Retrieve the current status and latest result payload for a GPT-4o image text-to-image task by its ID.
Fetch the current status and latest result payload for a gpt-4o-image task.
| Name | Required | Description | Default |
|---|---|---|---|
| action | No | Asynchronous endpoint the task was created on. Defaults to the line's only asynchronous endpoint. | |
| task_id | Yes | Task id returned when the task was created. |
Changes observed during successful MCP inspections.
v0.2.0Input schema / additionalPropertiesRemoved value: -falsev0.1.7Input schema / properties / action / descriptionPrevious value: -"Endpoint the task was created on. Defaults to the line's only endpoint."New value: +"Asynchronous endpoint the task was created on. Defaults to the line's only asynchronous endpoint."v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It usefully signals a read-only retrieval that returns 'current status' plus the 'latest result payload' (implying results may be partial), but omits terminal-state semantics, polling behavior, and auth/permission requirements.
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?
A single front-loaded sentence with no filler; the resource and scope are stated immediately and nothing 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?
For a low-complexity 2-param fetch with no output schema, the description does convey what comes back (status and latest payload). However, without annotations or an output schema it should say more about result states and polling expectations to be fully self-sufficient.
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 100%, so both task_id and the action enum/default are already documented in the schema. The description adds no parameter-level meaning beyond what the schema provides, so the baseline 3 applies.
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 uses a specific verb ('Fetch') and names the exact resource ('current status and latest result payload') scoped to a gpt-4o-image task. It is clearly distinct from text_to_image, check_pricing, and login, though it never explicitly contrasts itself with the creation sibling.
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?
Usage is only implied: an agent can infer this is the polling/retrieval counterpart to an async text_to_image call. There is no explicit statement of when to call it (e.g., after task creation, on what cadence) or what alternatives exist.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.