mcp-skill-discovery-reuse

Reuse fetch, build, and memoization patterns to load MCP skills.

Updated Aug 27, 2026
One-click install
npx skills add https://github.com/liuyu520/cc_source --skill mcp-skill-discovery-reuse
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: mcp-skill-discovery-reuse
Source: https://github.com/liuyu520/cc_source/tree/main/.claude/skills/mcp-skill-discovery-reuse
Command: npx skills add https://github.com/liuyu520/cc_source --skill mcp-skill-discovery-reuse

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill helps teams extend MCP skill discovery by reusing established parsing, command-creation, and caching patterns, reducing duplication and avoiding circular dependencies.

Core Features & Use Cases

  • Reuse fetchMcpSkillsForClient, mcpSkillBuilders registry, parseSkillFrontmatterFields, createSkillCommand, and memoizeWithLRU caching.
  • Add new resource-to-Command converters and wire MCP skills into new consumption points.
  • Debug MCP skill loading issues and verify integration with client workflows.

Quick Start

Use this skill to extend MCP discovery by adding new resource converters and wiring skills into client workflows.

Frequently Asked Questions about mcp-skill-discovery-reuse

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I reuse existing MCP skill patterns to add new resource-to-command converters?

To reuse MCP skill patterns, wire new resource-to-command converters into the mcpSkillBuilders registry and leverage memoizeWithLRU caching to produce consistent Command objects from MCP resources without duplicating logic.

What's the best way to avoid circular dependencies when extending MCP skill discovery?

Avoid circular dependencies in MCP skill discovery by reusing established parsing and command-creation patterns like parseSkillFrontmatterFields and createSkillCommand, ensuring consistent Command object generation across client workflows.

How does memoization work with MCP skill fetching for client workflows?

Memoization in MCP skill fetching uses a memoized fetchMcpSkillsForClient function with LRU caching to store and retrieve loaded skills, reducing redundant parsing and improving integration performance across client workflows.

Can I debug MCP skill loading issues using frontmatter parsing utilities?

Yes, you can debug MCP skill loading issues by applying parseSkillFrontmatterFields utilities to inspect resource metadata, verify builder registry integration, and validate that consistent Command objects are produced correctly.

Do I need a builder registry to wire MCP skills into new consumption points?

Yes, you need the mcpSkillBuilders registry to map MCP resources to Command objects, along with the memoized fetch function and frontmatter parsing utilities, to successfully wire skills into new client workflow consumption points.