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

No annotations are provided, so the description carries the full behavioral burden. It mentions filtering by column values and preserving the given order, but omits whether the tool is read-only, what the return format is, how missing values are handled, and what 'side by side' actually means.

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 no filler, but the phrasing is awkward and not front-loaded. The key action is not stated clearly at the start, making the sentence less effective despite its brevity.

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?

With no annotations, no output schema, and 0% parameter description coverage, the definition should explain the operation and result more fully. It is insufficiently complete for an agent to call the tool confidently.

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 0%, so the description must compensate. It loosely maps both required parameters by mentioning 'column' and 'given values' and notes order preservation, but it does not clarify that column is a column name or that values must contain 2 to 10 entries, and the comparison semantics remain ambiguous.

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 is a noun phrase that describes filtering rows by column values, while the title says 'Compare rows side by side' and the tool name dataset_compare implies comparison. It names the dataset but does not clearly state the core operation, leaving the agent unsure whether it returns matching rows or a side-by-side comparison.

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 gives no guidance on when to use this tool versus siblings such as dataset_search, dataset_row, or dataset_top. The phrase 'for X vs Y questions' hints at a use case but does not provide explicit selection criteria or exclusions.

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