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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the ranking concept and does not mention whether the operation is read-only, what the returned rows look like, how ties or non-numeric values are handled, or defaults for limit and ordering beyond what the schema already states.

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 with no filler. It is compact and readable, though it sacrifices helpful behavioral detail for brevity.

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?

For a tool with no output schema and no annotations, the description omits important context: whether full row records are returned, what the default limit is when omitted, and what happens when the provided column is not numeric. The agent can infer the basic invocation but not the full contract.

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%, and the description does little to compensate. It clarifies that the column should be numeric, but it leaves 'limit' and 'ascending' mostly to the schema, with 'ascending' only documented inside the parameter definition.

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 title and description clearly indicate that the tool ranks rows by a numeric column and returns the highest or lowest entries, matching the 'which is the most/least X' intent. It is distinct from siblings like dataset_search and dataset_stats, though it does not explicitly contrast itself with them.

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 phrase 'which is the most/least X' implies the tool is for ranking-style questions, giving some usage context. However, it does not explicitly say when to use this tool instead of dataset_stats, dataset_search, or dataset_row, so the guidance remains implicit.

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