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submit_image_edit

Submit image edit jobs asynchronously with uploaded images; returns a task ID so you can query results and save edited images later.

Instructions

POST edits?async=true 提交收费异步编辑,以 image[] 上传;返回 task_id,之后查询并落盘。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sizeNo可选 auto 或 WIDTHxHEIGHT;两边为16倍数、最大3840、比例不超过3:1、总像素655360..8294400。省略时不发送。
groupNo分组声明:默认 reverse(逆向);仅用户明确使用官转时传 official。此字段不发送上游、不改变密钥后台分组。reverse
modelYesGPT Image 2.5 Sunburst 非常适合对编辑精度要求极高的应用场景;GPT Image 2.5 Flare 是目前用于生成高质量图片的最快模型。模型可以接受文本和图片作为输入,然后输出相应的图片。以上为用户提供的供应商选型说明,尚未做速度或质量对比实测。请结合用户意图选择并告知所用模型。
imagesYes本机绝对图片路径、公开 HTTP(S) 图片 URL 或 base64 data URL;PNG/JPEG/WebP。
promptYes
qualityNo
output_dirNo可选绝对输出目录;默认配置目录。异步任务查询默认沿用提交目录。
official_optionsNo仅 group="official" 可用的官转扩展参数。未声明官转时传入此对象会在收费前拒绝。

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
costNo
noteNo
filesNo
groupNo
usageNo
statusYes
task_idNo
warningNo
progressNo
responseNo
next_toolNo
output_dirNo
fail_reasonNo
save_statusNo
wait_timed_outNo
download_errorsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already declare non-read-only, non-idempotent, open-world. The description adds genuinely new context: the call is paid (收费) and asynchronous, uploads via image[], returns a task_id, and must be followed by a query/save step. Cost and the async contract are material facts not carried by the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single dense sentence with the operation and the follow-up contract front-loaded; nothing is padded. The mixed Chinese/English and URL-fragment style ('POST edits?async=true') cost a little clarity for no gain.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

An output schema exists, so return-value detail is not required, and the description does name task_id. However, for an 8-parameter paid async tool with several siblings that also submit or edit images, it omits the sync-vs-async decision and lifecycle guidance an agent needs to call the right tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 75% and the schema descriptions for size, group, model, images, output_dir, and official_options are already detailed. The description only echoes the image[] upload field and adds nothing about the other parameters, so it does not compensate for the remaining gap — baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb + resource (submit an async paid image edit via image[] upload) and notes the return value (task_id) and follow-up step. An agent can distinguish it from submit_image_generation/submit_image_batch, though the terse mixed-language phrasing ('POST edits?async=true') relies on prior knowledge of the API shape.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Implies a workflow — submit, then '查询并落盘' (query then save to disk) — which points at the get_image_task/wait_image_task siblings. But it never explicitly says when to prefer this async submission over the sync edit_image or over submit_image_batch, so the choice among siblings is left to inference.

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