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

Goes well beyond the readOnlyHint/openWorldHint annotations: it discloses the billing model (2 credits per successful call, 1 credit = 1 CAD cent), that schema-invalid input is rejected before billing, and that the error list is truncated to the first 100 with errorCount/errorsTruncated flags. Those are exactly the operational facts an agent needs before spending credits on a large payload.

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?

Front-loads the purpose before the return shape, and every clause carries information. It is a single dense run-on sentence with semicolons and an inline field dump, which is harder to scan than bulleted lines, but no sentence is filler.

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?

There is no output schema, and the description compensates by spelling out the full return object including error and duplicate shapes plus truncation flags. Minor gaps remain: it does not say what costEstimate contains when pricePerMillionTokens is omitted, nor how duplicates are matched.

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 100%, so jsonl limits, epoch bounds, the format enum values, and pricePerMillionTokens are already fully documented in the schema. The description only restates that cost comes 'from your price' and that token estimates are produced; it adds no syntax, unit, or edge-case detail beyond the schema, so the baseline 3 applies.

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?

States a specific verb (checks/validates) and concrete resource (chat, messages, or Alpaca JSONL) and enumerates the exact checks performed: per-line errors, role order, empty turns, duplicates, token estimates, cost estimate. It is clearly distinct from sibling tools like dataset-convert or dataset-split by the enumeration of checks, but never names those siblings or states the boundary explicitly.

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?

Usage is implied by the enumerated checks and the format enum, and the pricing sentence hints at a paid-call context, but there is no explicit 'use this when X, use dataset-convert when Y' routing. An agent must infer from the name and format list that this is the pre-flight validation step before splitting or converting.

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