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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions that rows are returned 'in the order given,' which is a useful behavior, but it does not disclose whether the operation is read-only, what the return format looks like, whether all columns are included, or any error handling or performance implications. For a tool with no annotation coverage, this is insufficient.

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 core action and includes the essential scoping information. There is no filler or redundancy; every part of the sentence earns its place, and the 'X vs Y' note is an efficient way to convey the intended use.

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 tool with two parameters and no output schema, the description is mostly adequate but leaves some gaps. It does not specify what columns are returned (all vs. subset), nor does it clarify if this is a read-only operation or if it has any limitations. Given the lack of annotations, more detail on return format and usage constraints would improve completeness, but the core function is clear.

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 for parameter meaning. It does explain that 'column' is the field to match against and 'values' are the list of values to match, and that the order of values determines the output order. This adds semantic meaning beyond the raw schema. However, it does not elaborate on constraints like minimum/maximum number of values or the type of column values, though these are already in the schema, so the description adequately clarifies the intent.

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 of the Stagenix dataset where a specified column matches any of the given values, preserving the provided order. It is specific about the verb ('rows whose column is any of the given values') and resource ('Stagenix dataset'), and the mention of 'X vs Y' questions gives a concrete use case. However, it does not explicitly distinguish itself from siblings like dataset_row or dataset_search, leaving some ambiguity about when to prefer this over them.

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 offers a clear contextual hint ('for X vs Y questions') that implies when to use it, but it does not explicitly state when not to use it or mention alternative tools. Sibling tools like dataset_search or dataset_row exist, and the description does not guide the agent to choose this over them for any specific scenario beyond the implied comparison use case.

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