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

With no annotations, the description carries full behavioral burden. It discloses only the result ordering ("in the order given"), which is useful. It says nothing about whether the hardcoded dataset can vary, case sensitivity, what happens for missing values, or any limits on how many values can be compared.

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 tight sentence, which is good, but the front-loading is weak (the reader must reach the em-dash to learn the tool's actual purpose) and the hardcoded dataset name inflates the sentence without helping tool selection.

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 annotations and no output schema, so the description is the only source of behavioral and return information, and it provides neither. The value-count limit, the fixed dataset, and the shape of the returned rows are all undisclosed, leaving real gaps for a filtering tool.

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, and it partly does: "column is any of the given values, in the order given" explains both parameters and clarifies that the values array is a match-any list whose order matters. It omits the 2–10 item constraint and the non-empty string requirement, so the schema constraints remain unexplained.

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 conveys that it returns rows of a specific dataset filtered by a column matching any of the given values, in the given order, and frames it for "X vs Y" questions. However it is a noun phrase with no verb, and it hard-codes "Asbestos Survey Cost dataset" rather than treating the dataset as a parameter, which muddies what resource is actually being operated on.

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 cue that pairs with the title's "Compare rows side by side." But it names no alternatives and gives no exclusions versus the clearly overlapping siblings dataset_search, dataset_row, and dataset_top, so the agent must still guess whether this or a search tool is correct.

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