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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It discloses case-insensitive matching and the 50-row cap, but omits the output format, row ordering, pagination behavior, and what happens when the query matches non-string cells.

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, front-loaded sentence communicates the essential behavior with no filler. Every clause adds either matching semantics or a constraint.

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 description is sufficient for a basic call, but with no output schema, it should clarify the response structure and pagination limitations more explicitly. The mention of 'rows' implies the return type, but an agent still lacks detail on the exact result shape.

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%, and the description adds useful semantics by clarifying query matching is case-insensitive and across any cell, and by stating the up-to-50 limit. However, the limit parameter's exact role beyond the cap is not elaborated, so the compensation is partial.

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 operation: returning rows of the DamageRestore HQ dataset that contain the query in any cell, with case-insensitivity and an upper bound. This clearly distinguishes it from siblings like dataset_columns, dataset_row, and dataset_stats.

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 intended use as a full-text row search is implied by the description, but there is no explicit guidance on when to choose this tool over alternatives such as dataset_row or dataset_top, nor any exclusions or conditions.

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