ms-fabric-mcp-server

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

With no annotations provided, the description carries full burden for behavioral disclosure. While it mentions 'wait for completion' (implying synchronous operation), it doesn't address critical aspects: what permissions are required, whether this is a destructive operation (could overwrite data), potential rate limits, error conditions, or what happens if the refresh fails. For a mutation tool with zero annotation coverage, this is insufficient.

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 extremely concise - just 7 words in a single sentence. It's front-loaded with the core action and includes the important 'wait for completion' detail. There's zero wasted language or redundancy.

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 complexity (mutation operation with 5 parameters, 0% schema coverage, no annotations) and the existence of an output schema, the description is incomplete. While the output schema might document return values, the description fails to explain parameter usage, behavioral constraints, or operational context needed for safe and effective use of this tool.

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% (none of the 5 parameters have descriptions in the schema), and the tool description provides absolutely no information about any parameters. The agent must guess what 'workspace_name', 'semantic_model_name', 'semantic_model_id', 'refresh_type', and 'objects' mean and how to use them. This is a critical gap for a tool with multiple parameters.

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 ('Refresh') and target ('semantic model'), and specifies that it 'waits for completion' which adds important behavioral context. However, it doesn't differentiate this tool from potential alternatives or siblings like 'get_semantic_model_details' or 'get_job_status' that might provide status information without performing the refresh.

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. With many sibling tools available (like 'get_semantic_model_details', 'create_semantic_model', 'add_measures_to_semantic_model'), there's no indication of when refresh is appropriate versus other operations on semantic models, nor any prerequisites or constraints mentioned.

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