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

With no annotations provided, the description carries the behavioral disclosure burden. It usefully discloses case-insensitive matching, searching across all cells, and the 50-row cap. However, it does not describe output shape, ordering, or behavior when no rows match.

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 with no filler. It front-loads the core behavior and includes the most important constraint immediately.

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 core search behavior plus row cap are present. However, with no output schema, the description leaves the return format and the meaning of 'rows' somewhat underspecified, and it does not clarify whether the 50-row limit is a default or maximum.

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 query parameter is already described in the schema, and the description adds case-insensitivity and 'any cell' semantics. The limit parameter's meaning is only weakly implied by 'up to 50' and its schema constraints, leaving room for more explicit documentation.

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 Rotazo dataset matching a case-insensitive query across cells. This identifies the resource and core operation, though it does not explicitly contrast with sibling tools.

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 dataset_row, dataset_columns, dataset_top, or the other siblings. There is no mention of exclusions, prerequisites, or alternative tool selection.

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