Three tools with basic descriptions and minimal schemas. check_config and list_models have empty input schemas ({}), which is acceptable for parameterless tools. consult_model has a proper schema with three parameters (prompt, model, role), all with descriptions. However, descriptions lack depth and actionability. No output schemas documented. No error handling guidance. No parameter constraints (enums, ranges). Naming is clear (verb_noun pattern), but descriptions are generic and under 200 chars. No tool annotations (readOnlyHint, etc.). Overall structure is functional but falls short of production quality.

• Add output schema documentation for each tool. Example for list_models: 'Returns {models: [{name, provider, context_window, cost_per_1k_tokens, recommended_use}]}'. This enables LLMs to extract and chain data.
• Add enum constraint to 'model' parameter in consult_model. List 5-10 representative OpenRouter model IDs (openai/gpt-4, google/gemini-2-pro, xai/grok-3, etc.) so LLMs know valid options.
• Expand consult_model description to 150-200 chars: 'Send a prompt to an external LLM via OpenRouter and get its response. Useful for multi-perspective analysis. Requires OPENROUTER_API_KEY or OPENAI_API_KEY. Returns response text, token usage, and cost estimate.'
• Add error handling guidance to consult_model: 'If API key is missing, call check_config first to verify setup. If model not found, call list_models to see available options.'
• Add readOnlyHint: true to all three tools in the schema to signal they are safe to call without side effects.