Single tool 'search_skill' has a reasonable description (145 chars) but critical schema gaps. Input schema visible with user_query parameter (string type, description present). However, output schema is completely undocumented, the tool returns CallToolResult with Content::text but no structured schema is declared. Parameter descriptions are minimal. Tool does one thing (search skills) but lacks error handling guidance, pagination support, and output structure documentation. No tool annotations present. Naming is verb-forward (search_skill) which is good, but the implementation reveals keyword-matching logic that may not scale, no guidance on matching quality or fallback behavior.

• Define a structured output schema for search_skill. Return JSON with fields: {skill_name, description, content, match_score, available_scripts}. Document this schema in the tool definition so LLMs know what to extract.
• Add explicit error handling: return error (not success) when no skills match, with guidance like 'No skills matched query. Try broader keywords or call list_skills() to see available options.'
• Expand user_query parameter description to ~100 chars: 'Natural language query describing the task (e.g., "send email", "generate report"). Matches against skill names and descriptions. Returns best match or error if no match found.'
• Add optional limit parameter (default 1, max 5) to return top N matching skills ranked by score. Include match_score in output so LLM knows confidence level.
• Document the matching algorithm in tool description: 'Uses keyword matching on skill name and description. Scores name matches higher than description matches. Returns single best match or error if no match exceeds threshold.'

Inferred effective spec: <=2025-11-25.

• Relies on Logging (deprecated) - log to stderr or use OpenTelemetry