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

With no annotations, the description carries the full burden of behavioral disclosure. It reveals the ordering behavior ('in the order given') and the OR logic ('any of the given values'), but it does not disclose whether the operation is read-only, how results are returned, error handling, pagination, or performance implications. For a simple read-like tool, this is a notable gap, especially without annotations to cover safety.

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, tightly worded sentence. It leads with the core behavior, then the ordering constraint, then the intended use case. There is no extraneous text, and it is structured so the most important information appears first. Ideal conciseness for this tool.

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?

Given only two simple parameters and no output schema, the description covers the essential purpose and key behavior. However, it omits practical details like whether the operation is read-only, what happens if a value is not found, and whether results are limited. Since there are no annotations to fill these gaps, the description is not fully complete for an agent to use the tool without additional assumptions.

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 clarifies that 'column' is a field in the dataset and 'values' are the target values to filter on, and it adds the ordering semantics tied to the values order. However, it does not specify the expected format for 'column' (e.g., exact name match) or whether values are case-sensitive. The description adds some meaning beyond the bare schema but leaves room for 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 clearly states the operation: it retrieves rows from the PunchListWorks dataset where a specified column matches any of the given values, preserving the order of the values. It also provides the use case ('X vs Y' questions), which helps distinguish it from sibling tools like dataset_row (single row) or dataset_search (broader search). The verb 'compare' is implied but the actual behavior is explicit.

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 mentions the tool is for 'X vs Y' questions, which gives some context on when to use it, but it does not explicitly state when to prefer alternative tools or when not to use it. There is no mention of exclusions or comparisons to siblings, leaving the agent to infer usage from the phrase. This is adequate but not explicit.

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