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

With no annotations, the description carries the burden of behavioral disclosure. It reveals useful behaviors: matching 'any of the given values' (OR semantics) and preserving the supplied order. However, it does not explain what 'side by side' comparison means in the output, nor any result formatting or edge-case behavior.

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 use case. Every phrase contributes meaning, and there is no redundant or filler content.

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, the description covers the main invocation details. However, with no output schema and no annotations, it leaves unspecified what the returned rows look like or how the side-by-side comparison is presented, which an agent might need to know for post-processing.

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 to match on and 'values' are the matching targets, with order semantics tied to the values array. This adds meaning beyond the bare schema, though it could be more explicit about each parameter individually.

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 identifies the resource (Medcontra dataset rows) and the operation (select rows whose column matches any given values, preserving the given order). It implicitly distinguishes itself from sibling tools like dataset_row by focusing on multiple-value lookups for comparison, though it doesn't explicitly name alternatives.

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 clear use case: 'for X vs Y questions,' which tells an agent when this tool is appropriate. It does not explicitly list exclusions or alternatives, but the context is sufficient to infer its purpose relative to sibling tools.

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