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

With no annotations, the description carries the full burden. It mentions 'highest (or lowest)' and references a numeric column, but does not disclose default sort order, handling of ties, or the effect of the 'limit' and 'ascending' parameters. The behavior is partially described but not fully transparent.

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 sentence with an em dash and example, making it concise and easy to read. It is well-structured for a simple operation, though the example phrase is somewhat colloquial.

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 provides a basic idea but omits details like return format, pagination, or edge cases (e.g., non-numeric data). The absence of an output schema and minimal behavioral disclosure leaves the description incomplete for robust use.

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?

The description clarifies that 'column' should be numeric, but it does not explain the 'limit' parameter or the exact meaning of 'ascending' beyond the schema's own brief note. With schema coverage at only 33%, the description adds some context for 'column' but leaves limit and ascending under-explained.

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 of the dataset by a numeric column, and provides a concrete example query ('which is the most/least X'). It is distinct from sibling tools like dataset_search or dataset_stats, which serve other purposes.

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 implies usage for ranking queries with the example 'which is the most/least X', which helps an agent know when to use it. However, it does not explicitly contrast with siblings like dataset_stats or dataset_search, leaving some room for ambiguity.

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