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

With no annotations, the description must carry behavioral disclosure. It states the basic sort/rank behavior and high/low orientation, but does not mention default limit, tie handling, error behavior for non-numeric columns, or what the returned rows look like.

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 efficient sentence with a helpful illustrative phrase. It is front-loaded with the tool's core behavior and contains no filler.

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 3-parameter tool this is adequate but not complete: an agent can infer the call shape, but the optional `limit` behavior, default output size, and returned row format are left unspecified.

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 needs to add parameter meaning. It adds the useful notion that `column` must be numeric and that high/low corresponds to `ascending`, but it does not clarify the meaning or default of `limit`.

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 identifies a ranking operation ('highest (or lowest) rows ... by a numeric column') and attaches it to the BioBricks dataset. It distinguishes the tool from sibling search/stats/row tools conceptually, though it does not name any sibling explicitly.

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 quoted use case, 'which is the most/least X', implies when to use the tool for ranking questions. It does not provide explicit guidance on when not to use it or which sibling (e.g., dataset_search, dataset_stats) would be a better alternative.

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