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

No annotations are provided, so the description carries the full disclosure burden. It does add one genuine behavioral fact not present in the schema: results come back 'in the order given', which matters for side-by-side comparison. It says nothing about read-only nature, cardinality or limits, behavior when a value has no match, or the shape of the returned rows, leaving real gaps.

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 compact sentence with no filler, and the core mechanics are front-loaded before the 'X vs Y' use case. The em-dash clause is slightly clumsier than a separate sentence would be, 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?

The schema is tiny and there is no output schema or annotations, so the description has to stand in for the missing context. It explains matching and ordering but never says what a result row looks like, how many rows can come back, or what happens when column is unknown or a value matches nothing — an agent could still call it, but not predict the response.

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 does: 'whose column is any of the given values' clarifies both the target parameter (column) and the any-of/OR matching semantics of values, which the bare schema does not convey. It also documents the output ordering tied to the values array. What it omits is whether column expects a header name versus an index, leaving one small ambiguity.

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?

Names the operation and the resource precisely: returns the dataset rows whose column matches any of the supplied values, with an intent tag ('X vs Y' questions). The mechanics (an OR-filter over one column) are clear even though the tool is named 'compare' rather than 'filter'. It does not explicitly contrast itself with siblings like dataset_search or dataset_top, so it stops 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?

The phrase 'for "X vs Y" questions' implies the usage scenario, giving the agent a rough trigger condition. However, it names no alternative tools and states no exclusions (e.g., how this differs from dataset_search when you want a keyword match rather than exact values), so the guidance remains implied rather than explicit.

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