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

With no annotations, the description carries the full burden. It does disclose one real behavioral trait — results come back 'in the order given' — which is not derivable from the schema. It is silent on read-only safety, what happens to values that match no rows (omitted vs. error), and whether full rows or just matched columns are returned.

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 compact sentence with no filler, and the dataset scope plus filtering rule come first. The em-dash clause placement and fragment form make it slightly less crisp than a clean verb-first statement, but nothing is padded.

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?

No output schema, no annotations, and 0% schema coverage leave the description doing all the work, yet it does not state the return shape, ordering guarantee for unmatched values, or error behavior. For a 2-parameter retrieval tool with an identical-looking sibling set, this is under-specified.

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 the any-of (OR) semantics of 'values' and the order-sensitivity of the result, which adds meaning beyond the bare types. It still omits the 2-item minimum, the 10-item cap, and that all values must belong to a single named column.

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 conveys a filter-and-retrieve operation ('rows ... whose column is any of the given values') and adds an ordering nuance, but it is a noun-phrase fragment with no verb and never states the actual comparison behavior the title advertises. An agent can infer it selects rows by column match, but the wording is implied rather than stated.

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?

'for "X vs Y" questions' is a genuine usage trigger that hints at the right scenario, which is more than most siblings offer. However, it names no alternatives (dataset_search or dataset_row are obvious overlapping options) and gives no when-not-to-use condition, so routing is left partly to inference.

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