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

With no annotations, the description must carry the behavioral disclosure burden. It does describe the core behavior—sorting rows by a numeric column and returning top or bottom rows—but it omits details like limit defaults, tie-breaking, handling of non-numeric values, or read-only guarantees.

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, compact sentence that front-loads the ranking purpose. Minor redundancy exists with the title ('numeric column' repeats), but the added 'most/least X' phrasing earns its place by clarifying the intended query.

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 conveys the essential operation and return type (rows). However, with no output schema and no annotations, important details such as the default limit value, behavior on non-numeric columns, and explicit read-only status are missing, leaving the agent to infer them.

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%, so the description needs to compensate. It adds important meaning by specifying that the column must be numeric and indicating the ascending/descending intent, but it does not explain the 'limit' parameter beyond what the schema's min/max bounds imply.

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 returns the highest or lowest rows by a numeric column, which is a specific ranking operation. It conveys the 'most/least X' use case and can be distinguished from sibling tools like dataset_search or dataset_stats, though it does not explicitly name 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' gives a clear implied use case for the tool. However, it does not explicitly say when to prefer this tool over siblings such as dataset_stats or dataset_row, and it offers no exclusions or alternative guidance.

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