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

With no annotations, the description must carry the behavioral disclosure burden. It reveals case-insensitive equality, which is useful, but it does not state whether one or all matching rows are returned, what happens on no match, or how the values are normalized. The singular title ('a row') versus plural description ('the rows') creates ambiguity about the return shape.

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 with no wasted words, and the exact-match condition is prominently stated. It is concise and readable, though it lacks an explicit verb and leaves some behavioral details unstated.

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 absence of annotations and an output schema, the description needs to explain what the caller should expect after invocation. It does not clarify whether the result is a single record or a list, how matches are ordered, or how errors/missed keys are handled, so an agent is left with meaningful uncertainty even for a simple lookup.

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 compensate. It does identify `column` as the field to match and `value` as the value to compare, and it communicates the case-insensitive exact-match rule. However, it does not explain column name formatting or provide any additional detail beyond what the two parameter names already suggest.

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 returns rows from the Runwayze dataset where a column equals a value exactly, and it adds the case-insensitive qualifier. The verb is implied rather than explicit ('Look a row up' in the title), but the resource and matching behavior are specific enough to distinguish from a general search.

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 does not say when to use this tool versus siblings like dataset_search, dataset_top, or dataset_compare. It implies exact-match usage but gives no exclusions or alternative routing, leaving the agent to infer when dataset_row is the right choice.

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