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

Adds real context beyond annotations: credit consumption, an async-style project id consumed by wait_for_image_project, and plan-gated model availability including the default model. It stops short of stating what happens on failure, whether credits are refunded, or how long the project takes.

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?

Four short sentences, front-loaded with the core action and the sibling contrast, then cost, then follow-up tool, then plan caveat. No sentence is wasted.

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?

With an output schema, full annotations, and 86% parameter coverage, the description covers the agent-critical gaps: cost, the async handoff tool, and plan-dependent model choice. The missing piece is guidance on how this general editor relates to the specialized edit_* siblings.

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 86% and the model/resolution enums already document tier availability and per-model resolution limits, so the schema carries the parameter burden. The description's note that the default model is not on every plan adds a little meaning but largely restates the schema's tier lists.

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?

States a specific verb and resource ('Edits one or more supplied images using a text prompt') and immediately contrasts with the closest sibling, generate_image, for prompt-only creation. An agent can tell this apart from generate_image without reading either schema.

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?

Explicitly routes prompt-only work to generate_image and points to wait_for_image_project as the follow-up. It does not say when to prefer this general editor over the many specialized siblings (edit_face_in_photo, change_clothes_in_photo, remove_image_background, upscale_image), leaving that boundary to inference.

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