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

No annotations are supplied, so the description carries the full burden; it does disclose the core behavior (ordering by a numeric column, ascending or descending) and implicitly a read-only nature. It omits tie-breaking, what happens with a non-numeric or missing column, and the default result size, though the 50-row cap is visible in the schema.

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 sentence with the ranking behavior and column constraint front-loaded. The trailing quoted question is a little gimmicky and only marginally earns its place, but nothing is redundant or padded.

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, an agent still needs to know the default limit, tie behavior, and whether non-numeric columns error or sort lexically. The description plus schema covers the happy path but leaves these edge behaviors to guesswork.

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 coverage is only 33%, so the description must compensate. It adds real meaning for the required `column` parameter by stating it must be numeric, which the bare string schema does not convey, but `limit` is never mentioned in either the description or the schema, leaving its default unrecoverable without inference.

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 specific operation (return the highest or lowest rows) on a specific resource (the Contractor Lead Quotes dataset) keyed by a numeric column, which is clearly distinct from row lookup, search, or stats siblings. It stops short of naming any sibling tool, so the boundary is clear in concept but not explicit.

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 framing question "which is the most/least X" implies the class of user question this tool answers, which is genuine usage context. There is no guidance on when to prefer this over dataset_search or dataset_stats, and no exclusions or prerequisites beyond the 'numeric column' constraint.

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