Two tools with basic verb-noun naming (search_apis, get_api_page_content). Both have descriptions present but lack depth and actionable guidance. search_apis description is 180 chars (within baseline 194 avg but generic); get_api_page_content is 156 chars. Input schemas are minimal: single string parameters with descriptions present. No output schemas documented. No error handling guidance, no parameter constraints (enums, ranges), no pagination support despite search returning lists. No tool annotations (readOnlyHint, etc.). Composition is reasonable (two-step search→fetch pattern), but missing critical details for LLM planning.

• Add explicit output schema to both tools. For search_apis: document that it returns List[{id: str, title: str, url: str, snippet: str, category: str, last_updated: str}]. For get_api_page_content: document the structure of parsed content (parameters, members, return values, remarks, related_links sections).
• Add pagination to search_apis: accept optional 'limit' (1-50, default 10) and 'offset' (default 0) parameters. Return total_results count so LLM knows if more pages exist.
• Enhance error messages with recovery guidance. E.g., 'Search API returned 429 (rate limited). Retry in 60 seconds.' or 'Invalid URL format. Ensure URL starts with https://learn.microsoft.com'.
• Add readOnlyHint=true annotation to both tools in FastMCP registration to signal they are safe to call repeatedly without side effects.
• Expand descriptions to 150-250 chars with explicit dependency hints: 'Use this to find documentation pages. Returns URLs suitable for get_api_page_content. If you know the exact API name, skip this and call get_api_page_content directly.'

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

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