list_known_models

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

With no annotations, the description carries the full burden of disclosing behavior. '列出' clearly indicates a read-only listing operation with no mutation, but the description does not mention return format, whether the list is sorted, or what '容量' precisely refers to. This is acceptable for a simple list tool but not rich.

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 short sentence that directly states the tool's purpose with no filler. For a zero-parameter tool, this is appropriately sized and immediately informative.

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 no parameters, so the description covers the core purpose. However, with no output schema, no annotations, and no mention of the exact meaning of '容量' (e.g., context window size vs. model size), the description is only minimally 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 input schema has zero parameters, so the baseline is 4. The description adds no parameter details because none exist, and it appropriately focuses on what the tool returns.

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 names a specific action ('列出') and a specific resource ('内置映射表里已知的模型及其容量'), so the purpose is clear. However, it does not explicitly distinguish itself from siblings like model_context_window, which may also relate to model properties.

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?

There is no guidance on when to use this tool versus the sibling tools. The description implies a simple enumeration use case, but it never states conditions or alternatives, so the agent must infer when this is the right choice.

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