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

With no annotations, the description carries the full disclosure burden. It does contribute one real behavioral fact — results come back 'in the order given' — but says nothing about return shape, error conditions when a column or value doesn't exist, or how many rows to expect, which leaves meaningful gaps for a tool with no output schema.

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?

It is a single short sentence with no filler, which is good, but it is grammatically incomplete and front-loads an awkward relative clause rather than the action. Brevity here reflects under-specification rather than disciplined editing.

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 tool with no annotations, no output schema, and 0% parameter documentation, the description should do far more work. It omits the return structure (presumably the matched rows), any indication of how comparison output is arranged for 'X vs Y', and edge-case behavior, leaving the agent to guess at call outcomes.

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 for both parameters. It partially does: 'column is any of the given values' maps the filter semantics onto the `column` and `values` pair, and 'in the order given' clarifies that `values` order drives output order. It still never states that `column` is a column *name* or what happens with unmatched values.

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 resource (rows of the Procedure Cost Checker dataset), the filter (a column matching given values), and an intended use case ('X vs Y' questions). However, it is a sentence fragment with no verb, so it never plainly states that it *returns* those rows, and it doesn't clearly differentiate itself from siblings like dataset_row or dataset_search beyond the vague 'X vs Y' phrase.

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?

'For "X vs Y" questions' is a genuine usage signal that implies when to reach for this tool, and the 2–10 value constraint hints at comparison scenarios. But there is no explicit when-not guidance and no alternative sibling is named, so the agent must infer the routing decision.

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