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

No annotations are provided, so the description carries the full burden. It discloses the matching behavior ('whose column is any of the given values') and the ordering behavior ('in the order given'). It does not mention read-only status, but that is implied as a data query tool. Overall, the behavior is transparent enough for the intended use.

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, focused sentence that front-loads the key behavior and use case. No redundant words or unnecessary details. The title is also concise and descriptive.

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?

With no output schema, the description indicates the result is 'rows of the Lanyardo dataset', which suggests full-row objects. It does not specify whether all columns are returned or how no-match results are handled, but for a straightforward comparison tool this is mostly adequate. The ordering behavior is clearly stated, which is important for side-by-side comparison.

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 only provides types and constraints, with no per-parameter descriptions. The description explains the role of both parameters: 'column' is the field to match against, and 'values' are the list of allowed values, with the output ordered by that list. This adds meaningful context beyond the raw schema.

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 title 'Compare rows side by side' and description 'The rows of the Lanyardo dataset whose column is any of the given values, in the order given' clearly state the tool's function. It retrieves matching rows based on a column and value list, which is distinct from sibling tools like dataset_row (single row), dataset_search (search across columns), and dataset_stats (aggregate statistics).

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 explicitly states the use case 'for "X vs Y" questions', which guides when to use this tool. It does not explicitly name sibling alternatives, but the use case hint is sufficient to differentiate it from the other dataset tools.

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