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

No annotations are supplied, so the description bears the full disclosure burden. It does add one real behavioral trait — result ordering follows the order of supplied values — but never states that this is a read-only operation, how many rows come back, what happens with unknown values, or what the response looks like.

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?

Single short sentence with no padding, and the core filter semantics come first. The value is undercut by the missing predicate verb and by the use-case clause being tacked on at the end rather than integrated.

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?

A simple two-parameter read tool with no annotations and no output schema still needs the description to confirm read-only safety, expected result shape, and parameter limits — none of which appear. The description gives enough to guess the call but not enough to call it with confidence.

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 coverage is 0%, so both parameters are undocumented in the schema and the description must compensate. It conveys the meaning of 'column' and 'values' and the ordering guarantee, but omits the concrete constraints already in the schema (minimum 2 values, maximum 10) and adds no format guidance for value strings.

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 fragment states a specific filter behavior — rows whose column value is any of the given values, returned in the given order — so the resource and operation are inferable. However it is verbless (reads as 'The rows of...') and offers nothing that distinguishes it from siblings like dataset_search or dataset_row, leaving the agent to guess at the boundary.

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 clause 'for "X vs Y" questions' gives a genuine when-to-use cue, which is more than nothing. It stops short of naming an alternative or stating when not to use it (e.g. single-value lookup vs multi-value comparison).

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