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

With no annotations and no output schema, the description carries the full disclosure burden. It discloses one real behavioral trait — result ordering follows the order of the supplied values — but says nothing about what a returned row contains, whether both sides of the comparison are guaranteed present, or what happens when a value matches nothing.

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 padding, which is good. But it is a sentence fragment with no verb, so the key action is front-loaded only as an implied predicate, costing clarity at no saving in length.

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?

Two required parameters at 0% schema coverage, no annotations, no output schema — the description should be doing far more work. One sentence covering the dataset, the filter, and an ordering hint is not enough for an agent to invoke this confidently over its many row-returning siblings.

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 does add real meaning: 'column' is the field to match on and 'values' is an ordered list whose sequence drives output order, which goes beyond the bare schema types. It does not clarify the minItems/maxItems bounds or whether values must be distinct, leaving gaps for a 0%-coverage schema.

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 text names the dataset and the returned entity (rows whose column matches given values), which lets an agent infer this is a filtered row retrieval. However, it is a verbless noun phrase, and it never says what the tool 'compares' despite the name and title 'Compare rows side by side', so the distinctive comparison behavior is only implied by the trailing 'X vs Y' clause.

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 closing clause 'for "X vs Y" questions' gives an implied usage trigger, which is more than nothing. But no alternative is named — an agent cannot tell from this text when to prefer dataset_compare over dataset_row or dataset_search, both of which also return rows.

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