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

With no annotations, the description carries the full burden. It discloses the key behavior (sort rows by a numeric column and take highest or lowest) and the numeric-column constraint. However, it does not address default limit behavior, tie handling, non-numeric column errors, or return format.

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 conveys the core idea without wasted words. The trailing 'which is the most/least X' is a minor stylistic flourish rather than substantive guidance.

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 no annotations, no output schema, and low schema description coverage, the description is too thin. It omits the default limit behavior, how ties are broken, what the returned rows look like, and how it differs from sibling tools like dataset_stats or dataset_search.

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 schema documents only ascending (33% coverage). The description compensates partially by clarifying that column must be numeric and linking ascending to highest/lowest, but it adds nothing about limit, including its default or allowed values.

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 ranks rows by a numeric column and returns the highest or lowest rows, with a concrete use case ('which is the most/least X'). It does not explicitly reference sibling names, but the behavior is distinct from dataset_stats, dataset_row, and dataset_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 'which is the most/least X' phrase implies when to use this tool (top-N or bottom-N ranking questions), but there is no explicit guidance on when not to use it or which sibling alternative to choose. No exclusions or alternatives are mentioned.

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