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

With no annotations provided, the description carries the full behavioral burden. It does disclose useful traits: case-insensitive matching, substring containment across cells, and a 50-row cap. However, it is silent on result ordering, what happens when more than 50 rows match, and the exact return shape.

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 dense sentence where every clause carries information: scope, matching predicate, case-sensitivity, and result cap. It is appropriately front-loaded with the key matching behavior and contains zero filler.

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 2-parameter tool, the invocation essentials are covered, and 'Rows of the Monthendly dataset' hints at the return shape. But with no output schema and no annotations, the lack of ordering, truncation, and empty-match behavior leaves the definition minimally adequate rather than complete.

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 coverage is 50% — query is described ('text to look for in any cell') while limit has no description. The description adds the case-insensitive nuance and confirms the query semantics, and 'up to 50' clarifies the effective cap, but it does not fully compensate for the undocumented limit parameter's 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 precisely identifies the resource ('Rows of the Monthendly dataset') and specifies the matching predicate: cells containing the query, case-insensitive, capped at 50. It is clear and specific, though the verb is carried by the name/title ('Search the dataset') rather than the description itself, and sibling differentiation is implicit rather than explicit.

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?

No guidance is provided on when to use this tool versus its siblings. There is no mention of dataset_row for fetching a specific row, dataset_top for previewing, or dataset_columns for schema access, and no exclusion criteria or alternatives are named. Usage context is only loosely implied by the description.

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