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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states only that a new dataset is created and what datasets conceptually are. It does not disclose whether creation is idempotent, what happens on duplicate names, how the created dataset is identified in responses, or whether any side effects occur beyond the creation.

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 short and front-loaded with the core action. The second sentence explains the dataset concept and the intended integration path, earning its place. It could be slightly tighter but is well within reasonable length.

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 creation tool with an output schema, the description adequately covers the basic purpose and downstream usage. However, with no annotations and no mention of how the created dataset is referenced afterward, an agent may miss important operational context such as retrieving the dataset ID or choosing between direct creation and CSV-based creation.

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 the parameters are already well documented in the schema. The description's mention of connected_dataset_ids in submit_query adds downstream context but does not add new meaning about create_dataset's own parameters, so the baseline of 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 opens with 'Create a new dataset', which clearly names the verb and resource. It also defines what a dataset is (a collection of entities), but it does not explicitly distinguish itself from the sibling create_dataset_from_csv, which also creates datasets but through a different input path.

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 gives contextual usage for datasets ('Connect a dataset to a job via submit_query...') but provides no guidance on when to prefer this tool over create_dataset_from_csv, append_csv_to_dataset, or add_dataset_entities. There are no exclusions or alternatives mentioned, so an agent gets little decision support.

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