ai_classify

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

No annotations exist. The description only notes a cost per call. It does not disclose any behavioral traits such as whether it returns confidence scores, handles unknown categories, or requires internet access. Insufficient for a mutation-like AI tool.

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 extremely short, which is not conciseness but under-specification. Important details (e.g., category format, return structure) are missing. Every sentence must earn its place, and this one does not provide enough value.

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?

With no output schema, no annotations, and 4 parameters, the description is wholly inadequate. It does not explain return format, error handling, or authentication flow for L402 mode. An agent cannot reliably invoke this tool based on this description.

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% (preimage and macaroon have minimal descriptions). The tool description adds no extra meaning beyond the schema. The key parameters 'text' and 'categories' lack any description or usage hints.

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 core function: classifying text into user-provided categories. It also includes a cost note. However, it could be more specific about the nature of classification (e.g., multi-label, single-label).

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 siblings like ai_sentiment or ai_extract. No prerequisites, exclusions, or alternatives are mentioned.

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