Get Report

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

Annotations already declare readOnlyHint=true, so the description doesn't repeat that. It adds transparency by revealing the tool returns a boolean indicating the existence of a `.SemanticModel/` folder, which is useful behavioral context. A slightly richer output description could improve, but it's already good.

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 only two sentences, front-loading the purpose, then providing an output detail and a usage hint. Every sentence adds value with no 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 no parameters, an existing output schema (per context), and annotations covering read-only, the description adds critical context about the `hasSemanticModel` flag and its relation to a sibling tool, making the tool fully self-explanatory for an agent.

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?

There are no parameters, so schema coverage is trivially 100%. The description has no parameter info to add, and per rubric, 0 parameters with full coverage warrants a baseline of 4.

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 tool shows the currently connected report path and includes the `hasSemanticModel` boolean. This distinguishes it from sibling tools which manipulate visuals, pages, or other aspects.

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 explicitly advises to check `hasSemanticModel` before calling `pbir_model_usage`, providing a concrete when-to-use and when-not-to-use guideline. This is direct and unambiguous.

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