list_models

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

With no annotations, the description does disclose useful behavior: no credentials or network access is required. It does not explain filtering behavior, whether results are static/configured, or how the optional capability input changes the returned set, so the transparency is adequate but incomplete.

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 efficient sentence with the key information front-loaded. There is no wasted text.

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?

The tool is simple and has an output schema, so return values need not be explained. However, the description leaves out the optional capability filtering behavior, which is important given the 0% schema description coverage.

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%, and the only optional parameter, capability, is not mentioned at all. Worse, the description says it lists all nine models, which could mislead an agent about how the capability filter works.

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 gives a clear verb and resource: list configured models. It also states the count, which makes the tool concrete, but it does not explicitly distinguish itself from sibling media-generation tools beyond the obvious list-versus-act distinction.

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?

Usage is implied: use this tool to discover available models, and the no-credentials note suggests it is safe for setup or capability checks. However, it does not explicitly say when to choose this over other tools or how the optional capability filter should affect usage.

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