create_dataset

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

No annotations are provided, so the description must disclose behavioral traits. It mentions that the dataset is backed by an existing connection and lists required fields, but it does not specify side effects (e.g., does it overwrite?), error conditions, permissions, or data validation rules. Given the absence of annotations, the description covers basic behavior but lacks depth.

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 well-structured: first sentence states purpose, followed by context, important usage notes, and a field list. It is slightly verbose but every part adds value. Could be slightly more compact, but overall effective.

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 the complex input schema with an open-ended object, the description provides necessary context: relationship to connections, prerequisites, and field guidance. It does not explicitly mention return values, but an output schema exists. Minor gaps: no mention of required within body fields or validation.

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 only one required parameter 'body' with 'additionalProperties: true', meaning no property definitions. The description compensates by listing the expected fields: dc_id, name, type, detail, description, info, lvname, settings. This adds essential meaning beyond the minimal schema.

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 that the tool creates a new CDV dataset backed by an existing data connection, and explains what a dataset is. It distinguishes itself from sibling tools like 'create_connection' and 'create_dashboard' by focusing specifically on dataset creation.

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 instructions: do not call without first calling 'list_connections()' and 'list_datasets()', and always obtain explicit user confirmation. This clearly guides when and how to use the tool.

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