Three tools with clear verb-noun naming (send_tweet, get_tweet, get_tweet_replies). All have descriptions and input schemas with types. However, descriptions are terse (10-100 chars, below the 50-200 char LLM-optimized baseline), parameter descriptions lack detail on constraints/formats, and output schemas are not documented. send_tweet lacks error guidance for write failures. No tool annotations (readOnlyHint/destructiveHint). Parameter 'reply_to' and 'cursor' descriptions are minimal. Missing pagination details for get_tweet_replies despite mentioning 'next_cursor'. Overall: functional but underspecified for LLM reasoning.

• Expand send_tweet description to ~100 chars: 'Send a tweet to your timeline. Optionally reply to an existing tweet by ID. Text must be ≤280 characters. Returns the created tweet ID and URL.'
• Add parameter constraints: 'text' → 'Tweet content (max 280 chars, required)', 'reply_to' → 'Tweet ID (numeric string or full x.com/twitter.com URL) to reply to. If invalid, returns error with available tweet IDs.'
• Document output schema for each tool: send_tweet returns {tweet_id, url, created_at}; get_tweet returns {id, text, author, created_at, reply_count, like_count}; get_tweet_replies returns {replies: [{id, text, author, created_at}], next_cursor}.
• Add error handling to send_tweet: 'If text exceeds 280 chars, returns error with char count. If reply_to ID not found, suggests similar tweet IDs. If rate-limited, returns retry_after_seconds.'
• Add tool annotations via MCPServer: mark send_tweet with destructiveHint=true, get_tweet and get_tweet_replies with readOnlyHint=true, to signal intent to LLM.