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

No annotations are provided, so the description carries the burden of disclosing behavior. It adds important behavioral details: case-insensitive matching, matching across cells, and a 50-row cap. It does not mention ordering or exact output structure, but for a simple search tool it discloses the key runtime traits an agent needs.

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 sentence with no filler. Every phrase contributes: 'Rows', 'Consentvia dataset', 'cells contain the query', 'case-insensitive', and 'up to 50'. Critical information is front-loaded and easy to scan.

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?

For a two-parameter search tool with no output schema, the description is mostly complete. It tells the agent what is searched, how matching works, and the maximum result count. It could be slightly richer by naming the limit parameter or describing the exact row output, but the call can be correctly constructed from the available information.

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 input schema describes the query parameter but leaves limit undocumented, giving 50% schema coverage. The description compensates by explaining the query semantics ('contain the query, case-insensitive') and the result cap ('up to 50'), which clarifies how both parameters affect the call. It adds value beyond the schema without fully detailing default behavior.

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 and resource: it returns rows of the Consentvia dataset that match a query. It specifies the matching behavior as containing the query in cells, which distinguishes it from sibling tools like dataset_columns, dataset_stats, or dataset_row. The scope 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?

The description implies the tool should be used when an agent needs rows by arbitrary cell text, but it does not explicitly say when to use this over alternatives such as dataset_row, dataset_top, or dataset_compare. Usage context is reasonably clear from the wording, but no explicit when/when-not guidance is provided.

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