openclaw_models_list

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 explicitly declares the tool as read-only and reveals it wraps an existing API (`models.list`). This is informative, though additional details like pagination or default result limits would enhance transparency.

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?

Two sentences with no wasted words. The first sentence states purpose and scope; the second provides implementation context. Information is front-loaded and highly efficient.

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?

For a simple list tool with one optional parameter and no output schema, the description is complete. It specifies what is listed, read-only behavior, and the underlying API. No missing details for an agent to use it correctly.

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 coverage is 100% with one parameter (`instance`). The schema already describes the parameter well, including fallback behavior and cross-referencing other tools. The description adds no further meaning, so baseline score 3 is appropriate.

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 lists models available to the gateway, specifies the scope (Anthropic, OpenAI, etc.), mentions output includes IDs and provider metadata, and notes it wraps `models.list`. This distinguishes it from sibling tools like `openclaw_tools_catalog` or `openclaw_agents_list`.

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 usage for listing gateway models but does not explicitly state when to use this tool versus alternatives, nor provide exclusions or prerequisites. The read-only note offers some guidance, but lacks direct comparisons to sibling tools.

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