Server has 7 tools with clear verb-noun naming (list_, get_, search_, suggest_). All tools have descriptions (avg 95 chars, within baseline 34-392). Input schemas are present with type definitions. However, parameter descriptions are sparse or missing for optional params (limit, topTypes, samplePokemonPerType, topWeaknesses, suggestedDefensiveTypes). Output schemas are not documented, LLMs cannot predict response structure. No error handling guidance. No tool annotations (readOnlyHint present via Risk field but not in MCP schema). Composition is sound: tools are single-purpose and chainable.

• Document output schemas for all 7 tools. Example for get_pokemon: 'Returns {id: number, name: string, types: string[], stats: {hp, attack, defense, ...}, abilities: string[]}'. This enables LLMs to chain tools and extract fields.
• Add descriptions to all optional parameters with valid ranges. Example: 'limit: Maximum number of results to return (1-100, default 20)' and 'topTypes: Number of top counter types to suggest (1-10, default 5)'.
• Implement error recovery guidance. When get_pokemon fails, return: 'Pokemon "xyz" not found. Try search_pokemon("xy") to find similar names.' This guides the LLM to self-correct.
• Add readOnlyHint: true to all tool definitions in MCP schema to expose the READ_ONLY risk classification. This prevents agents from treating these as state-modifying operations.
• Add numeric constraints to JSON Schema. Example: {"type": "number", "minimum": 1, "maximum": 100, "description": "..."} for limit and topTypes parameters.