execute_sql_query

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It discloses only the CSV output format; it never states whether queries are read-only, whether DDL/DML (INSERT/DELETE/DROP) is permitted, permission/auth requirements, row or time limits, or cost implications for a raw SQL execution surface.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero waste. It is efficient, though arguably too terse for a powerful SQL execution tool with no annotations to back it up.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema exists, so the description's mention of CSV return format usefully covers the result shape, and the schema handles SQL syntax. However, for a raw SQL tool with no annotations, it omits critical operational context (read-only vs mutating, limits, required dataset discovery step).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% and the query parameter carries detailed syntax guidance (dataset ID in double quotes, columns in backticks) that the thin description does not repeat. Baseline 3 is appropriate since the schema does the heavy lifting and the description adds no parameter meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Execute) and resource (SQL query against Rockfish datasets) plus the return format (CSV), which an agent can distinguish from sibling dataset CRUD tools. It doesn't explicitly name an alternative, but no other sibling executes SQL, so the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to prefer this over the structured dataset tools (e.g., get_dataset, get_dataset_schema, or list_datasets) and no prerequisite noted, such as needing a dataset ID discovered from get_dataset_schema. Usage is only implied by the tool name.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.