get_datasets

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

No annotations are provided, so the description carries full burden. It explains the retrieval behavior and parameters but does not explicitly state that the tool is read-only or non-destructive, which is important for an agent to understand side effects.

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 with a clear opening, bullet points, and sections for parameters, returns, examples, and errors. It is slightly verbose with background on Power BI datasets but overall efficiently organized.

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 three optional parameters and an output schema (not shown but present), the description covers usage, return structure (list with IDs, names, optional metadata), and error handling. It provides sufficient context for an agent to understand and invoke the tool correctly.

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 0%, but the description compensates by explaining each parameter's purpose, defaults, and valid values (e.g., format: 'json' or 'markdown'). It clarifies the use of workspace_id for My workspace omission, adding value beyond the 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 states 'Get list of datasets from a specific workspace or My workspace,' clearly identifying the resource and scope. It includes usage bullet points that hint at differentiation from siblings like get_dataset (single) and query_dataset (querying), but does not explicitly name alternatives.

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 use cases (e.g., 'Find a dataset ID for querying') and error handling tips. However, it does not state when not to use this tool or directly compare with sibling tools, leaving some ambiguity.

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