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

No annotations are provided, so the description carries the full burden. It does disclose one real behavioral trait: results come back 'in the order given,' which tells the agent the output order is tied to the order of the supplied values. It says nothing about what happens when a value has no matching rows, whether the match is exact, or what fields the returned rows contain.

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 sentence with no filler, and the dataset scope is stated up front before the filter and ordering clauses. The only flaw is that it is a fragment rather than a complete sentence, which slightly hurts readability rather than wasting space.

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 and no output schema, the description should say what a returned row looks like and how matching behaves. It gives the dataset scope and ordering but leaves return shape, match semantics, and empty-result behavior entirely undocumented.

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 clarifies that 'column' is the field matched against and that 'values' is an ordered list whose order drives the result ordering, which is genuine added meaning, but it omits the 2-to-10 item bounds and whether matching is exact or partial.

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 Working Capital Quotes dataset) and the filter operation (rows whose column matches any of the given values), plus the ordering rule. But it is a sentence fragment with no explicit verb and never states that it returns the rows for side-by-side comparison, so the agent must infer the operation from the title and the '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?

The clause 'for "X vs Y" questions' gives an implied usage context that points at comparison scenarios. There is no explicit when-not guidance, no prerequisites, and no named alternative among siblings such as dataset_search or dataset_row, so routing between similar tools is left to inference.

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