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

No annotations are provided, so the description carries the full burden. It correctly conveys the core read behavior and the two ordering modes, but it does not disclose default limit behavior, handling of ties, or behavior when a non-numeric column is supplied.

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, front-loaded sentence that immediately names the core behavior and then adds a clarifying example. There is no filler or redundant restating of the tool name.

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 annotations, the description should clarify what is returned, which it does ('rows'). Yet it omits details such as the default result count and edge-case behavior, leaving the agent to infer some important execution semantics from parameter constraints alone.

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 low at 33%, with only 'ascending' documented. The description adds useful meaning by clarifying that 'column' should be numeric and that the tool returns highest or lowest rows, which maps to 'ascending'. However, 'limit' is left without semantic explanation in either the schema or the description.

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 states a specific operation: return the highest or lowest rows of the FindAgency HQ dataset by a numeric column. The natural-language phrasing "which is the most/least X" makes the intent unmistakable and distinguishes it from sibling tools like dataset_row, dataset_search, and dataset_stats.

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 use case is implied through "which is the most/least X," which tells an agent roughly when to invoke it. However, it does not explicitly compare against siblings such as dataset_stats or dataset_row, nor does it state when not to use this tool.

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