All-in-One Image Editing
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Please follow https://skillhub.cn/install/skillhub.md and install @ixhlink/ixhlink-skills-image-edit-pro.
About this skill
Problem
Image-editing Agents need to handle reference-image input, async task polling, and paid retry. This skill wraps the image_edit capability and keeps request, task status, and result URL in one call path.
Workflow
- Submit
POST /api/v1/llm/invokewithpromptandimages;imagesneeds at least 1 item, using eitherb64orurl. - On success, read
data.task.idand pollGET /api/v1/llm/tasks/{task_id}untilsucceededorfailed. - Output images are in
data.result.data[].url; poll every 2–5 seconds as a starting interval. - If the first call returns
402, keep the JSON body unchanged and retry withWeixinPay-RequiredandX-Payment-Idheaders.
Boundaries
- Paid calls require the Agent to have WeChat Pay capability; terminate and notify the user if it is missing.
400,404, and503usually point to parameter, model, or service issues; checkdata.error_messagewhen a task fails.
Use Cases
- An Agent edits a supplied product image according to a text prompt and returns the result image URL.
- A service submits a Base64 reference image and edit prompt, then polls the async task for output.
- A client receives a 402 response, keeps the request body unchanged, and retries with payment headers.
- An MCP/Web client checks WeChat Pay capability before confirming the paid image-editing flow.
Best For
- Platform engineers adding visual editing to Agents need to connect reference images, prompts, and result URLs.
- MCP developers integrating multimodal tools need to handle async polling and 402 payment retries.
- Backend engineers building paid creation products need per-call pricing, order confirmation, and body-preserving retries.
- Technical leads for image-editing products need clear Base64/URL input and task-status handling.
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