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

No annotations are provided, so the description carries the behavioral disclosure burden. It does reveal the key selection and ordering behavior, but it leaves the actual output format, exact-match semantics, duplicate handling, and empty-result behavior implicit.

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 entire description is one dense sentence that front-loads the operation and ordering, then ends with the use case. There is no filler, no repetition of schema information, and every part contributes to understanding.

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 small two-parameter tool the core invocation logic is covered, but with no output schema and no annotations, the description omits the actual side-by-side return format and edge-case behavior. An agent can invoke it, but may not know exactly what response shape to expect.

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%, and the description compensates by mapping both parameters: 'column' is the field whose values are matched, and 'values' are the row-selector values that also determine output order. It does not provide exhaustive detail, but it adds real meaning beyond the bare JSON Schema.

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 operation: return rows of 'the Turndownly dataset' using a filter column and a set of values, preserving the given value order. This clearly distinguishes it from siblings like dataset_row, dataset_search, or dataset_top by its value-based, order-preserving comparison behavior.

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 an explicit, recognizable use case for when to invoke this tool. It does not enumerate alternatives or state when not to use it, so it stops short of the full 5.

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