describe_data_query

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

No annotations are provided, so the description carries the full burden. It mentions the tool returns schema, row count, date range, and sample rows, but does not discuss any potential side effects, permissions, or rate limits. It is adequate but not thorough.

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?

The description is very concise, using a clear format: a one-line summary followed by a bullet for the argument. Every sentence provides necessary information without wasted words.

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?

Given the tool's simplicity (1 parameter, no output schema), the description is essentially complete. It explains the return values and the parameter. However, it could benefit from mentioning potential error cases or output format details.

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?

The description adds significant context to the sole parameter query_id by specifying it is a 'Dataset ID from list_data_queries', which explains its origin and role. This compensates for the 0% schema description coverage.

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?

The description clearly states the verb 'describe' and resource 'data query', listing what it returns (schema, row count, date range, sample rows). It distinguishes itself from sibling tools like list_data_queries and safe_query by its specific function.

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?

The description tells the user that query_id comes from list_data_queries, implying when to use it. However, it does not explicitly mention when not to use or alternative tools, leaving some ambiguity.

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