Local Skills FAQs

Question 1

What is Local Skills MCP and how does it benefit AI agents?

Accepted Answer

Local Skills MCP is a universal server that enables any LLM or AI agent to access expert skills directly from your local filesystem. It benefits AI agents by providing structured instructions, reducing context consumption through lazy loading, and ensuring universal compatibility across various AI systems.

Question 2

Does Local Skills support hot reloading of skills?

Accepted Answer

Yes, Local Skills features hot reload. All changes to your skill definitions—including new skills, edits, or deletions—are applied instantly without requiring any server restart, ensuring an agile development workflow.

Question 3

Can I use Local Skills with various LLMs and AI clients?

Accepted Answer

Absolutely. Local Skills is universally compatible with any Model Context Protocol (MCP) client, such as Claude Code, Cline, or custom agents. It works seamlessly with various LLMs, including Claude, GPT, Gemini, and local models like Ollama.

Question 4

How does Local Skills manage context efficiency for LLMs?

Accepted Answer

Local Skills employs context-efficient lazy loading. Only skill names and brief descriptions (~50 tokens per skill) are loaded initially. The full content of a skill is loaded on-demand only when the AI agent explicitly requests to use it, significantly reducing token consumption.

Question 5

Where does Local Skills find skill definitions?

Accepted Answer

Local Skills automatically aggregates skill definitions from multiple local directories, including package built-in skills, `~/.claude/skills/`, project-specific folders (`./.claude/skills/`, `./skills`), and custom paths defined by the `$SKILLS_DIR` environment variable. This allows for flexible and organized skill management.

Local Skills

Local Skills

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About

Key Features

Use Cases