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

No annotations are present, so the description carries the disclosure burden. It explains the core rank-ordering behavior (highest or lowest by numeric column) but does not disclose the default when limit is omitted, tie-breaking behavior, or how invalid or non-numeric columns are handled.

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?

A single front-loaded sentence conveys the behavior, scope, and a concrete query example with no filler. Every phrase earns its place.

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 signature this is mostly adequate, but the optional limit has no stated default and there is no output schema describing what the ranked rows look like. An agent could make a valid call but might not know what response or default row count to expect.

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 33%, so the description needs to compensate. It adds the key constraint that the column must be numeric and clarifies highest vs. lowest ordering, but it leaves the limit parameter to be inferred from its name and schema bounds.

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?

Title 'Rank rows by a numeric column' states a specific verb and resource, and the description elaborates on highest/lowest rows and the 'which is the most/least X' use case. It is clear enough to distinguish from sibling tools like dataset_search or dataset_stats, though it does not explicitly name a sibling.

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 description gives a clear use-case trigger: ranking rows by a numeric column to answer 'which is the most/least X.' It does not explicitly list exclusions or alternative tools, but the context for when to use this tool is readily apparent.

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