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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions that rows are returned 'in the order given', which is a behavioral detail, but it is ambiguous whether that order refers to the input values or the dataset's natural order. It does not disclose what happens when no rows match, whether all columns are returned, case sensitivity, or any error behavior. For a read-only filter tool, this is a significant transparency gap.

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 sentence that is front-loaded with the main action ('The rows of the Xlifflane dataset...') and efficiently conveys the filtering and ordering behavior. There is no waste, though the phrase 'in the order given' could be more precise. 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 tool has only 2 parameters and no output schema or annotations, the description is expected to cover essential usage context. It does explain the core function but fails to describe the return format (e.g., does it return full rows? side-by-side as the title suggests?) or any edge cases. The title mentions 'Compare rows side by side', but the description does not elaborate on the output structure, leaving the agent uncertain about what to expect. This is a notable gap for a simple 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?

The schema has 0% description coverage, so the description must compensate. It does explain the roles of 'column' (the field to filter on) and 'values' (the values to match) by stating 'whose column is any of the given values'. This adds meaning beyond the bare schema. However, it does not explicitly define the constraints (e.g., minimum 2 values) or clarify that values must be strings, which are left to the schema. It partially compensates but not fully.

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 clearly states the tool returns rows from the Xlifflane dataset filtered by a column matching any of the given values, in the specified order. It conveys a specific verb (returns rows) and resource (dataset), and hints at a comparison use case ('for X vs Y questions'). However, it does not explicitly differentiate from sibling tools like dataset_search, which also filters, so it misses a clear distinction.

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 description provides a usage context: 'for X vs Y questions' implies comparing two or more specific values of a column. This gives a clear situational cue. However, it does not mention when not to use this tool, nor does it name alternatives or exclusions, so the guidance is incomplete.

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