describe_image

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

With no annotations provided, the description carries full burden. It discloses the underlying models (Florence-2, MiniCPM-V) and the return structure (dict with description, model name, prompt). It does not mention limitations, rate limits, or destructive behavior (not applicable).

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 structured with an introductory sentence followed by Args and Returns sections. It is moderately concise; each sentence adds value. Minor redundancy: 'Returns Dict with ...' could be integrated, but overall well-organized.

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?

Given that an output schema exists (as indicated by context signals), the description explains the return format. It covers all parameters and the tool's purpose. No gaps for a tool of this complexity.

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 0%, so the description must compensate. It explains all three parameters: image_path supports various formats, detail_level differentiates normal vs high, model_mode explains the two model choices with use cases (default vs document understanding). This adds significant meaning beyond the schema.

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 starts with 'Describe an image in natural language using Florence-2' which clearly states the action and resource. It distinguishes from sibling tools (e.g., describe_screenshot, ocr_image) by focusing on image description vs. OCR or document parsing.

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 does not explicitly state when to use this tool vs. alternatives. However, it does differentiate model modes ('fast' vs 'deep' for document understanding), giving some guidance on parameter choices. No exclusion or alternative tool references.

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