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

With no annotations provided, the description must carry the behavioral disclosure burden. It adds useful detail—case-insensitive matching and a 50-row cap—but omits other behavioral traits such as default limit behavior, zero-result handling, or whether matching is substring-based. It is partial rather than comprehensive.

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 sentence, 13 words, front-loaded with the result type. No filler or redundant phrasing; every word contributes to the tool's purpose and key behavior.

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 simple search tool with no output schema and no annotations, the description conveys the essential behavior: what is searched, how matching works, and the result cap. It does not mention the limit parameter explicitly, but the input schema covers that; overall the definition is close to complete for the tool's complexity.

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 schema already describes query as 'text to look for in any cell' and includes limit with maximum 50. The description's 'cells contain the query' and 'up to 50' mostly restate that existing schema information, adding no meaningful new meaning about the limit parameter or how it controls results.

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 states a specific operation (search rows) on a specific resource (the Subbielane dataset) with precise behavioral constraints (case-insensitive, up to 50 rows). This clearly differentiates it from siblings like dataset_row (which fetches a specific row) and dataset_top (which summarizes data).

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 gives no guidance on when to use this tool versus its alternatives. It does not mention dataset_row, dataset_stats, or any other sibling, nor does it state conditions that would make search preferable over other operations.

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