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

With no annotations, the description must carry the full burden of behavioral disclosure. It reveals that output order follows the given values and that matching is 'any of' (inclusive), but it does not mention what happens on no matches, whether matching is case-sensitive, or the structure of returned rows. These gaps are significant for an agent deciding whether this tool fits.

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 core behavior and includes a usage hint. There is no fluff; every word contributes to understanding the tool's function. It is appropriately sized for the tool's simplicity.

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?

For a simple two-parameter tool with no output schema or annotations, the description covers the essential behavior (filter rows by column values, preserve order) and hints at the intended use case. However, it lacks details on edge cases (empty results, invalid column) and does not explicitly distinguish from sibling tools, leaving some ambiguity about when to use it. 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 coverage is 0%, so the description is the only source of parameter meaning. It explains that 'column' is the field to filter on and 'values' are the list of accepted values, and that output order follows the values order. This adds meaning beyond the schema, but it doesn't clarify constraints like min/max items or exact-match semantics. Adequate but not exhaustive.

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 action: returning rows of the Subbielane dataset where a column matches any of given values, preserving order. It clearly indicates the resource and behavior, and the phrase 'for "X vs Y" questions' hints at its comparison use case. It doesn't explicitly differentiate from siblings like dataset_search, but the core purpose is unambiguous.

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 gives a clear context (comparison questions) but does not explicitly state when to prefer this over alternatives or provide exclusions. It implies usage for side-by-side comparisons but doesn't name sibling tools or conditions when they should be used instead. This is adequate but not explicit.

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