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

No annotations are provided, and the description does not disclose side effects, output structure, or error behavior. As a read-only operation, missing annotation lowers transparency; the description does not compensate.

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 a single concise sentence that conveys the core functionality without unnecessary verbosity. It lacks structural elements like examples but remains efficient.

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 sibling tools, the purpose is fairly clear, and the description adds the ordering detail. However, it does not specify the output format or edge cases (e.g., no matches), so completeness is not full.

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 explains that 'column' is the field to filter on and 'values' are the matching values, with ordering respected. This adds meaning beyond the raw schema, though the exact matching semantics (e.g., exact vs substring) are not detailed.

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 tool filters rows based on a column matching any of the given values, and mentions the use case for 'X vs Y' questions. However, it could be more explicit about the comparison semantics and the exact return format.

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 explicit guidance on when to use this tool instead of alternatives like dataset_search or dataset_row. The phrase 'for X vs Y questions' offers some context but does not differentiate from sibling tools.

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