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 discloses the core selection logic (matching values in order) but omits details like return format (full rows? specific fields?), pagination, empty-result behavior, or error conditions. It's not contradictory, but it's incomplete for a tool with no output schema.

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, compact sentence with no filler. The core behavior is front-loaded, and the use-case hint is appended efficiently. Every word contributes.

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 row-selection tool, the description gives the essential filter logic and ordering, but lacks any mention of output structure (since no output schema exists) or edge cases like missing columns or no matching values. It's adequate for a basic call but not fully complete for an agent to anticipate results.

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 explain parameters. It does convey that 'column' is the field to match and 'values' are the target values, and mentions ordering. However, it doesn't clarify constraints like minimum 2 values, max 10, or value formats. It adds meaning but not comprehensive compensation for the coverage gap.

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 it returns rows of the dataset filtered by a column matching any given values, in a specific order, and hints at its use case ('X vs Y' questions). This is specific and distinguishes it from siblings like dataset_row (single row) or dataset_search (search), though it doesn't explicitly 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?

It provides a clear context for when to use the tool ('for X vs Y questions') which implies a comparative side-by-side scenario. It doesn't explicitly state when not to use it or name sibling tools, but the context is enough to guide selection.

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