classify_image

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

With no annotations provided, the description carries full burden for behavioral disclosure. It reveals offline capability, no API key requirement, 1000+ categories, and confidence scores sorted descending. However, it doesn't mention error handling for invalid paths or unsupported image formats, which would enhance transparency.

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 clear sections (main action, use cases, exclusions, return format). Every sentence adds value. It could be slightly more structured (e.g., bullet points) but is well-organized for an AI agent.

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?

Despite lacking an output schema, the description explains the return format (JSON array with label names and confidence scores) and sorting order. It covers key aspects like local file path, offline operation, and category scope, making it complete for a simple classification tool.

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 describes the only parameter 'path' with a clear description. The tool description reinforces that it's a local image path but adds no additional semantics beyond what the schema provides. Since schema coverage is 100% and the parameter is straightforward, a baseline score of 3 is appropriate.

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: classifying local image content into categories using Apple Vision. It distinguishes itself from sibling tools by explicitly listing what not to use it for (text extraction, face/barcode detection) and referencing dedicated alternatives.

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 provides explicit 'USE WHEN' scenarios (user wants to know what is depicted) and 'DO NOT USE' examples with specific alternative tools (ocr_image, detect_faces). It also notes that the tool works offline without an API key.

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