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

With no annotations, the description carries the whole behavioral burden. It does disclose a real trait beyond the schema: returned rows preserve the order of the supplied values. But it says nothing about read-only semantics, output shape, error behavior when a value matches nothing, or the 10-value ceiling.

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?

A single tight sentence with no filler, and the core matching rule leads. The em-dash usage clause lands awkwardly at the end of a grammatically tangled clause, but nothing is wasted.

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?

No output schema and no annotations mean the description should describe the return payload, and 'the rows' is only a vague gesture at it. For a compare-oriented tool, it also omits the value-count limit and how missing matches surface, leaving meaningful gaps for an agent to guess at.

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 clarify that 'values' are matched against 'column' and that value order drives row order, which is real added meaning. It still never explains what a valid column name looks like (presumably from dataset_columns) or the minimum/maximum value count.

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 VPNCompareHQ dataset), the matching condition (column equals any of the given values), and the ordering guarantee. It is a noun-phrase fragment rather than a verb-led statement, and it never differentiates itself from the closely related dataset_search or dataset_row siblings, so it falls short of a 5.

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?

It gives a genuine usage trigger with '"X vs Y" questions', which tells the agent when this is the right call. However it names no alternative tool and no when-not condition, so the agent must infer the boundary between this and dataset_search on its own.

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