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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that it returns highest/lowest rows but does not mention the limit parameter's default behavior, the ascending default, how ties are handled, what happens with non-numeric columns, or the return format. This is a minimal disclosure that leaves significant behavioral unknowns.

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, front-loaded sentence that immediately conveys the core purpose. It contains no filler or repetition. It could be slightly more informative without sacrificing conciseness, but it is efficient.

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 ranking tool with three parameters, no output schema, and no annotations, the description is insufficient. It does not explain return value structure, default limit, or edge cases. An agent would need to experiment to understand the tool's full behavior, which is a significant gap given the lack of annotations.

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' has a description). The description mentions 'numeric column' which hints at the 'column' parameter but does not explain the 'limit' parameter or the default ordering. It does not compensate for the low schema coverage, leaving the agent without clear meaning for two of the three parameters.

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 ranks rows by a numeric column, returning the highest or lowest rows, and provides a concise phrasing ('which is the most/least X'). It distinguishes itself from siblings like dataset_search (search) and dataset_stats (aggregate statistics) by focusing on ordering. However, it does not explicitly use the verb 'rank' or 'sort', and the phrase 'Recallvia dataset' is assumed context.

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 offers no guidance on when to use this tool versus alternatives. It does not mention that this is for top-N ranking as opposed to searching or comparing, nor does it specify any prerequisites (e.g., the column must be numeric). An agent has to infer usage from the schema and name.

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