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

With no annotations, the description carries the burden of behavioral disclosure. It conveys that the tool orders rows by a numeric column and can return highest or lowest, which is meaningful but does not address tie-breaking, handling of missing or non-numeric values, or the exact shape of the returned rows.

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 entire description is one tight sentence that front-loads the core behavior and then illustrates the intended question. No filler or repetition; every clause adds meaning.

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?

The tool is simple enough that the description covers the main use case, but with no output schema and no annotations, an agent still lacks details about return format, column selection behavior, and edge cases. It is minimally adequate but leaves several operational questions unanswered.

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%, so the description needs to compensate. It adds the important constraint that 'column' must be numeric and that 'ascending' controls highest vs lowest, but it says nothing about the 'limit' parameter beyond what the schema's numeric bounds provide.

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 states a clear action: returning the highest or lowest rows of the Limslane dataset by a numeric column, which distinguishes it from generic retrieval or stats tools. It lacks an explicit sibling comparison, but 'top rows by numeric column' is specific enough to identify this as a ranking tool.

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' implies the intended use case: finding extreme rows by a numeric field. However, there is no explicit guidance on when to use this tool instead of dataset_row, dataset_search, or dataset_stats, nor any exclusions.

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