edit_image

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions returning a task id and status, hinting at asynchronous behavior, but does not explain polling, wait semantics, callback_url, or how output URLs become available. It omits authentication requirements, rate limits, and whether the operation is blocking. The description provides minimal insight into the task lifecycle.

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 a single concise sentence that front-loads the action ('Create a GPT Image task') and includes essential context (edit image, return values). There is no redundancy or wasted words, exemplifying efficient structure.

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 9 parameters, no output schema, and no annotations, the description is too sparse to be complete. It does not explain the overall workflow (e.g., pairing with get_task to retrieve results), the async behavior controlled by wait, or how callback_url and poll_interval_ms function. The description leaves significant gaps for a complex task-based tool.

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 only 22% (2 of 9 parameters have descriptions). The tool description adds no parameter details beyond the name 'edit image,' failing to clarify required parameters like prompt, source_image_urls, aspect_ratio, or quality. It does not compensate for the low schema coverage, leaving the agent without meaningful guidance on how to construct valid requests.

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's function: 'Create a GPT Image task on RunAPI (edit image).' This distinguishes it from sibling tools like text_to_image by explicitly indicating it handles image editing. It also states return values (task id, status, output URLs), making the purpose unambiguous.

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 implies usage for image editing but provides no explicit guidance on when to use this tool versus alternatives like text_to_image. It does not mention prerequisites (e.g., needing a source image URL) or complementary tools like get_task for retrieval. Guidance is only implicit through the tool's name and the phrase 'edit image.'

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