list_datasets_in_workspace

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

No annotations are present, so the description must cover behavioral traits. It only states 'List datasets' and describes the input, but omits any output behavior (e.g., pagination, whether the list includes all datasets, or any side effects). Even though an output schema exists, the description does not reference it or any operational characteristics.

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 and front-loaded with the core purpose. It includes a structured Args and Raises section, using minimal sentences without any filler. 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?

Given the existence of an output schema (covering return structure), the description adequately explains the input and error handling. However, it could mention that it lists all datasets in the workspace or any limitations, though the output schema compensates somewhat. Still, it is mostly complete for a simple list operation.

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 schema has 0% description coverage, but the description adds meaningful information for workspace_id: 'The unique identifier of the Power BI workspace (UUID format)'. This clarifies the required format beyond the schema's plain type: string, making it easier for the agent to correctly invoke the tool.

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 'List datasets' and the context 'in the specified workspace', using a specific verb and resource. It distinguishes from siblings like get_dataset_details (single dataset) and execute_dax_query (querying), making the tool's purpose unambiguous.

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 no guidance on when to use this tool versus alternatives (e.g., get_dataset_details). It only mentions the required parameter and error, but no context for selection, such as 'use this to get a high-level overview' or contrasting with sibling tools.

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