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

There are no annotations provided, so the description carries the full burden. The description only states the functional behavior and does not disclose any side effects, permissions, or read-only guarantees. It is not explicit about whether the tool modifies data or requires specific access, which limits transparency.

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, concise sentence that packs all essential information without redundancy. It is well-structured and does not include any extraneous details.

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 description provides sufficient context for a simple tool: it mentions the dataset name, the matching logic, and the ordering behavior. It does not specify the output format (e.g., whether all columns are returned), but this is a minor omission given the simplicity of the tool and the clarity of the stated behavior.

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?

The description effectively explains both parameters: 'column' as the field to match against and 'values' as the list of allowed values. It also clarifies that the output order follows the order of the 'values' array. This fully compensates for the lack of per-parameter descriptions in the schema.

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's function: it retrieves rows from the Rebadgo dataset where a specified column matches any of the given values, preserving the order of the values. It also provides a specific use case ('X vs Y' questions), making the purpose unambiguous and distinct from siblings.

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 partial usage hint by mentioning 'X vs Y' questions, implying it is suited for comparing specific values. However, it does not explicitly contrast with sibling tools like dataset_search or dataset_row, leaving some ambiguity about when to prefer this tool over alternatives.

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