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

With no annotations, the description carries the behavioral disclosure burden. It usefully discloses the filter logic ('whose column is any of the given values') and ordering ('in the order given'), but it omits matching exactness, case sensitivity, return shape, or any side-effect/read-only guarantees.

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?

One sentence conveys the core behavior and the intended use case without repetition. The phrasing is slightly awkward ('The rows ... whose column is any'), but every element earns its place.

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 tool is simple and the description gives enough to attempt a call, but without annotations or an output schema, more detail would help: exact-match behavior, row output format, and how this differs from dataset_search or dataset_row. It is adequate but not fully 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 does tie 'column' to the matching field and 'values' to the list used for filtering, and it explains ordering. However, it does not define exact-match semantics or value formatting beyond what the schema's types already provide.

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 specifies the operation: return rows from the DrawScheduleWorks dataset filtered by a column matching a list of values, preserving the given order. The title adds the 'compare side by side' framing, though the description itself lacks an explicit verb and does not directly name sibling tools.

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' provides clear context for when this tool should be used. It does not explicitly contrast it with sibling tools like dataset_search or dataset_row, but the described behavior is specific enough to imply its niche.

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