dataset_define_dataset

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

With no annotations, the description carries the transparency burden. It discloses prerequisite constraints (license, environment, table location) which is valuable behavioral context. However, it does not describe the mutation nature (create vs update), idempotency, side effects, or response format, leaving gaps for a state-changing operation.

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 concise, using bolded notes for prerequisites and a clear lead sentence. There is minor redundancy between the first sentence and the second, but overall it is efficient and easy to scan.

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 tool with a single nested parameter and no output schema, the description covers important prerequisites (license, environment, table location) but omits expected return values, error conditions, or whether the operation is idempotent. It is adequate but has clear gaps given the lack of annotations.

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 input schema has 0% top-level coverage and only describes table_name within the nested object. The description adds the critical constraint that the table must be under public_access_user, which is not in the schema. It also reinforces the 'created by the user' requirement. However, it does not explain the request_data wrapper or provide format examples, so compensation is partial.

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: 'Define an XQL user dataset based on an existing BigQuery table created by the user.' This specifies the verb (define), the resource (XQL user dataset), and the source (existing BigQuery table), distinguishing it from sibling tools like dataset_get_created_datasets or xql_add_dataset.

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 explicit operational constraints: the BigQuery table must exist under public_access_user, required license tiers are listed, and the API is only applicable from the XSIAM Notebook environment. This gives clear context on when the tool can be used, though it does not mention alternatives or when-not-to-use scenarios.

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