edit_image

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

With no annotations, the description carries the full burden and performs admirably. It discloses backend-specific limitations (mask, strength, watermark support differences), supported input formats (local path/URL/data URL), model defaults, and the output_dir saving behavior. This is rich behavioral context beyond simple tool purpose.

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 organized as a concise bullet list with each parameter on one line, packed with essential information. The front-loading of the purpose sentence and the elimination of redundant wording make it efficient for the tool's complexity.

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 15 parameters, two backend modes, and an output schema, the description is comprehensive: it covers parameter semantics, backend limitations, defaults, and input formats. The output schema exists, so return-value details are not needed. This description is highly complete 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 description coverage is 0%, but the description compensates by explaining every parameter (all 15) and adding constraints and defaults not present in the schema, such as mask not being supported by DashScope native API, watermark only for qwen-image-3.0, and strength only for the OpenAI-compatible backend. This fully compensates for the lack of schema 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 it is an image-to-image / editing tool that generates new images from 1-3 reference images and edit instructions. It distinguishes itself from sibling tools like generate_image (likely text-to-image) and video tools by emphasizing the reference-image-based editing workflow.

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 context by specifying that it uses 1-3 reference images plus an edit prompt, which implies when to use it (when editing/reference images are available). However, it does not explicitly name alternatives or state when not to use it, such as when starting from text-only, which could be done with generate_image.

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