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

The description discloses the core ranking behavior and the ascending/descending intent through 'highest (or lowest)' and 'most/least X'. However, with no annotations, it does not mention return shape, default limit behavior, tie handling, or whether the operation is read-only.

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 compact and front-loaded, with the key operation stated immediately. The quoted phrase adds a little color but no real bloat; using a clearer verb like 'Returns' would improve it slightly.

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?

With no output schema and no mention of result shape, defaults, or how this tool relates to its siblings, the description leaves an agent to infer important invocation details. It is minimally adequate only for very simple calls.

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 only 33%, so the description must compensate for the undocumented column and limit parameters. It adds the 'numeric' qualifier for column and the high/low semantics, but it does not clarify limit defaults or the relationship between ascending and ordering beyond what the schema already states.

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 text clearly conveys a specific operation: selecting the highest or lowest rows of a dataset by a numeric column. It aligns with the title and the intended 'most/least X' behavior, though it does not explicitly differentiate itself from sibling tools.

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?

There is no guidance about when to use dataset_top versus dataset_row, dataset_search, or dataset_stats, and no exclusions or alternative recommendations are given. The only implied context is that the user wants top/bottom rows by a numeric value.

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