Server has 4 tools with complete input schemas and descriptions, but quality is uneven. Tool names follow verb_noun convention (report_, get_, get_best_, get_trending_). Descriptions are present (100-150 chars) but lack actionable context for LLM selection. Parameters have types and descriptions, but lack constraints (enums, ranges, validation guidance). Output schemas are partially documented in code but not formally declared. Error handling is minimal, no recovery guidance or categorization. No tool annotations (readOnlyHint, destructiveHint). The report_tool_result tool modifies state but lacks confirmation/dry-run pattern. Overall: functional but below production baseline.

• Add enum constraints to quality_score (1-10), limit (1-100), and days (1-365) in input schemas. Include min/max in parameter descriptions.
• Add tool annotations: mark get_* tools with readOnlyHint=true; mark report_tool_result with destructiveHint=true and idempotentHint=false.
• Implement dry-run mode for report_tool_result: add optional 'dry_run' parameter that returns 'Would record: ...' without persisting to database.
• Document output schemas formally (JSON Schema) for each tool. Specify field names, types, and whether arrays are paginated.
• Enhance error messages with recovery guidance: 'No feedback data for tool_name. Try report_tool_result() to add feedback, or search get_best_tools() for alternatives.'