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

With no annotations, the description carries the behavioral burden. It discloses case-insensitive matching and the 50-row cap, which is useful. But it does not clarify whether full rows are returned, what happens when no rows match, whether the limit applies as a default, or any ordering/performance behavior, leaving notable gaps.

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 entire description is one crisp sentence that front-loads the core behavior (rows with matching cells), then adds the case-insensitive and limit modifiers. Every word 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?

Despite lacking an output schema, the description's 'Rows... up to 50' gives the agent a clear expectation of result shape and scale. For a simple 2-parameter search tool, this is largely sufficient, though a note on default limit or empty results would make it fully 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 in the schema, limit is not. The tool description adds the 'case-insensitive' nuance and confirms the 50-row ceiling, but it does not explain limit's default value or interaction with the query, so it only partially compensates for the schema gap.

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 action: returning rows of the Exitvo dataset whose cells contain the query, with a clear scoping detail (case-insensitive, up to 50). It clearly differentiates from siblings like dataset_row or dataset_columns by describing a content-based search rather than a fetch-by-key or structural operation.

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 usage: use this tool when you need rows matching a text query across cells. However, it does not explicitly mention when not to use it or name alternatives such as dataset_top or dataset_row, so the guidance is implied rather than explicit.

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