Single tool with well-structured schema and clear descriptions. The tool name starts with a verb (search_), parameters are fully typed with constraints, and descriptions are detailed and actionable. Output schema is documented in the description. Error handling returns structured responses with actionable guidance. Main limitation: this is a single-tool server, so composition patterns cannot be fully evaluated. The tool demonstrates above-average quality for community servers but lacks some production refinements like batch operations or dry-run capabilities.

• Add explicit outputSchema to the tool registration with typed fields (images: array, hasMore: boolean, nextOffset: number, thumbnailUrl?: string). This allows clients to validate and structure responses programmatically.
• Document per-parameter constraints in descriptions more formally: 'offset: Number of results to skip. Must be >= 0 and < total results (use hasMore and nextOffset for pagination).'
• Add a 'dry_run' or 'preview_thumbnails_only' boolean parameter to allow agents to preview results without the computational cost of composite image generation.
• Return explicit field names matching downstream tool needs (if an LLM will want to fetch full images, ensure the response includes both thumbnail URL and full-resolution URL with clear naming).
• Add pagination guidance in the description: 'To iterate through all results, call with offset=0, then use nextOffset from the response. Continue until hasMore=false.'
• Consider adding a 'format' parameter to allow LLMs to request YAML vs JSON output, improving compatibility with different agent frameworks.
• Add error recovery hints to the description: 'If no results found, try: 1) Simplify query (use fewer, common terms), 2) Set license="all", 3) Use offset for pagination.'
• Truncation logic should preserve a metadata object (count, total, nextOffset) even when text is truncated, so agents can plan pagination correctly.