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

With no annotations, the description is the only behavioral disclosure. It usefully reveals OR-style matching and order preservation, but it does not specify exact-match semantics, case sensitivity, duplicate or no-match handling, or the output side-by-side representation. Useful but incomplete.

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 efficient sentence that front-loads the selection rule and adds the intended use case. No filler or repetition of the schema.

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 two-parameter read-style tool, the description is mostly complete: it names the selection rule, the ordering, and the intended comparison use case. The lack of an output schema or annotations makes the omitted match/empty-result details more noticeable, but they are not fatal for this complexity.

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 carries the semantics burden. It explains that column is the field to match and values are the set of values to compare, and it ties them to the output ordering. This is meaningful semantic content beyond the bare 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 title 'Compare rows side by side' plus the description states the operation and the exact row-selection rule: rows whose column value is any of the supplied values, in the supplied order. This clearly distinguishes it from single-row siblings like dataset_row and from search-oriented tools.

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 explicitly targets 'X vs Y' questions, which tells an agent when this tool is appropriate. It does not name alternatives or give exclusion criteria, so it stops short of a 5.

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