ms-fabric-mcp-server

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

No annotations are provided, so the description carries the full burden. It describes the tool's behavior as retrieving status and mentions the return structure, but lacks details on error handling, rate limits, authentication needs, or side effects. For a tool with no annotations, this leaves gaps in behavioral understanding.

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 and front-loaded with the core purpose, followed by parameter and return explanations, and an example. Every sentence adds value without redundancy, making it efficient and easy to parse.

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 tool has an output schema (so return values are documented elsewhere) and low complexity, the description covers purpose, usage, parameters, and returns adequately. However, with no annotations, it could benefit from more behavioral details like error cases or performance hints to be fully complete.

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 that 'location_url' is 'The location URL returned from job creation' and ties it to run_on_demand_job. This adds meaningful context beyond the bare schema, though it doesn't detail format or validation rules. With 1 parameter, this is sufficient for a high score.

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 specific action ('Get job status') and resource ('using the location URL from run_on_demand_job'), distinguishing it from sibling tools like get_job_status. It explicitly explains this tool is for when you have the location URL but not other identifiers, making the purpose distinct and well-defined.

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 guidance on when to use this tool ('when you have the location URL but not the individual workspace/item/job identifiers') and references the alternative ('same structure as get_job_status'), clearly differentiating it from the sibling tool get_job_status. The example further illustrates the usage context.

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