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

With no annotations, the description carries the behavioral disclosure burden. It does disclose case-insensitive matching and the 50-result ceiling, but it does not state result ordering, whether matches are substring-only beyond 'contain', or what an empty result set signifies.

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?

One compact sentence front-loads the resource and predicate, includes the key matching behavior, and adds no filler. Every clause contributes meaning.

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 with only two parameters, but there is no output schema, and the description does not specify which row fields are returned or how results are ordered. It is adequate for a basic search, but an agent still has to guess about the result shape beyond 'rows'.

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%; the query parameter is already described as text to look for in any cell. The description adds 'case-insensitive' to query and 'up to 50' to limit, the latter largely repeating schema constraints. It does not clarify the default limit or whether rows are returned in any particular order.

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?

States a specific action: return rows whose cells contain a query string, with case-insensitivity and a 50-row cap. This clearly separates it from siblings like dataset_row, dataset_top, and dataset_columns, which serve different purposes.

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 on when to prefer this tool over siblings such as dataset_row or dataset_top. The description implies a general search use-case but gives no exclusions, alternatives, or prerequisites.

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