cohere_classify

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 does not disclose behavioral traits such as whether the operation is read-only, authentication requirements, rate limits, or the nature of the response. The minimal description offers no insight beyond the basic action.

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 very short (one sentence) and front-loaded with the key action. However, it is so brief that it sacrifices essential details. It earns a 4 for efficiency but loses a point for being too terse.

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 has four parameters (two required), no output schema, and no annotations. The description does not explain the output format, how to structure the few-shot examples, or what model options exist. Given the complexity of few-shot classification, the description is incomplete and lacks necessary context for effective use.

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 schema already describes 'inputs' and 'examples' as JSON arrays, but the description adds no further meaning. It does not explain what 'api_key' or 'model' should contain, nor does it elaborate on the format of the few-shot examples. With 50% schema coverage, the description fails to compensate for the undocumented 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 the tool's purpose: 'Classify texts into categories using Cohere Classify with few-shot examples.' It specifies the verb 'classify' and the resource 'texts', and mentions a distinguishing feature (few-shot examples). Among sibling tools like cohere_chat and cohere_embed, this uniquely identifies the classification capability.

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 only implies usage with 'few-shot examples' but provides no explicit guidance on when to use this tool versus alternatives (e.g., cohere_generate or cohere_rerank). It does not mention prerequisites like needing an API key or cite any context for appropriate use.

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