cohere_list_models

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

The description lacks behavioral details beyond a basic action. It does not mention authentication requirements (despite an optional api_key parameter), side effects (none implied), or output format. With no annotations to compensate, the agent cannot assess safety or prerequisites.

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?

While the description is a single sentence with no wasted words, it is under-specified. Conciseness should not come at the expense of necessary information; the tool description should include usage context, parameter semantics, and behavioral notes, which are missing.

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 lack of annotations and output schema, the description should fully explain the tool's behavior and results. It fails to mention what a 'model' listing contains (IDs, names?), or whether pagination exists. The description is insufficient for an agent to use effectively without external knowledge.

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 one parameter (api_key) with no description, and the description does not mention it. The agent is left guessing whether an API key is needed and how it might affect the results. The parameter is essential for context, but the description provides no semantic value.

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 explicitly states 'List all available Cohere models,' which is a clear verb+resource combination. It differentiates from sibling Cohere tools (e.g., cohere_chat, cohere_generate) by specifying the listing action, and from other model listing tools (e.g., openai_list_models) by specifying Cohere.

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?

No guidance is provided on when to use this tool versus alternatives (e.g., for selecting a model before calling cohere_chat). The description does not explain prerequisites, the read-only nature, or that results can be used in other Cohere calls. This forces the agent to infer usage context.

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