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

The description discloses one behavioral trait: the match is case-insensitive. However, it does not mention whether the operation is read-only, nor does it describe the output format or error handling behavior. Given the absence of annotations, the description carries the burden but only partially fulfills it.

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 directly communicates the core functionality without any fluff or redundant details. It is well-structured and easy to parse.

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 nature of the tool and the minimal schema, the description is largely complete for basic usage. It lacks an output schema and details on pagination or limits, but for an exact-match lookup, the information provided is sufficient to understand what the tool does.

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 implicitly defines both parameters: 'column' refers to a column name and 'value' is the exact value to match. This adds semantic meaning that the schema lacks (which only specifies string type and minLength). However, it does not elaborate on valid column names or value formatting rules.

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 purpose: to retrieve rows from the Requly dataset where a column equals a value exactly, with case-insensitivity. Although it lacks an imperative verb like 'find' or 'get', the intent is unmistakable and specific.

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 no explicit guidance on when to use this tool versus siblings such as dataset_search or dataset_compare. It does not mention alternative tools or specify conditions for selection, leaving the agent to infer usage from naming conventions.

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