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

No annotations are provided, so the description carries the full behavioral burden, yet it only implies read-only retrieval and discloses order preservation. It says nothing about what happens when a value matches no rows, whether results are paginated, or how many rows are returned, and it does not mention the 10-value cap.

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 compact sentence with the resource and matching rule front-loaded and the use case appended after an em dash. It is slightly fragment-like (no verb) but wastes no words.

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 two-parameter retrieval tool with no output schema and no annotations, the essentials (dataset, filter semantics, ordering, intent) are covered. However, return shape, missing-value behavior, and the values cap are absent, leaving meaningful gaps the agent must guess at.

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 0%, but the description does explain both parameters semantically: 'column' is the filter attribute and 'values' is an ordered list to match against, with matching being 'any of'. It does not convey the 2–10 item constraint enforced by the schema, so it only partially compensates for the coverage 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 names the concrete resource (rows of the Working Capital Quotes dataset) and the selection rule (column equals any of the given values, in the given order). The 'for X vs Y questions' clause gives an intent that helps distinguish it from dataset_row (single row) and dataset_stats, though it never uses an explicit verb and doesn't clearly separate itself from dataset_search.

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 trailing 'for "X vs Y" questions' clause implies the use case, which is the only usage guidance present. There is no explicit when-not guidance and no sibling alternative named (e.g., dataset_search or dataset_row), so the agent must infer selection criteria itself.

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