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 important behavioral traits: 100% determinism, no LLM, freeness of this endpoint, and the limitation that datasetId is not resolvable. It also lists the exact output facts and conditional cross-source price divergence, providing a detailed behavioral model.

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 front-loaded with a clear call-to-action and efficiently lists output facts. The cost comparison with the POST /api endpoint adds useful context but also extra length. Overall, it is well-organized but could be slightly tightened without losing essential information.

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?

The description covers the tool's purpose, input format, output details, determinism, and the datasetId limitation. However, it does not explicitly state whether rawJson is required (the schema lists 0 required parameters), nor does it describe error behavior or what happens when both parameters are absent. Given no output schema, these are minor gaps in an otherwise complete description.

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 the baseline is 3. The tool description largely repeats the schema's parameter details (rawJson as JSON array or object; datasetId not resolvable) without adding new syntax, validation, or usage nuances. The only addition is a slight emphasis on rawJson, but it does not go beyond what the schema already states.

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 tool checks dataset quality and returns a deterministic verdict (RELIABLE / USABLE_WITH_CLEANING / UNRELIABLE) with specific quality facts. It distinguishes itself from the alternative paid POST /api endpoint, making the purpose and scope unambiguous.

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?

Explicitly instructs to call before using any dataset, and provides clear alternatives: the paid POST /api endpoint and the recommendation to pass rawJson instead of datasetId. This gives strong contextual guidance for when and how to use the tool.

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