Single tool with solid naming (search_fluent_icons) and comprehensive parameter descriptions. Input schema is well-defined with types, defaults, and constraints (maxResults clamped 1-200). Output is JSON-serialized but schema not formally documented in code. Tool description is adequate (97 chars) but could better explain when/why to use it. No error handling guidance visible, tool silently returns empty results on invalid input rather than guiding recovery. Follows verb_noun pattern well; parameter naming is clear (name, tags, code, maxResults). Missing: output schema documentation, error recovery patterns, and examples of expected response structure.

• Document the output schema explicitly in the tool description or as a separate schema block. Example: 'Returns {TotalMatches: int, ReturnedCount: int, Icons: [{Code: string, Name: string, Tags: string[]}]}'.
• Add error handling that returns structured error messages. E.g., if code format is invalid after normalization, return {error: 'Invalid icon code format', expected_formats: ['E700', 'U+E700', '0xE700'], received: '<input>'}.
• Expand tool description to 150-200 chars explaining: 'Search Windows Fluent Icons by name, tags, or Unicode code. Returns matching icons with their codes, names, and tags. Use this to find icon codes for UI designs. Supports partial name/tag matching and exact code lookup.'
• Clarify in the 'code' parameter description that all formats (E700, U+E700, 0xE700, \uE700) are accepted and normalized. Add: 'All formats are equivalent and normalized internally.'
• Add a note in the tool description about result limits and pagination: 'Results capped at 200. If you need more, refine your search with additional filters (name, tags, or code).' This sets LLM expectations.

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

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