create_dataset

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

Annotations are absent, so the description must disclose all behavioral traits. It mentions the S3 import mechanism but fails to detail failure modes, error handling, idempotency, or permission requirements (e.g., AWS credentials, region). The impact of existing datasets with the same name is not addressed.

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?

Two sentences, no wasted words. Action is front-loaded ('Create a new dataset'), and the purpose is clearly stated. Ideal conciseness.

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?

With 8 parameters, no output schema, and no annotations, the description provides acceptable context (S3 import, usage for fine-tuning/evaluation) but lacks critical details like error handling, duplicate handling, and output expectations for a creation 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?

Schema description coverage is 100%, so baseline is 3. The description adds no additional meaning beyond the schema; it merely restates the S3 import aspect. No further enrichment of parameter semantics.

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 action ('Create a new dataset'), the source ('importing from S3'), and the purpose ('fine-tuning or model evaluation'). It effectively distinguishes from sibling tools like 'delete_dataset' or 'list_datasets'.

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?

No guidance on when to use this tool versus alternatives. The description does not mention prerequisites, when not to use it, or suggest other tools like 'validate_s3' for pre-checking S3 access.

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