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

With no annotations, the description carries the full behavioral burden, and it does disclose one genuinely non-obvious trait: results are returned 'in the order given', which matters for side-by-side comparison. It says nothing about what happens when a value matches no row, the 10-value ceiling, or that this is a read-only operation, leaving meaningful gaps.

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 tightly-written sentence with the resource and filter stated up front and the use case appended after an em-dash. No waste, though the relative clause makes it slightly dense on first read.

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 tool with no annotations and no output schema, the definition covers the core contract (rows returned, ordering, use case) but leaves out the value-count limits and unmatched-value behavior. Adequate to invoke, not fully self-contained.

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 supply the semantics, and it does: 'column' is the field to match against and 'values' are the values to match, with input order determining output order. This compensates well for the missing schema docs, though it omits the schema's 2–10 item bounds.

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 concretely what is returned: the rows of the Calibvo dataset whose column matches any of the given values, preserving input order. That is a specific resource plus filtering behavior, and the 'for X vs Y questions' clause hints at the comparative niche. It does not, however, name any sibling to distinguish itself from dataset_search or dataset_top, so it stops short of a 5.

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?

It gives one positive usage cue ('for "X vs Y" questions'), which tells the agent when this tool is appropriate. It offers no when-not guidance and never names an alternative such as dataset_search for single-value lookups or dataset_row for one row, so the routing burden stays largely with the reader.

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