5 tools with basic schemas and descriptions, but significant gaps. All tools have input schemas with type definitions and descriptions present. However, descriptions are minimal (10-50 chars), parameter descriptions lack detail on constraints/formats, and output schemas are completely undocumented. No error handling guidance, no recovery paths. Tools lack annotations (readOnlyHint/destructiveHint). Naming is verb-based but generic ('x_post', 'x_read_*', 'x_send_dm'). No pagination support despite read tools. Confirmation gate exists for writes but no structured error responses.

• Document output schemas for all tools. E.g., x_post should return {tweet_id: string, created_at: ISO8601, url: string} instead of free-text. x_read_mentions should return {mentions: [{id, text, author_id, created_at}], total_count: int}.
• Add min/max bounds to numeric parameters. E.g., 'limit: integer, minimum 1, maximum 10' in schema and description. Add format hints to string IDs: 'tweet_id: string (numeric Twitter ID, e.g. "1234567890")'.
• Expand tool descriptions to 100-200 chars. Include when to use, what it returns, and any prerequisites. E.g., 'Read recent tweets mentioning the user (up to 10). Returns tweet ID, text, author ID, and timestamp. Use this to monitor mentions before replying.'
• Implement structured error responses. Return {success: false, error: string, error_code: string, recovery_hint: string} instead of free-text. E.g., {error: 'Invalid tweet_id', error_code: 'INVALID_ID', recovery_hint: 'Use x_read_mentions to find valid tweet IDs.'}
• Add tool annotations to schema. Mark x_read_mentions and x_read_dms with readOnlyHint: true. Mark x_post, x_reply, x_send_dm with destructiveHint: true. This signals to LLMs which tools have side effects.