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

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds meaningful details beyond the schema: matching is case-insensitive, it searches across cells, and results are capped at 50 rows. It does not mention ordering, default limit behavior, or what happens with no matches, but the disclosed behavior is clear and useful.

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 that front-loads the core operation and includes the two most important behavioral constraints: case-insensitive cell matching and the 50-row cap. There is no filler or repetition of schema information.

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 two-parameter search tool with no output schema, the description covers the essential semantics: what is searched, how matching works, and the result limit. It could be more complete by noting the default limit and result shape, but an agent has enough information to call the tool correctly in the common case.

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?

Schema description coverage is only 50%, since limit has no schema description. The tool description compensates by explaining that the result size is capped at 50, which maps directly to the limit parameter, and by adding case-insensitivity semantics for query. It does not explain the default value when limit is omitted, but the main parameter behaviors are clarified.

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 that the tool returns rows of the Eobify dataset matching a query in any cell, with case-insensitive matching and a limit of 50. This is specific enough to distinguish it from sibling tools like dataset_stats or dataset_columns, though it lacks an explicit verb and does not directly name any sibling it is not.

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 primary use case: find rows containing arbitrary text. However, it provides no explicit guidance on when to prefer this over sibling tools such as dataset_row or dataset_top, and it does not mention exclusions or alternative tools even though the sibling list makes selection decisions relevant.

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