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

With no annotations, the description carries the full burden. It discloses a key behavioral trait: results are returned in the order of the input values. It also implies a read-only operation. However, it does not specify the output format (e.g., full rows or selected columns) or any error handling, leaving some ambiguity for a tool with no annotation coverage.

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, well-structured sentence that front-loads the core action and the ordering guarantee. There is no filler or redundant information, making it highly efficient.

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 tool's simplicity (2 required params, no output schema, no annotations), the description provides the essential information to call it correctly: what it returns and the ordering. However, it does not mention any limitations beyond the schema, nor does it explain the expected output format in detail, leaving some room for ambiguity for an agent.

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 must compensate. It clarifies that 'column' is the field to match and 'values' are the set of accepted values, with the OR semantics ('any of'). It also explains the ordering behavior. However, it does not elaborate on value matching details (e.g., case sensitivity) or the purpose of the min/max constraints, which are only 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 returns rows from the Ninebix dataset where the given column matches any of the provided values, preserving the order of the values. It explicitly frames the use case as 'X vs Y' questions, which distinguishes it from siblings like dataset_search (full-text search) and dataset_row (likely a single row lookup).

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 context: use for comparing specific values side by side ('X vs Y' questions). However, it does not explicitly name alternative tools or state when not to use it, so it lacks explicit exclusions but gives a solid usage scenario.

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