cohere_classify

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

With no annotations provided, the description lacks behavioral details such as authorization needs (api_key is required but not mentioned), rate limits, or whether the tool is destructive. The few-shot learning aspect is implied but not explained.

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?

One short sentence with no wasted words. The key action and resource are front-loaded.

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 tool with 4 parameters and no output schema, the description is incomplete. It does not explain the format of inputs, the structure of examples, the model parameter, or the expected return type.

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 50% with two params described (inputs and examples) in the schema. The description repeats 'few-shot examples' already in schema and adds no meaning for api_key or model. It does not compensate for undocumented params.

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 verb 'classify', the resource 'texts into categories', and the method 'using Cohere Classify with few-shot examples'. It distinguishes from sibling tools like cohere_chat and cohere_embed which have different purposes.

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 on when to use this tool versus alternatives. While siblings include text_analyse and other classification tools, no explicit when-to-use or when-not-to-use is provided.

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