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Skill

/github-search

Search GitHub code, repositories, issues, and PRs via MCP

From plugin
vibecosystem
531200 skills138 agents7 hooks
Install
$ npx -y skills add vibeeval/vibecosystem --skill github-search --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/github-search

Context preview

The summary Claude sees to decide when to auto-load this skill.

Search GitHub code, repositories, issues, and PRs via MCP

SKILL.md

github-search.SKILL.md
name: github-search
description: Search GitHub code, repositories, issues, and PRs via MCP
allowed-tools: [Bash, Read]

GitHub Search Skill

When to Use

  • Search code across repositories
  • Find issues or PRs
  • Look up repository information

Instructions

uv run python -m runtime.harness scripts/mcp/github_search.py \
    --type "code" \
    --query "your search query"

Parameters

  • `--type`: Search type - `code`, `repos`, `issues`, `prs`
  • `--query`: Search query (supports GitHub search syntax)
  • `--owner`: (optional) Filter by repo owner
  • `--repo`: (optional) Filter by repo name

Examples

# Search code
uv run python -m runtime.harness scripts/mcp/github_search.py \
    --type "code" \
    --query "authentication language:python"

# Search issues
uv run python -m runtime.harness scripts/mcp/github_search.py \
    --type "issues" \
    --query "bug label:critical" \
    --owner "anthropics"

MCP Server Required

Requires `github` server in mcp_config.json with GITHUB_PERSONAL_ACCESS_TOKEN.

Ships withvibecosystem

Your AI software team. Built on Claude Code. vibecosystem turns Claude Code into a full AI software team — 138 specialized agents that plan, build, review, test, and learn from every mistake. No configuration needed — just install and code.

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