[Claude Code consulting you for a second opinion]

Task: Review this Claude Code skill design for blind spots, missing features, or shifts in thinking we haven't considered. The skill is called "brains-trust" and it lets Claude Code consult other LLMs for second opinions.

Context: This is a skill for Claude Code (Anthropic's CLI tool). Skills are markdown instruction files that guide Claude through workflows. They live in a public plugin repo. The user (Jez) is a solo developer building tools for his web agency.

The skill replaces a Gemini-only "peer review" skill with a multi-model consultation tool. Key design decisions already made:
- Uses OpenRouter as universal API (one key, all providers)
- Runtime model discovery via models.flared.au (curated list of ~40 leading models, auto-updated from OpenRouter)
- No hardcoded model IDs (they go stale constantly)
- No output token caps (let models reason fully)
- File-based prompts (avoids shell escaping issues)
- Generated Python script using urllib (no pip dependencies)
- Three consultation patterns: single opinion, consensus (2-3 models in parallel), devil's advocate
- Seven modes: code review, architecture, debug, security, strategy, prompting, general
- AI-to-AI framing (consulted model knows it's advising Claude, not talking to the human)

What we want to know:
1. Are there obvious features or patterns we've missed that would be high-value additions without over-complicating things?
2. Is there a shift in thinking or approach we should consider?
3. Are the default choices good? (e.g. should "brains trust" default to consensus rather than single? Should there be a recommended "go-to" model per provider?)
4. Any UX friction points — things that would annoy a user in practice?
5. Anything that seems over-engineered or under-engineered?

Keep suggestions practical and grounded. This is a solo dev tool, not enterprise software. Simple > complex.

--- SKILL.md ---
[See full SKILL.md content above — 130 lines covering setup, patterns, modes, workflow, rules]

--- references/prompt-templates.md ---
[AI-to-AI templates for 7 modes plus devil's advocate framing — ~125 lines]

--- references/provider-api-patterns.md ---
[Python patterns for OpenRouter, Gemini direct, OpenAI direct, parallel execution, error handling — ~204 lines]
