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

No annotations are provided, so the description carries the behavioral disclosure burden. It does disclose row selection and order preservation, which are meaningful behaviors. But it does not explain output format, exact-match/case sensitivity, or what happens when a value has no matching rows.

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 a single compact sentence that includes the resource, filtering logic, ordering behavior, and intended use-case. The phrasing 'whose column is any of the given values' is slightly awkward, but every component earns its place and there is no redundant filler.

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 tool with low schema richness, the description covers the essential invocation semantics: what dataset, which column, what values, and the ordering behavior. No output schema exists, but the result type (rows for comparison) is reasonably implied by the title and description.

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%, so the description must compensate. It effectively communicates that 'column' is the field to match against and 'values' is the list of allowed values, and it clarifies the relationship between them. It does not explicitly name the parameters, but the relational semantics are clear.

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 identifies the resource (Clientvo dataset), the operation (select rows where a column matches any of the given values), and the ordering behavior (in the order given). It lacks an explicit imperative verb like 'returns' or 'retrieves', but the intent is unambiguous and distinct enough even without sibling names.

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 phrase 'for "X vs Y" questions' gives useful usage context, implying the tool is for comparing rows for two or more values. However, it does not state when not to use it, mention alternatives, or describe prerequisite conditions.

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