This server demonstrates moderate definition quality with significant gaps. All 6 tools have descriptions (10-200 chars range), but parameter documentation is inconsistent. Tools like `execute_sql` and `lookup_entry` have well-defined input schemas with type and description fields. However, `list_tables` and `report_validation_result` lack visible input schemas in the provided code. Output schemas are not documented for any tool, forcing LLMs to infer response structure. Error handling guidance is absent, tools do not indicate what failures mean or how to recover. The server follows basic naming conventions (verb_noun pattern) but lacks the depth of parameter constraints (enums, ranges, format specs) expected in production tools. No tool declares permissions, audit requirements, or idempotency guarantees.

• Document output schemas for all tools. Specify field names, types, and whether results are paginated. E.g., `list_tables` should return `{tables: [{name: string, row_count: number}], total: number}`.
• Add input schema to `list_tables`. If it takes no parameters, explicitly document this: `input: {type: 'object', properties: {}, required: []}`.
• Enhance parameter descriptions with format specs and constraints. E.g., `table_name: 'Fully qualified BigQuery table name (format: project.dataset.table, e.g., bigquery-public-data.google_trends.top_terms)'`.
• Add error handling guidance to tool descriptions. E.g., `execute_sql`: 'Returns error if query is invalid SQL, table/column does not exist, or user lacks permissions. If invalid, use `report_validation_result` to guide fixes.'
• Clarify `report_validation_result` purpose and add idempotency/side-effect declaration. If it controls agent flow, document the state mutation it triggers.