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

With no annotations, the description carries the full behavioral burden. It discloses one useful trait, that output follows the order of the given values, but says nothing about return shape, whether all matching rows or a comparison view is returned, limits on values, or failure behavior.

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?

It is a single compact sentence with no padding, but the awkward nested quoting and the mismatch between the stated comparison purpose and the actual filter mechanics make it less front-loaded and clear than it could be.

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 tool with no annotations, no output schema, and 0% parameter documentation, a single sentence is thin. It does not explain what a 'comparison' result looks like or how the ordered output should be interpreted, leaving real gaps for an agent.

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 does clarify that 'column' selects the matching column and 'values' supplies an ordered list of match values, which is meaningful, but it omits the 2-10 item bounds and the minLength constraints the schema enforces.

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 names a specific dataset (Contractor Lead Quotes) and a mechanism (rows whose column matches given values), but the title's claim of 'compare rows side by side' is not supported by the text, which actually describes a value-based filter with ordered output. The vague phrasing makes it hard to tell how this differs from siblings like dataset_search or dataset_row.

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 trailing clause 'for "X vs Y" questions' gives an implied usage context, which is better than nothing. However, it never states when to choose this over dataset_search or dataset_row, nor any prerequisites or exclusions.

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