get_dataset

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves dataset details, but doesn't disclose traits like whether it's read-only, requires specific permissions, has rate limits, or what happens on errors. For a retrieval tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 well-structured and appropriately sized, with a clear purpose statement followed by separate 'Args' and 'Returns' sections. Every sentence adds value, and it's front-loaded with the main functionality. It could be slightly more concise by integrating the sections more fluidly, but it's efficient overall.

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 tool's moderate complexity (3 parameters, no annotations, but with an output schema), the description is reasonably complete. It explains the purpose, parameters, and return values. Since an output schema exists, it doesn't need to detail return values extensively, but it could improve by adding more behavioral context or usage guidelines.

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 description includes an 'Args' section that lists and briefly describes the three parameters (environment, connection, dataset), adding meaning beyond the input schema, which has 0% description coverage. However, it doesn't provide examples (e.g., for 'connection'), constraints, or format details, so it only partially compensates for the schema gap.

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's purpose: 'Get a single dataset by connection/name.' It specifies the verb ('Get') and resource ('dataset'), and distinguishes it from siblings like 'list_datasets' by focusing on a single dataset retrieval. However, it doesn't explicitly contrast with other get_* tools (e.g., 'get_topic'), so it's not a perfect 5.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'list_datasets' for browsing or 'get_dataset_message_metrics' for metrics, nor does it specify prerequisites or exclusions. The usage is implied by the purpose but lacks explicit context.

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