analyze_image

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

With no annotations, the description carries the transparency burden. It discloses the automatic compression behavior for local images, its effect on OCR vs. original detail, and how to disable it with compress=false. This is valuable behavioral context beyond the schema.

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 two sentences, front-loaded with the core purpose. Every clause earns its place: capabilities, image vs. batch, presets vs. prompt, and compression policy. No wasted words.

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 7 parameters and no output schema, the description covers the main invocation patterns, task types, and a key behavioral caveat. It doesn't explain return formats, but that is expected when no output schema is provided. The description is sufficient for an agent to select and use the tool effectively.

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 100%, so the baseline is 3. The description adds meaning by clarifying the difference between image and image_batch, and by explaining the practical implications of the compress parameter (OCR clarity vs. detail/token cost). This goes beyond the schema's basic field descriptions.

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 performs image understanding and OCR, listing concrete use cases (description, text recognition, chart/UI/error diagnostics). This distinguishes it from sibling tools like analyze_video, analyze_audio, and asr by explicitly focusing on images.

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 clear usage guidance: single image vs. multi-image (image_batch), preset selection vs. free-form prompt, and compression behavior. It does not explicitly mention exclusions (e.g., 'use analyze_video for video'), but the tool name and sibling list make the domain obvious.

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