create_dataset

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states this creates a new dataset but doesn't mention important behavioral aspects: whether this requires specific permissions, what happens if the dataset already exists, whether there are size/name constraints, or what the response contains. For a creation tool with zero annotation coverage, this leaves significant behavioral gaps.

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 efficiently structured with a clear purpose statement followed by parameter documentation. Each sentence earns its place by providing essential information. The formatting with 'Args:' and bullet-like parameter explanations makes it scannable, though the lack of complete sentences for parameters slightly affects readability.

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 this is a creation tool with no annotations and no output schema, the description does an adequate job covering the basic purpose and parameters. However, it lacks important context about behavioral aspects (permissions, error conditions, response format) and usage guidelines relative to sibling tools. The parameter documentation is strong, but other contextual elements are incomplete.

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 provides parameter documentation for all 4 parameters, adding meaningful context beyond the schema's 0% description coverage. It explains what each parameter represents ('Pool name where dataset will be created', 'Dataset name', 'Compression algorithm', 'Optional quota in bytes') and notes the default for compression. This fully compensates for the schema's lack of 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 the verb ('Create') and resource ('dataset'), making the purpose immediately understandable. However, it doesn't differentiate this from sibling tools like 'create_snapshot' or 'create_snapshot_policy' which also create resources, missing the opportunity to clarify this creates a storage dataset rather than a snapshot or policy.

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 prerequisites (like needing an existing pool), when not to use it (e.g., for modifying existing datasets), or refer to sibling tools like 'modify_dataset_properties' for updates. The only implied context is dataset creation, but no explicit usage boundaries are provided.

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