3.10–3.13 plus Git.
Resource types
Use cases
Platforms
Turns GitHub repositories into executable software-engineering tasks for training SWE agents.
Help LangGraph agents retrieve relevant tools from very large registries.
Runtime
Capabilities
Public GitHub facts last synced Jul 14, 2026.
Studies active tool discovery for autonomous agents with an MCP retrieval dataset and scripts.
Retrieve only the most relevant tools for an LLM query