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

No annotations and no output schema, so the description carries the full burden and does not meet it. It never states what is returned (whole rows? just the ranked column?), whether ties are broken, what happens beyond the row count, or whether the 50-row cap truncates silently.

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 that states the resource and the ordering semantics immediately, with no filler. The trailing quoted example is slightly awkward but does add framing value.

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 ranking tool with no annotations, no output schema, and one undocumented parameter, more is needed. The description should say what a result looks like and note the limit ceiling, since nothing else in the definition conveys it.

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 there. The description partially compensates by stating the ranking column must be numeric, a constraint the schema (plain string, minLength 1) does not enforce, but it says nothing about the limit parameter or valid column values.

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 a specific operation (return the highest/lowest rows of the Working Capital Quotes dataset ranked by a numeric column), which is concrete enough to distinguish it from dataset_stats or dataset_row. It stops short of naming a sibling alternative explicitly, so an agent must infer the boundary from the tool name alone.

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" frames the natural-language question this tool answers, which implies usage. However, it gives no explicit when-not guidance, no mention of when dataset_stats or dataset_search would be the better pick, and no preconditions.

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