local_gpu_list_profiles

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

No annotations are provided, so the description must disclose behaviors. It only states the action without confirming read-only status, permissions, or side effects. The optional 'authorization_scope' parameter is not explained, and 'capabilities' is undefined.

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 a single, focused sentence with no redundant words. It front-loads the action and resource, making it easy to parse while conveying the core functionality.

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?

An output schema exists, so return values are covered. However, the description omits any explanation of the authorization_scope parameter and provides no usage context (e.g., when to use vs. siblings). These gaps make it only minimally viable for a simple list 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?

The input schema has one optional enum parameter 'authorization_scope' with 0% schema description coverage. The description does not mention it, leaving its meaning and effect on the returned profiles completely unexplained.

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 uses a specific verb 'List' with clear resources: 'registered visual-asset profiles' and 'current local backend capabilities.' This distinguishes it from sibling tools like local_gpu_generate_image or local_gpu_discover_models, which focus on generation or model discovery.

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 implies a discovery/inventory use case but provides no explicit when-to-use guidance or alternatives. It names no exclusions or conditions for choosing this over sibling tools, leaving the context implicit.

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