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 does disclose one important trait — rows are returned 'in the order given' — but says nothing about read-only safety, lack of side effects, permissions, pagination, or the 2–10 value constraint, leaving key operational behavior undisclosed.

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 definition is a single sentence with the operation front-loaded and no filler. It is appropriately sized for a simple two-parameter tool, though its terseness contributes to the semantic gaps noted elsewhere.

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 output schema and no annotations, the description should explain return shape, matching semantics, and constraints such as the 2–10 value limit. Instead it gives only a compact summary, so an agent lacks enough information to call the tool confidently in edge cases.

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 fully explain the two parameters. It conceptually maps 'column' and 'values' ('whose column is any of the given values'), which adds some meaning, but it never explains that column should be a dataset column name or that values are exact-match strings capped at 10 items, leaving substantial ambiguity.

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 retrieval operation on a named dataset: rows whose column matches any given value, ordered as specified, aimed at 'X vs Y' questions. It is clear enough to distinguish comparison-by-equality from a general free-text search, though it does not explicitly name or rule out sibling tools such as dataset_search.

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 implied usage context: it is meant for side-by-side comparison of specific values. However, it offers no explicit when-not guidance and never names an alternative sibling (e.g. dataset_search for text matching or dataset_row for single-row retrieval), so the agent must infer boundaries.

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