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

With no annotations, the description carries the behavioral burden. It indicates read-only lookup and exact matching, but it does not specify whether multiple rows can be returned, whether missing columns cause errors, or any other side effects. The behavior is only partially disclosed.

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 with no redundant or irrelevant content. It communicates the core operation efficiently without unnecessary detail.

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 lacks important contextual details such as whether all matching rows are returned or just one, the output format, error handling for invalid columns, and pagination behavior. Given no output schema or annotations, this sparse description leaves several usage questions unanswered.

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 parameters 'column' and 'value' are self-explanatory in the context of the description, indicating the field to match and the target value. However, the description does not clarify whether the column must exist, how value types are handled, or any constraints beyond the schema's minLength. The semantics are adequate but rely heavily on the parameter names.

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 operation: retrieving rows from the HardFM dataset where a specified column matches a value exactly, with case-insensitive matching. It distinguishes this from a general search by emphasizing exact equality, making the tool's purpose unambiguous.

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 implies when to use this tool—when an exact, case-insensitive match is required—but it does not explicitly contrast it with sibling tools like dataset_search or dataset_top. The matching semantics are clear enough to guide basic usage, though explicit alternative guidance is absent.

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