Single tool 'tool_search' has a well-structured schema with proper Zod validation and clear descriptions. Input parameters (query, limit) are typed and documented. However, the tool serves a meta-purpose (searching the tool registry itself) rather than domain functionality. Output is unstructured text rather than typed JSON. No error recovery guidance beyond 'no matches' case. Naming is clear (verb_noun pattern), but the tool is utility-focused rather than user-facing.

• Return structured JSON with fields: {matches: [{name, description, permission}], total_count, query_normalized}. This enables LLMs to extract tool names programmatically.
• Add error recovery: when no matches found, suggest partial matches or similar tool names. E.g., 'No exact match for "sarch". Did you mean: search_users, search_files?'
• Document the scoring algorithm in the description so LLMs understand why results are ranked (exact name match > prefix > substring > description).
• Add a 'category' or 'tags' field to tool metadata so agents can filter by domain (e.g., 'file', 'api', 'communication').
• Implement batch tool lookup: add a 'names' parameter accepting an array of tool names to fetch multiple tools in one call, reducing round-trips.