get-dataset-examples

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

The description implies a read-only operation ('Get examples') and specifies the expected return (object with dataset ID, version ID, array of examples). Without annotations, it does not disclose additional behavioral traits like rate limits, authentication needs, or whether the operation is destructive (likely not). Adequate but minimal.

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?

Description is concise (few sentences) with a clear structure: purpose, definition of examples, example usage, expected return. No unnecessary words, but the example usage could be more specific about parameter usage.

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 4 parameters, no output schema, and no annotations, the description is incomplete. It does not explain how parameters like 'splits' or 'dataset_name' affect the result, leaving ambiguity. The expected return format lacks detail about the exact structure of examples. More context is needed for effective agent invocation.

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% (no parameter descriptions in the schema). The description does not explain the four parameters (splits, dataset_id, version_id, dataset_name) or how they filter/fetch examples. It only mentions dataset_id and version_id in the expected return, not their usage. Lacks compensation for missing schema descriptions.

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

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?

Provides an example usage ('Show me all examples from dataset...') but does not explicitly state when to use this tool versus alternatives like get-dataset or add-dataset-examples. No when-not or explicit guidance on prerequisites.

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