get-dataset-examples

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that examples are used for testing and that the return includes dataset ID and version ID, but it fails to describe authentication requirements, error scenarios, or whether the operation is idempotent. This is insufficient for a read operation with no annotation safety net.

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 relatively short and front-loaded with the purpose. The example usage and expected return are helpful but could be integrated more concisely. Overall, it is efficient without being too verbose.

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?

Given the absence of output schema and annotations, the description should thoroughly cover the tool's behavior. It describes the return structure generally, but fails to detail parameter usage, error behavior, or the format of individual examples. This leaves significant gaps for an agent to correctly invoke the tool.

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?

The input schema has 4 parameters with 0% schema description coverage. The description does not explain any of the parameters (dataset_id, dataset_name, version_id, splits) beyond showing dataset_id in an example. It does not clarify the difference between dataset_id and dataset_name or the purpose of splits, leaving the agent without guidance on how to specify the request.

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 verb 'Get' and the resource 'examples from a dataset'. It explains what dataset examples are (array of objects with input, output, metadata), distinguishing it from sibling tools like 'add-dataset-examples' and 'get-dataset'.

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 does not provide explicit guidance on when to use this tool versus alternatives. It only includes an example usage and expected return, without indicating when-not-to-use or contrasting with siblings like 'add-dataset-examples' or 'get-dataset'.

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