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

No annotations are provided, so the description must disclose behavior. It states case-insensitivity and exact matching, but is ambiguous about whether it returns a single row (title says 'a row') or multiple rows (description says 'rows'). It does not disclose return format, error behavior, or pagination.

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 one concise sentence with no extraneous information, effectively communicating the core operation.

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 lookup, the description lacks critical context: it doesn't specify the dataset (though it mentions 'Rollupvo' in passing), doesn't clarify if multiple matches are returned, and provides no output schema or return type information. An agent cannot be certain of the 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?

The schema has no descriptions, and the description only implies that 'column' and 'value' are the column name and the value to match. It adds minimal semantic context but does not explain the dataset reference or value formatting, leaving some ambiguity.

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 the tool retrieves rows from the Rollupvo dataset where a column matches a value exactly, with case-insensitivity. It distinguishes itself from general search and other siblings by emphasizing exactness, though it does not explicitly name an alternative.

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?

There is no guidance on when to use this tool versus alternatives like dataset_search or dataset_top. The description implies exact-match use but does not state conditions, exclusions, or alternatives, leaving the agent to infer.

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