Edit image(s) (img2img)

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

With no annotations provided, the description carries the full behavioral burden. It discloses supported image reference formats, mask usage, return behavior ('Returns the edited image URL(s) and metadata'), optional local saving, and configuration-derived credentials/model. It does not detail local save destination/overwrite behavior or API rate-limit/cost effects, but overall it provides substantial operational context.

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 front-loaded with the core purpose, followed by compact, non-redundant sentences covering accepted input formats, mask behavior, output/save behavior, and configuration source. Every sentence adds useful information without padding.

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?

The tool has 9 parameters, no annotations, no output schema, and zero schema descriptions, so the description needs to be quite comprehensive. It covers the essential workflow and several optional behaviors, but leaves size/quality/n/include_preview semantics and output metadata shape undocumented, which limits how confidently an agent can use the full parameter surface.

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%, so the description must compensate for undocumented parameters. It adds meaning for images (local path, URL, data URI, base64), mask (region to regenerate), save (optional local saving), and model (default from config), but it does not clarify n, size, quality, or include_preview beyond their bare schema names and defaults.

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 opens with a precise verb set ('Edit, transform, combine or extend') applied to 'one or more input images' and clarifies the modality as 'image + text to image, aka img2img'. This clearly distinguishes the tool from the sibling generate_image, which would operate without input 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 makes the use case clear: editing/transforming existing images with a prompt via the images/edits API. It also points to get_config/set_config for endpoint/key/model configuration, but it does not explicitly state when to prefer generate_image or list_image_models instead, leaving alternatives to inference rather than instruction.

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