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 explains the ranking intent but does not mention default ordering for the absent 'ascending' flag, limits on returned rows, handling of non-numeric columns, or any other runtime behavior.

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, focused sentence with no filler. The key ranking behavior is front-loaded, and the illustrative 'most/least X' phrase adds clarity without unnecessary length.

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 simple ranking tool, the description covers the core selection logic, but with no annotations and no output schema, an agent is left without explicit information about return shape, row limits, or default ordering behavior. The schema fills some gaps for 'ascending' but not all.

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%, so the description should compensate. It adds useful meaning for 'column' by specifying it must be numeric and for 'ascending' by describing lowest vs. highest ordering, but it does not clarify the 'limit' parameter or its default/cap behavior.

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 action — returning the highest or lowest rows — and identifies the exact dataset and column type. The clarifying phrase 'which is the most/least X' makes the purpose immediately understandable and distinguishes it from sibling tools like dataset_stats or 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 use case is implied by the description: rank rows by a numeric column. However, the description does not explicitly state when to prefer this over sibling tools such as dataset_search or dataset_stats, nor does it mention any exclusions or alternatives.

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