Two tools with reasonable descriptions and parameter schemas, but significant gaps in output documentation, error handling guidance, and parameter constraints. Tool names follow verb_noun convention. Descriptions are adequate (100-150 chars) but lack actionable context for LLM selection. Parameters have types but many lack detailed constraints or validation guidance. No evidence of error recovery patterns or output schema documentation. Composition is sound (two independent, read-only tools), but parameter design could be more LLM-friendly.

• Document output schema for both tools. Specify: for 'debrief', return structure (e.g., {findings: [{source, reliability_score, content}], synthesis: string}); for 'list_sources', return array of {name, category, reliability_tier, cost_usd, availability}.
• Convert 'categories' parameter to a formal enum constraint in the schema rather than listing values in description text. This makes valid options machine-parseable and prevents hallucination.
• Add min/max bounds to 'budget' parameter (e.g., 0.01 - 1000 USD) and document the default value from config. Include guidance: 'If budget is exceeded, research stops and returns partial results.'
• Add error recovery guidance to tool descriptions. E.g., 'If synthesis fails due to API limits, results are returned without synthesis. If a source is unavailable, research continues with remaining sources.'
• Specify valid Anthropic model names for the 'model' parameter (e.g., 'claude-3-5-sonnet-20241022', 'claude-3-opus-20250219') and document the default model used if omitted.