Coordinate external LLM consultations by gathering context and invoking the consult_llm MCP tool.
npx skills add https://github.com/raine/consult-llm-mcp --skill consult-llm
Please help me install this Agent Skill. Skill: consult-llm Source: https://github.com/raine/consult-llm-mcp/tree/main/examples Command: npx skills add https://github.com/raine/consult-llm-mcp --skill consult-llm
This Skill automates the process of consulting external LLMs by collecting relevant file context, selecting the appropriate model/mode (Gemini or Codex, API/CLI/web), and invoking the consult_llm MCP tool. It ensures neutral prompts and focused context to reduce noise and save you time.
In Claude Code, say: "ask gemini about the race condition in server.ts" or "ask codex about the race condition in server.ts" or "ask in browser about the race condition in server.ts". The skill will gather relevant files, determine mode and model, and present a summarized response with next steps.
High-intent search queries and answers about installing and using this skill.
Consult external LLMs by gathering repository context, selecting the appropriate model (Gemini or Codex), and invoking the consult_llm MCP tool with filtered files. This automates context collection and reduces noise in your query.
Yes. Use commands like 'ask gemini about the race condition in server.ts' or 'ask codex about the issue in main.py'. The Skill gathers relevant files, determines the model, and presents a summarized response with next steps.
API mode invokes Gemini or Codex programmatically; CLI mode runs through command-line; web mode consults in the browser. The Skill automatically selects the mode based on your instruction ('ask in browser' triggers web mode) and your environment.
The Skill uses Glob and Grep to automatically gather and filter relevant files from your repository, then prioritizes file relevance to create concise context. This reduces noise and ensures the LLM receives only pertinent information.
No. The Skill enforces neutral, focused prompts and standardized output formatting automatically. It handles context collection and prompt structuring so you can focus on the core question.
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