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 discloses case-insensitivity and the 50-row cap, which are useful behavioral details. However, it does not mention default limit behavior, ordering, pagination, or error handling, leaving gaps for an agent relying solely on this text.

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, front-loaded sentence with no filler. It immediately states what the tool returns, the matching rule, and the cap, making it efficient and easy to parse.

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?

The tool is simple and the description covers the core function, but it omits practical details like the default limit when 'limit' is not provided, whether results are sorted, or if all columns are returned. Since there is no output schema, these gaps could leave an agent uncertain about the exact response format.

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?

With only 50% schema coverage (query has a description, limit does not), the description compensates meaningfully. It clarifies that 'query' matches any cell (beyond the schema's 'text to look for in any cell') and adds case-insensitivity, while also reinforcing the limit maximum with 'up to 50'. This adds value beyond the schema.

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 verb ('search'), a clear resource ('FlatRateBook dataset'), and precise behavior (rows whose cells contain the query, case-insensitive, up to 50). It clearly distinguishes from sibling tools like dataset_stats or dataset_columns by focusing on content search across all cells.

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 when to use it (when you need to find rows matching a text query) but does not explicitly mention alternatives or when not to use it. There is no comparison to siblings or any exclusion criteria, so the guidance is minimal and relies on the agent to infer context.

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