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

With no annotations, the description carries the full behavioral burden, and it only discloses one trait: rows are returned in the order the values were given. It says nothing about read-only safety, result size, whether the returned rows are truncated, or any permission/scope requirements.

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 front-loaded sentence that leads with what is returned. Untidy dash clause and slightly tangled phrasing, but no wasted content.

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 two-parameter, no-annotation, no-output-schema tool, the description covers filtering and ordering but not the shape of the result (how the two compared rows are returned, which columns come back), leaving a real gap for an agent constructing a 'vs' answer.

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 the description must compensate, and it partially does: it clarifies that 'column' is the attribute matched against and 'values' is a set matched with OR semantics, in caller-specified order. It never says whether column must be an exact dataset header name, nor why values is capped at 10.

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?

States a specific operation: return the rows of a named dataset whose column matches any of the given values, preserving order. The 'compare' framing is loose (it filters rather than computes a comparison), and it doesn't explicitly distinguish itself from siblings like dataset_row or dataset_search, but the filter semantics are concrete enough to identify it.

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' gives an implied usage context, which is more than nothing. However, it names no alternative tool and gives no condition for choosing this over dataset_row, dataset_search, or dataset_top.

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