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

With no annotations, the description must carry behavioral disclosure. It clearly conveys row filtering and value-order preservation, but it does not describe the return presentation, whether the operation is read-only, or any output limits. The title's 'side by side' comparison behavior is implied, not fully specified.

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?

One dense sentence packs all essential information: the target dataset, filtering mechanism, ordering behavior, and intended use case. No wasted words, and the core behavior is front-loaded.

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 (two parameters, no nested objects, no output schema), and the description covers the core invocation details. The main gap is clarifying what 'compare rows side by side' means in the output, which the title implies but the description does not detail.

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 0%, so the description must compensate. It effectively explains that 'column' is the filter field and 'values' are the matching values, adding the crucial detail that row order follows the given value order. This provides meaning beyond the raw schema.

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 rows whose column matches any given values, in a specified order. This distinguishes it from siblings like dataset_search (keyword search) and dataset_row (likely a single row fetch).

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 'for "X vs Y" questions' gives a clear, useful context for when this tool is appropriate. However, it does not explicitly name alternatives or conditions when not to use it.

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