list_models

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

With no annotations, the description carries the full burden. It communicates a safe, read-only 'List' operation with no side effects, but does not disclose potential return format, pagination, or what 'capabilities' means specifically. This is acceptable but leaves room for more behavioral detail.

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, front-loaded sentence that immediately states the action and resource. Every word is useful, and there is no redundancy or filler.

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's simplicity (no parameters, no annotations, no output schema), the description gives enough context: it names the resource and the type of output (available models + capabilities). It could be more explicit about the return format, but the simple nature makes it largely 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?

The tool accepts zero parameters, and the schema coverage is 100% (empty schema). Per the baseline for no parameters, a score of 4 is appropriate. The description adds no parameter-specific information because there are no parameters to describe, and it correctly references the output content.

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') and identifies the exact resource ('available FLUX models on NVIDIA NIM') plus additional value ('their capabilities'). This clearly distinguishes it from sibling tools like generate_image and edit_image, which perform actions rather than listing.

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 the tool should be used when an agent needs to know which FLUX models are available and what they can do. While it doesn't explicitly exclude alternatives or mention sibling tools, the context is clear and unambiguous for a listing tool.

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