This server has critical gaps in definition quality. All 4 tools lack parameter descriptions, the rubric requires every parameter to have a description explaining what it controls. Tool descriptions are extremely terse (6-24 chars), well below the 10-1024 char baseline and the 50-200 char LLM-optimized range. No output schemas are documented. Tool names lack action verbs (user, kata are nouns, not verb_noun patterns like get_user, get_kata). No error handling guidance, no pagination documentation for user_completed despite accepting a page parameter. The codebase shows inline tool definitions with minimal metadata.

• Rename tools to action verbs: 'user' → 'get_user', 'user_completed' → 'list_user_completed_challenges', 'user_authored' → 'list_user_authored_kata', 'kata' → 'get_kata'. This matches the verb_noun baseline and helps LLMs infer intent from the name alone.
• Expand tool descriptions to 50-200 characters. Example: 'get_user: Retrieve a Codewars user profile including rank, honor points, and language proficiencies. Pass a username to fetch their public profile.' This tells the LLM what data is available and when to call it.
• Add descriptions to all parameters. Example for 'username': 'Codewars username (case-insensitive, 2-50 characters). E.g. "jhoffner". This is the public username visible on the user's profile page.' For 'page': 'Page number for pagination (1-indexed). Default is 1. Each page contains up to 50 completed challenges.'
• Document output schemas for each tool. Example for get_user: 'Returns {username, name, rank, honor, clan, leaderboard_position, languages}'. This lets agents know what fields to expect and plan chaining.
• Add error handling guidance. Example: 'If username is not found, returns error 404. Suggest the user check the spelling or call list_users() to search by partial name.' This guides the agent's recovery strategy.