get_dataset

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

With no annotations provided, the description carries the burden of disclosing behavior. 'Fetch' clearly implies a read-only operation with no side effects, which is useful. However, the description does not disclose limit/pagination behavior, response shape, or edge cases. These are not heavily problematic for a simple fetch tool, but they remain undisclosed.

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 a single sentence, front-loaded with the action 'Fetch' and the resource 'dataset examples', followed by a short purpose clause. There is no filler, redundancy, or repetition of schema details.

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 simple two-parameter tool with no output schema, the description plus the input schema give an agent enough to understand the operation and purpose. It does not describe the exact shape of the returned examples, but the term 'examples' and the limit parameter make the return type reasonably inferable.

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% and the schema already documents dataset_id and limit, including the default for limit. The description adds no parameter-level semantics beyond the stated purpose. With full schema coverage, baseline 3 is appropriate.

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 clear action and resource: 'Fetch dataset examples'. The purpose clause 'for review or eval comparison' adds context and helps distinguish it from list_datasets, which presumably lists dataset metadata rather than examples. It does not explicitly differentiate itself from siblings like get_evaluation_summary, so it is clear but not fully differentiated.

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 review or eval comparison' implies when an agent might want this tool, but it does not explicitly state when to use it over siblings such as list_datasets or get_evaluation_summary. The usage guidance is inferred from the purpose rather than stated as a decision rule.

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