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

With no annotations, the description carries the full disclosure burden, and it leaves key behaviors unstated: that this is a read-only operation, what the response contains (full rows vs. values), and how a non-numeric column is handled. Only the ordering semantics (highest by default, lowest optional) are conveyed.

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 with the ranking semantics first and a concrete example question appended. No filler, though the nested quotes make it slightly awkward to parse.

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 three-parameter, annotation-free tool with no output schema, the definition should say more about the returned shape and about what happens to ties or non-numeric columns. The description is accurate but thin relative to the tool's surface.

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 coverage is 33%, with only 'ascending' documented structurally. The description compensates partially by tying 'highest (or lowest)' to the ordering flag and by constraining 'column' to a numeric one. The 'limit' parameter and its 1-50 cap are left entirely to the schema.

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 names the specific operation (return the highest/lowest rows), the resource (the Wedding Cost Checker dataset), and the ordering key (a numeric column). That is enough to distinguish it from dataset_search or dataset_stats, though no sibling is named explicitly.

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 quoted phrase "which is the most/least X" implies the intended question type, which is useful context for selecting the tool. However, there is no explicit when-to-use/when-not guidance and no routing to alternatives such as dataset_stats for aggregate rankings.

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