Single tool with basic schema and minimal descriptions. Tool name 'resolve_entities' lacks action verb prefix (should be 'cluster_entities' or 'resolve_entity_mentions'). Description is adequate (89 chars) but parameters lack individual descriptions entirely, LLMs cannot infer what 'mentions' or 'threshold' control without explicit guidance. Input schema is present with types but no parameter-level descriptions. No output schema documented. No error handling guidance. No security considerations. Composition is single-purpose but lacks richness for production use.

• Rename tool to 'cluster_entities' or 'resolve_entity_mentions' to start with a clear action verb. This helps LLMs recognize the tool's purpose immediately.
• Add parameter descriptions: 'mentions' → 'Array of entity names or aliases to cluster (e.g., ["OpenAI", "Open AI", "OpenAI Inc"]). Each string will be compared using Jaro-Winkler similarity.' 'threshold' → 'Similarity threshold (0.0-1.0, default 0.82). Pairs of mentions with similarity >= threshold are grouped into the same cluster.'
• Document output schema in tool definition: 'Returns array of cluster objects, each with: canonical (string, canonical entity name), aliases (array of strings, all mentions in cluster), cluster_size (integer, number of aliases).'
• Add error handling: validate that 'mentions' is non-empty, all items are strings, and 'threshold' is in [0.0, 1.0]. Return actionable errors: 'mentions array is empty, provide at least one entity name' or 'threshold 1.5 is invalid, must be between 0.0 and 1.0.'
• Add parameter constraints to schema: 'mentions' minItems=1, maxItems=1000; 'threshold' minimum=0.0, maximum=1.0. Include these in the description as well for LLM clarity.