create_dataset

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

No annotations are provided, so the description carries full burden. It describes that datasets are collections and can be seeded with entity IDs, but does not detail creation behavior (e.g., whether it's immutable, what happens to existing data, or return value). Adequate but could add more context.

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 three sentences: first states the action, second defines what datasets are, third explains usage with submit_query. It is concise, front-loaded, and every sentence adds value.

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 an output schema present (not shown), the description does not need to explain return values. It provides essential context about dataset role within the system. Could mention that dataset is empty unless seeded, but overall is complete.

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 coverage is 100%, so parameters are well-documented in the schema. The description adds conceptual context (datasets as entity collections, connection to queries) but does not provide additional meaning beyond the schema for individual parameters. Baseline score 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 clearly states 'Create a new dataset' and explains what datasets are (collections of entities) and their role in queries via submit_query. This distinguishes it from sibling tools like list_datasets, get_dataset, update_dataset, etc.

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 explicitly says to connect a dataset to a job via submit_query to narrow retrieval scope, providing clear context for when to use this tool. It does not explicitly state when not to use it, but the purpose is clear and alternatives are implied by sibling tool names.

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