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

No annotations are provided, so the description carries the full burden. It reveals the ordering behavior but omits side effects (none expected, but not stated), return format, pagination, error handling, or what happens when no rows match. For a read-only operation, this is thin disclosure.

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 sentence with a clarifying dash clause. It is front-loaded with the core behavior and ends with a usage context. No fluff, but the dash fragment is slightly informal.

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 simple filter tool, the description covers the essential semantics, but given no output schema and no annotations, it should state that this is a read operation, describe the result shape (e.g., rows preserving original order), and possibly mention limitations (e.g., only matches exact values). The description is adequate but leaves gaps an agent would need to infer.

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 coverage is 0%, so the description must compensate. It does explain that 'column' is the field to filter on and 'values' are the list of acceptable values, which maps to the schema properties. However, it doesn't clarify parameter constraints (e.g., minItems=2, maxItems=10) beyond what schema already specifies, and it doesn't mention the 'column' must exist in the dataset.

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 the operation (retrieve rows), the target (PTOroom dataset), the filter condition (column equals any of given values), and ordering. It distinguishes itself from sibling tools like dataset_search by explicitly describing the 'X vs Y' use case, though it doesn't name alternatives.

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 gives a usage hint ('for "X vs Y" questions') which implies when to use it, but doesn't explicitly contrast with alternatives like dataset_search or dataset_row. No exclusions or prerequisites are mentioned, leaving some ambiguity about when this is preferred over similar tools.

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