semantic_model_get_datasources

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

The annotations already declare readOnlyHint=true and destructiveHint=false, so the description is consistent with the safety profile. However, the description adds little beyond 'via the Power BI API' and does not disclose return shape, pagination, connection details, or failure behavior.

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 one short sentence with the core action front-loaded. 'via the Power BI API' is mild filler, but the overall structure is efficient and avoids unnecessary detail.

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 simple read-only tool with two fully documented parameters and clear safety annotations, invocation requirements are mostly covered. However, there is no output schema and the description does not clarify what the returned data source information contains or how this call relates to semantic_model_get_details.

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 provides 100% description coverage for workspaceId and semanticModelId, so the description does not need to repeat parameter meanings. It also adds no extra parameter-level nuance beyond what the schema already conveys.

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 a specific verb ('Get'), a specific resource ('data sources of a semantic model'), and the API context. This is enough to distinguish it from related siblings like semantic_model_get_details and report_get_datasources.

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?

There is no guidance on when to use this tool versus related alternatives, no mention of prerequisites, and no exclusions. The description states what it does but not when it is the right choice in a workflow.

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