SQLSense has clear, well-structured tool definitions with proper schemas and descriptions. All 4 tools have non-empty descriptions (avg ~120 chars, within baseline 34-392 range) and complete input schemas with typed properties. However, parameter descriptions are sparse or missing context. The sql_query tool lacks guidance on what 'params' should contain or how to structure them. Output schemas are not documented, LLMs cannot predict what fields to expect from query results. Error handling descriptions are generic ('Blocked queries return an error with the reason') without actionable recovery guidance. No tool annotations (readOnlyHint, destructiveHint) despite clear risk profiles (sql_query is WRITE, others READ_ONLY). Parameter constraints (e.g., limit range for get_audit_log) are absent. Overall solid foundation but missing LLM-optimization details.

• Add output schema documentation to all tools. For sql_query, document result structure (rows array, column names, types). For get_schema, document table/column objects. For get_audit_log, document audit entry fields (timestamp, query, user, status).
• Add tool annotations: set destructiveHint=true on sql_query; set readOnlyHint=true on get_schema, explain_query, get_audit_log. This enables agents to reason about safety.
• Expand 'params' parameter description: 'Optional named parameters for parameterized queries. Pass as key-value pairs (e.g., {"user_id": 123}). Parameters are bound using ? or :name syntax depending on dialect.'
• Add parameter constraints: limit in get_audit_log (min=1, max=1000); sql in sql_query (max=10000 chars); table in get_schema (optional, pattern for valid identifiers).
• Enhance error descriptions with recovery guidance. E.g., 'Blocked queries return an error with the reason. Call explain_query() to validate before retrying, or check guardrails documentation for allowed patterns.'