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

With no annotations, the description carries the burden and does reveal key behavior: case-insensitive substring matching across cells and a 50-row cap. It doesn't disclose default limit behavior when omitted, ordering, or lack of side effects, though read-only nature is implied by 'search'.

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?

Single sentence, front-loaded with the core operation, and no redundant words. It earns its place.

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 without an output schema, the description says what is returned (rows) and how matching works, and the parameters are bounded by the schema. It lacks only minor details like the default limit and ordering, which are not essential for a basic call.

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 covers only query ('text to look for in any cell'); description compensates partially by explaining search semantics and the 'up to 50' result ceiling, which clarifies limit's role. It doesn't fully document the limit parameter's default or effect beyond the maximum.

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 names a concrete verb ('Rows ... whose cells contain') and resource (Attestroom dataset), making it clear this is a row-content search. It is implicitly distinct from sibling tools like dataset_columns and dataset_stats, but does not explicitly differentiate itself.

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 makes the usage context clear: use it to find rows where any cell contains the query, with case-insensitive matching. It provides no exclusion criteria or pointers to alternatives among the sibling tools, so the guidance is adequate but not explicit.

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