AI Skills
brains-trust

brains-trust

熱門

Get a second opinion from leading AI models on code, architecture, strategy, prompting, or anything. Queries models via OpenRouter, Gemini, or OpenAI APIs. Supports single opinion, multi-model consensus, and devil's advocate patterns. Trigger with 'brains trust', 'second opinion', 'ask gemini', 'ask gpt', 'peer review', 'consult', 'challenge this', or 'devil's advocate'.

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更新於 2026/9/29
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SKILL.md
唯讀
名稱
brains-trust
描述

Get a second opinion from leading AI models on code, architecture, strategy, prompting, or anything. Queries models via OpenRouter, Gemini, or OpenAI APIs. Supports single opinion, multi-model consensus, and devil's advocate patterns. Trigger with 'brains trust', 'second opinion', 'ask gemini', 'ask gpt', 'peer review', 'consult', 'challenge this', or 'devil's advocate'.

Brains Trust

Consult other leading AI models for a second opinion. Not limited to code — works for architecture, strategy, prompting, debugging, writing, or any question where a fresh perspective helps.

Defaults (When User Just Says "Brains Trust")

If the user triggers this skill without specifying what to consult about, apply these defaults:

  • Pattern: Consensus (2 models from different providers) — it's called "brains trust", not "single opinion"

  • Scope: Whatever Claude has been working on in the current session. Look at recent context: files edited, decisions made, architecture discussed, problems being solved.

  • Mode: Infer from context:

Recently wrote/edited code → Code Review

  • In a planning or design discussion → Architecture

  • Debugging something → Debug

  • Building prompts or skills → Prompting

  • No clear signal → General (ask: "what are we missing? what are our blind spots?")

  • Models: Pick the newest pro-tier model from 2 different providers (check models.flared.au). Prefer diversity: e.g. one Google + one OpenAI, or one Qwen + one Google. Never two from the same provider.

  • Prompt focus: "Review what we've been working on. What are we missing? What could be improved? What blind spots might we have? Are there simpler approaches we haven't considered?"