Claude-skill-registry consult-llm

When consulting with external LLMs:

install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/consult-llm" ~/.claude/skills/majiayu000-claude-skill-registry-consult-llm && rm -rf "$T"
manifest: skills/data/consult-llm/SKILL.md
source content

When consulting with external LLMs:

1. Gather Context First:

  • Use Glob/Grep to find relevant files
  • Read key files to understand their relevance
  • Select files directly related to the question

2. Determine Mode and Model:

  • Web mode: Use if user says "ask in browser" or "consult in browser"
  • Codex mode: Use if user says "ask codex" → use model "gpt-5.1-codex-max"
  • Gemini mode: Default for "ask gemini" → use model "gemini-2.5-pro"

3. Call the MCP Tool: Use

mcp__consult-llm__consult_llm
with:

  • For API mode (Gemini):

    • model
      : "gemini-2.5-pro"
    • prompt
      : Clear, neutral question without suggesting solutions
    • files
      : Array of relevant file paths
  • For API mode (Codex):

    • model
      : "gpt-5.1-codex-max"
    • prompt
      : Clear, neutral question without suggesting solutions
    • files
      : Array of relevant file paths
  • For web mode:

    • web_mode
      : true
    • prompt
      : Clear, neutral question without suggesting solutions
    • files
      : Array of relevant file paths
    • (model parameter is ignored in web mode)

4. Present Results:

  • API mode: Summarize key insights, recommendations, and considerations from the response
  • Web mode: Inform user the prompt was copied to clipboard and ask them to paste it into their browser-based LLM and share the response back

Critical Rules:

  • ALWAYS gather file context before consulting
  • Ask neutral, open-ended questions to avoid bias
  • Provide focused, relevant files (quality over quantity)