list-models

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

No annotations are provided, so the description carries the burden. It states it lists models but does not disclose any behavioral traits such as read-only nature, authentication, or caching. However, the tool is simple and likely read-only, so the lack of disclosure is not critical but could be improved.

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 concise with two sentences, front-loading the purpose. The second sentence adds clear usage guidance. No fluff.

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 that there are no parameters and the tool is simple, the description is complete enough. It tells the agent what the tool does and when to use it. An output schema is present but not detailed in the description; however, for a list operation, the description is adequate.

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?

There are no parameters, and schema description coverage is 100% (vacuously). The description does not need to add parameter meaning. Baseline for zero parameters is 4, and the description adds no unnecessary information about parameters.

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 what the tool does: 'List models currently supported by qodercli.' It uses a specific verb ('List') and resource ('models supported by qodercli'). It also distinguishes from siblings by noting to use this before picking a model name for ask-qoder, implying ask-qoder is a different action.

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 explicitly states when to use this tool: 'Use this before picking a model name for ask-qoder.' This gives clear context. It does not explicitly mention when not to use it, but given the tool's singular purpose, the guidance is sufficient.

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