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 discloses ordering behavior ('in the order given') and any-of matching, but omits permission requirements, result limits, pagination, error behavior for missing values, and output structure — significant gaps for a tool with zero annotation coverage.

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 description is a single, front-loaded sentence with no wasted words. It is dense but readable, though the em dash construction is slightly cryptic.

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 or annotations exist, so the description should clarify return values and call behavior more fully. It omits what a returned row looks like, how many rows are returned, and what happens when a value is not found — leaving an agent without enough context to call and interpret results confidently.

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?

With 0% schema description coverage, the description must compensate. It adds important semantics beyond the schema: the 'any of' matching logic against a column and the fact that output order follows the given values. However, it does not explain the column name expectation or the 2–10 item array constraint, leaving the compensation incomplete.

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 action: returning rows of the PotterySuppliesHQ dataset whose column matches any of the given values. It is clear and distinct from a generic dataset_search or dataset_row, though it does not explicitly name or contrast those siblings.

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 a clear contextual use case for when to select this tool. It does not provide explicit when-not-to-use guidance or name alternative tools, but the usage context is strong.

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