Four tools with clear verb-noun naming (get_*, search_*) and reasonable descriptions (100-200 chars). All tools have input schemas with types and descriptions. However, output schemas are undocumented, LLMs cannot plan downstream calls or extract fields reliably. Error handling is minimal: get_story and get_comments return bare error dicts without recovery guidance. Parameter constraints (count 1-30, limit 1-30) are enforced in code but not declared in schema, forcing LLMs to guess valid ranges. No tool annotations (readOnlyHint, idempotentHint) despite all being read-only. Missing pagination support, search_stories caps at 500 items but returns all matches without limit/offset params or total count.

• Document output schemas for all tools. Example for get_story: 'Returns {id: int, title: str, url: str, text: str, score: int, by: str, time: int, type: str, comments_count: int, comment_ids: [int]}'.
• Add min/max constraints to input schemas: count and limit params should declare 'minimum': 1, 'maximum': 30 (or 500 for search_stories).
• Enhance error messages with recovery hints. Change get_story error to: 'Item {story_id} not found. Try search_stories(query=...) to find valid story IDs.'
• Add pagination to search_stories: accept 'offset' param (default 0) and return {results: [...], total_count: int, has_more: bool}.
• Add tool annotations via FastMCP: decorate all tools with readOnlyHint=True and idempotentHint=True to signal safety to agents.