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

With no annotations provided, the description carries the full behavioral burden. It discloses the key behaviors: filtering by column values and preserving the order of the provided values. It does not disclose matching semantics (exact vs. partial, case sensitivity), what happens with duplicate matches, or the output format, leaving some behavior implicit.

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 efficiently conveys the filtering logic, ordering behavior, dataset scope, and intended use case. There is no redundant phrasing or filler, and every component adds relevant information.

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?

Given the simple two-parameter schema and lack of an output schema, the description covers the essential call semantics: which rows are returned and in what order. It does not describe the response shape or exact-match behavior, but those are less critical here than they would be for a tool with mutation side effects or a richer output schema.

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 explain the parameters, and it does: 'column' is the field to match on, and 'values' are the candidate values whose order determines the output ordering. It could add more detail about value formatting or matching rules, but the core semantic connection between the two parameters is clearly conveyed.

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 that the tool retrieves rows from the Partnro dataset where the specified column matches any of the given values, in the order provided. It has no explicit verb like 'return' or 'select,' and it does not explicitly distinguish itself from sibling tools such as dataset_row or dataset_search, though the 'X vs Y' framing signals its comparison purpose.

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' implies this tool is for comparing two or more values side by side, which is useful usage guidance. However, it does not explicitly state when to choose this over alternatives like dataset_row or dataset_search, and it provides no exclusions or alternative routing.

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