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

No annotations are provided, so the description carries the full burden. It implies a read-only ranking operation but discloses nothing about return format, row cap behavior, ordering ties, or dataset assumptions beyond the numeric-column hint, leaving meaningful behavioral gaps.

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 compact sentence with the ranking intent front-loaded and no filler. It is efficient, though the parenthetical aside adds modest redundancy.

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 read tool with no annotations and no output schema, the description establishes the core operation but does not describe the shape of the returned rows or the limit semantics. It is minimally adequate rather than complete.

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% (only 'ascending' is documented), but the description adds the non-obvious constraint that the column must be numeric and that results are highest-first by default. It says nothing about the limit parameter or its 50-row ceiling, which the schema documents structurally.

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?

States a specific verb+resource: returning the highest/lowest rows of the Wedding Cost Checker dataset ranked by a numeric column. This clearly separates it from dataset_row, dataset_stats, and dataset_search, though it leaves the phrase 'top' to be inferred from the title rather than restating it in the body.

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 framing 'which is the most/least X' implies the analytical question the tool answers, giving implied usage context. However, it never states when to prefer this over dataset_stats or dataset_search, nor any exclusion or prerequisite, so guidance remains implicit.

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