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

There are no annotations, so the description carries the full burden. It discloses the ordering behavior ('in the order given') and the filtering mechanism ('whose column is any of the given values'), which is helpful. However, it does not mention what happens if no rows match, whether the result includes the column used for filtering, edge cases like duplicate values, or any performance or data-volume implications. For a read-style comparison tool, the safety profile is implicit but not stated.

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?

The description is a single compact sentence that front-loads the essential behavior (filtering and ordering) and ties it to a clear use case. It earns its place with two useful pieces of information: the exact match filter and the ordering guarantee. It loses one point because the schema is minimal and the description could have briefly stated the two parameter names, but overall it is appropriately concise.

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?

Given the absence of an output schema, the description does not explain return values or the result format, but that is likely acceptable for a simple comparison tool. It covers the key behavior: selecting rows by column values and preserving order. It omits edge-case behavior (empty results, duplicate values) and does not state whether the output is rendered as a comparison table, which could be relevant for 'X vs Y' questions. Still, for the tool's likely simplicity, the description is largely complete.

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 explains that 'column' is the field used to filter rows and that 'values' are the specific values to match, and it adds the ordering semantics ('in the order given'). It does not explicitly name the parameter keys in the description; an agent must infer the mapping from context. It also does not clarify whether 'given values' corresponds exactly to the 'values' array order, though that is fairly evident from the phrasing.

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 states a specific verb ('Compare rows side by side') and a specific resource (the Cafmlane dataset rows filtered by column values), plus the use case ('X vs Y' questions). It distinguishes this tool from siblings like dataset_row (single-row access) and dataset_search (fuzzy/query-based access), and makes clear it returns multiple rows in a specified order.

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' gives an explicit use-case context, and the instruction that rows are returned 'in the order given' tells the agent exactly how to construct the values array. It clearly implies when this tool is appropriate versus alternatives: when comparing specific row values side by side rather than retrieving one row or searching broadly.

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