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Agent Skill · 图像处理

qwencloud-image-generation(qwencloud 图像生成)

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

qwencloud-image-generation 是图像处理类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在图像处理类的 1,562 个 Skill 里排第 404。

总安装 7,566周安装 325GitHub Stars 公开资料未说明下载 2,652核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.2.0

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:qwencloud-image-generation(qwencloud 图像生成)
来源仓库:https://github.com/cuixiaoyang123/qwencloud-image-generation
安装命令:
openclaw skills install qwencloud-image-generation
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install qwencloud-image-generation

这个 Skill 是做什么的

图像处理类 Skill 处理生成、裁剪、压缩和批量转换图片的任务。

qwencloud-image-generation 使用 Wan 与 Qwen Image 模型生成及编辑图像。适用于文生图、风格转换与主题一致性处理的场景。支持文本渲染与局部编辑,适合广告与设计工作流。使用前需确认输入图片版权归属,避免生成侵权内容。建议设置负面提示词以减少不适当元素出现概率。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install qwencloud-image-generation;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

qwencloud-image-generation 怎么安装?

在终端执行 openclaw skills install qwencloud-image-generation。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

qwencloud-image-generation 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

qwencloud-image-generation 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

qwencloud-image-generation 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

qwencloud-image-generation 用的人多吗?

公开数据是累计安装 7,566 次,近一周安装 325 次,下载 2,652 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

qwencloud-image-generation 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理图像处理类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

图像处理类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
ai-image-generation

AI 图像生成 · Codex、Claude

4,365,552382调用外部服务未明确有提醒
openai-image-gen

OpenAI 图像生成 · OpenClaw

1,906,88432需要联网MIT-0有提醒
image

图像 · OpenClaw

525,99926需要联网MIT-0通过
baoyu-cover-image

宝玉封面图 · Codex、Claude

474,24016,779只读MIT有提醒
baoyu-image-gen

宝玉图像生成器 · Codex、Claude

468,00716,778接触敏感数据MIT通过
qwencloud-image-generation

qwencloud 图像生成 · 本页

7,566—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
qwencloud-image-generation
description
[QwenCloud] Generate and edit images using Wan and Qwen Image models. Supports text-to-image, image editing (style transfer, subject consistency, text rendering), and interleaved text-image output. TRIGGER when: user wants to create illustrations, product images, artistic designs, posters, text-to-image generation, edit/transform existing images, apply style transfer, generate images based on reference photos, interleaved text-image content, mentions Wan/Qwen Image models/AI art creation, or explicitly invokes this skill by name (e.g. use qwencloud-image-generation). DO NOT TRIGGER when: user wants to understand/analyze existing images or OCR (use qwencloud-vision), video generation (use qwencloud-video-generation), text-only tasks.
compatibility
Requires Python 3.9+ and curl. Cursor: auto-loaded. Claude Code: read this skill's SKILL.md before first use.
Agent setup: If your agent doesn't auto-load skills (e.g. Claude Code), see agent-compatibility.md once per session.

Qwen Image Generation

Generate and edit images using Wan and Qwen Image models. Supports text-to-image, reference-image editing (style transfer, subject consistency, multi-image composition, text rendering), and interleaved text-image output. This skill is part of qwencloud/qwencloud-ai.

Skill directory

Use this skill's internal files to execute and learn. Load reference files on demand when the default path fails or you need details.

LocationPurpose
scripts/image.pyDefault execution — sync/async, upload, download
references/execution-guide.mdFallback: curl (sync/async), code generation
references/prompt-guide.mdPrompt formulas, style keywords, negative_prompt, prompt_extend decision
references/api-guide.mdAPI supplement
references/sources.mdOfficial documentation URLs
references/agent-compatibility.mdAgent self-check: register skills in project config for agents that don't auto-load

Security

NEVER output any API key or credential in plaintext. Always use variable references ($DASHSCOPE_API_KEY in shell, os.environ["DASHSCOPE_API_KEY"] in Python). Any check or detection of credentials must be non-plaintext: report only status (e.g. "set" / "not set", "valid" / "invalid"), never the value. Never display contents of .env or config files that may contain secrets.

When the API key is not configured, NEVER ask the user to provide it directly. Instead, help create a .env file with a placeholder (DASHSCOPE_API_KEY=sk-your-key-here) and instruct the user to replace it with their actual key from the QwenCloud Console. Only write the actual key value if the user explicitly requests it.

Key Compatibility

Scripts require a standard QwenCloud API key (sk-...). Coding Plan keys (sk-sp-...) cannot be used — image generation models are not available on Coding Plan, and Coding Plan does not support the native QwenCloud API. The script detects sk-sp- keys at startup and prints a warning. If qwencloud-ops-auth is installed, see its references/codingplan.md for full details.

Mode Selection Guide

User WantModeModel
Generate image from text onlyt2iwan2.6-t2i (default), or wan2.7-image / wan2.7-image-pro
Edit image / apply style transfer based on 1–4 reference imagesimage-editwan2.7-image-pro / wan2.7-image / wan2.6-image
Subject consistency: generate new images maintaining subject from referencesimage-editwan2.7-image-pro / wan2.7-image / wan2.6-image
Multi-image composition: combine style from one image, background from anotherimage-editwan2.7-image-pro / wan2.7-image / wan2.6-image
Single-image editing preserving subject consistencyi2iwan2.5-i2i-preview
Multi-image fusion: place object from one image into another scenei2iwan2.5-i2i-preview
Interleaved text-image output (e.g., tutorials, step-by-step guides)interleavewan2.6-image
Fast text-to-image draftst2iwan2.2-t2i-flash
Edit text within images, precise element manipulationimage-editqwen-image-2.0-pro
Multi-image fusion with realistic texturesimage-editqwen-image-2.0-pro
Posters / complex Chinese+English text renderingt2iqwen-image-2.0-pro
Text-to-image with fixed aspect ratios (batch)t2iqwen-image-plus / qwen-image-max

Model Selection

Wan Series (default)

ModelUse Case
wan2.6-t2iRecommended for text-to-image — sync + async, best quality
wan2.7-image-proMulti-function (4K support) — text-to-image, image editing (0–9 images), sequential multi-image, interactive editing (bbox), thinking mode, color palette. Max 4K for t2i, 2K for editing
wan2.7-imageMulti-function (faster) — same as pro but max 2K, no 4K support
wan2.6-imageImage editing (NOT for pure text-to-image) — requires reference_images or enable_interleave: true. Style transfer, subject consistency (1–4 images), interleaved text-image output, 2K
wan2.5-i2i-previewImage editing — single-image editing with subject consistency, multi-image fusion (up to 3 images), async-only
wan2.5-t2i-previewPreview — free size within constraints
wan2.2-t2i-flashFast — lower latency
wan2.2-t2i-plusProfessional — improved stability

Qwen Image Series

ModelUse Case
qwen-image-2.0-proFused generation + editing — text rendering, realistic textures, multi-image (1–3 input, 1–6 output)
qwen-image-2.0Accelerated generation + editing
qwen-image-edit-maxImage editing — 1–6 output images
qwen-image-edit-plusImage editing — 1–6 output images
qwen-image-editImage editing — 1 output image only
qwen-image-plusText-to-image — fixed resolutions only (async)
qwen-image-maxText-to-image — fixed resolutions only

Qwen Image editing models (qwen-image-2.0-pro, qwen-image-2.0, qwen-image-edit-max/plus/edit) use the same sync endpoint as wan2.6-image (/multimodal-generation/generation) with messages format. They support text editing in images, element add/delete/replace, style transfer, and multi-image fusion (1–3 input images). Size range: 512x512 to 2048x2048. qwen-image-2.0-pro and qwen-image-2.0 also support pure text-to-image (no reference images needed).

Qwen Image text-to-image models (qwen-image-plus, qwen-image-max) use a different endpoint (/text2image/image-synthesis) with input.prompt format (async-only). They support only 5 fixed resolutions: 1664\*928, 1472\*1104, 1328\*1328, 1104\*1472, 928\*1664.

Choosing between wan2.6-image and wan2.5-i2i-preview for image editing:

  • wan2.6-image supports up to 4 images, higher resolution (2K), interleaved text-image output, and sync mode. Use for multi-image style composition, interleaved tutorials.
  • wan2.5-i2i-preview uses a simpler prompt-only editing interface (no messages format), supports up to 3 images, async-only. Use for straightforward single-image edits and multi-image object fusion.
  1. User specified a model → use directly.
  2. Consult the qwencloud-model-selector skill when model choice depends on requirement, scenario, or pricing.
  3. Text-to-image (prompt only, no reference images) → use wan2.6-t2i (default) or wan2.7-image / wan2.7-image-pro (multi-function, higher quality). NEVER use wan2.6-image for pure text-to-image — it will error without reference images or enable_interleave: true.
  4. Reference images / image editing / interleaved output → wan2.7-image-pro (recommended), wan2.7-image, or wan2.6-image.
⚠️ Important: The model list above is a point-in-time snapshot and may be outdated. Model availability changes frequently. Always check the official model list for the authoritative, up-to-date catalog before making model decisions.
Model details: For more information about a specific model, direct the user to its detail page: https://www.qwencloud.com/models/<model-name> (replace <model-name> with the exact model ID, e.g. wan2.7-image-pro → https://www.qwencloud.com/models/wan2.7-image-pro). NEVER modify or guess the model name in the URL.
Dynamic model queries: If the qwencloud-model-selector skill or QwenCloud CLI (qwencloud models info <model>) is available, use it for real-time model data. CLI requires authentication — see the qwencloud-usage skill for login flow.

Execution

⚠️ Multiple artifacts: When generating multiple files in a single session, you MUST append a numeric suffix to each filename (e.g. out_1.png, out_2.png) to prevent overwrites.

Prerequisites

  • API Key: Check that DASHSCOPE_API_KEY (or QWEN_API_KEY) is set using a non-plaintext check only (e.g. in shell: [ -n "$DASHSCOPE_API_KEY" ]; report only "set" or "not set", never the key value). If not set: run the qwencloud-ops-auth skill if available; otherwise guide the user to obtain a key from QwenCloud Console and set it via .env file (echo 'DASHSCOPE_API_KEY=sk-your-key-here' >> .env in project root or current directory) or environment variable. The script searches for .env in the current working directory and the project root. Skills may be installed independently — do not assume qwencloud-ops-auth is present.
  • Python 3.9+ (stdlib only, no pip install needed)

Environment Check

Before first execution, verify Python is available:

python3 --version  # must be 3.9+

If python3 is not found, try python --version or py -3 --version. If Python is unavailable or below 3.9, skip to Path 2 (curl) in execution-guide.md.

Default: Run Script

Script path: Scripts are in the scripts/ subdirectory of this skill's directory (the directory containing this SKILL.md). You MUST first locate this skill's installation directory, then ALWAYS use the full absolute path to execute scripts. Do NOT assume scripts are in the current working directory. Do NOT use cd to switch directories before execution.

Execution note: Run all scripts in the foreground — wait for stdout; do not background.

Discovery: Run python3 <this-skill-dir>/scripts/image.py --help first to see all available arguments.

# Text-to-image (wan2.6-t2i, default)
python3 <this-skill-dir>/scripts/image.py \
  --request '{"prompt":"A cozy flower shop with wooden door"}' \
  --output output/qwencloud-image-generation/images/out.png \
  --print-response

# Image editing with reference images (wan2.6-image)
python3 <this-skill-dir>/scripts/image.py \
  --model wan2.6-image \
  --request '{"prompt":"Apply watercolor painting style to this photo","reference_images":["https://img.alicdn.com/imgextra/i1/NotRealJustExample/photo.jpg"],"n":1,"size":"1K"}' \
  --output output/qwencloud-image-generation/images/out.png \
  --print-response

More examples (interleaved output, wan2.5-i2i, qwen-image-2.0-pro, qwen-image-plus): See execution-guide.md

ArgumentDescription
--request '{...}'JSON request body
--file path.jsonLoad request from file
--asyncForce async mode (required for wan2.5 and older; auto-enabled for qwen-image-plus/max and interleaved output)
--model IDOverride model (wan2.6-t2i default; see model list in help)
--output pathSave image to path (or directory for multi-image output)
--print-responsePrint response JSON to stdout

Verify Result

  • Exit code 0 + output contains valid JSON with output.results or output.task_id → success
  • Non-zero exit, HTTP error, empty response, or error JSON → fail
  • Async: submission must return output.task_id; poll must reach task_status: SUCCEEDED
  • Post-execution check: Verify the output file exists and has non-zero size (ls -la <output_path>)
  • MANDATORY — stderr signal check: After confirming the result, scan the command's stderr output for [ACTION_REQUIRED] or [UPDATE_AVAILABLE]. If either signal is present, you MUST follow the instructions in Update Check below before responding to the user.

On Failure

If the script fails, match the error output against the diagnostic table below to determine the resolution. If no match, read execution-guide.md for alternative paths: curl commands (Path 2 — sync and async), code generation (Path 3), and autonomous resolution (Path 5).

If Python is not available at all → skip directly to Path 2 (curl) in execution-guide.md.

Error PatternDiagnosisResolution
command not found: python3Python not on PATHTry python or py -3; install Python 3.9+ if missing
Python 3.9+ requiredScript version check failedUpgrade Python to 3.9+
SyntaxError near type hintsPython < 3.9Upgrade Python to 3.9+
QWEN_API_KEY/DASHSCOPE_API_KEY not foundMissing API keyObtain key from QwenCloud Console; add to .env: echo 'DASHSCOPE_API_KEY=sk-...' >> .env; or run qwencloud-ops-auth if available
HTTP 401Invalid or mismatched keyRun qwencloud-ops-auth (non-plaintext check only); verify key is valid
SSL: CERTIFICATE_VERIFY_FAILEDSSL cert issue (proxy/corporate)macOS: run Install Certificates.command; else set SSL_CERT_FILE env var
URLError / ConnectionErrorNetwork unreachableCheck internet; set HTTPS_PROXY if behind proxy
HTTP 429Rate limitedWait and retry with backoff
HTTP 5xxServer errorRetry with backoff
PermissionErrorCan't write outputUse --output to specify writable directory

Quick Reference

Request Fields (Common)

FieldTypeDescription
promptstringText description of the image to generate (required)
negative_promptstringContent to avoid in the image (max 500 chars)
sizestringResolution — 1280*1280 (t2i default), 1K/2K or width*height (wan2.6-image)
seedintRandom seed for reproducibility [0, 2147483647]
modelstringwan2.6-t2i (default) or other Wan model
prompt_extendboolEnable prompt rewriting (default: true; image editing mode only)

Request Fields (wan2.7-image-pro / wan2.7-image — Multi-function)

FieldTypeDescription
reference_imagesstring[]0–9 image URLs or local paths
reference_imagestringSingle image URL/path (shorthand)
sizestring1K, 2K (default), or 4K (pro only, t2i mode). Or pixel dimensions
enable_sequentialbooltrue: sequential multi-image mode (n=1–12). false (default): single/batch mode (n=1–4)
nintImages to generate. Sequential mode: 1–12 (default 12). Non-sequential: 1–4 (default 4). Billed per image.
thinking_modeboolEnable enhanced reasoning for better quality (default: true). Only for t2i (no images, non-sequential)
bbox_listList[List[List[int]]]Interactive editing regions. Format: [[[x1,y1,x2,y2],...], ...]. List length = image count. Empty [] for images without edits
color_palettearrayCustom color theme (3–10 colors). Each: {"hex":"#C2D1E6","ratio":"23.51%"}. Sum of ratios = 100%. Non-sequential mode only
watermarkboolAdd "AI Generated" watermark (default: false)

Note: thinking_mode increases latency but improves quality. enable_sequential generates a coherent image sequence (e.g., same character across scenes).

Request Fields (wan2.6-image — Image Editing)

FieldTypeDescription
reference_imagesstring[]1–4 image URLs or local paths for editing mode; 0–1 for interleave mode
reference_imagestringSingle image URL/path (shorthand; reference_images takes precedence)
enable_interleaveboolfalse (default): image editing mode; true: interleaved text-image output
nintNumber of images to generate in editing mode (1–4, default: 1). Billed per image.
max_imagesintMax images in interleave mode (1–5, default: 5). Billed per image.
watermarkboolAdd "AI Generated" watermark (default: false)

Other Models (wan2.5-i2i, qwen-image-edit, qwen-image-plus/max)

These models have specific parameter requirements:

ModelKey Differences
wan2.5-i2i-previewasync-only, 1–3 images, prompt+images[] format (not messages)
qwen-image-edit-*1–3 images, n=1–6 (except qwen-image-edit: n=1 only), no interleave
qwen-image-plus/maxasync-only, n fixed at 1, 5 fixed resolutions only

Full parameter tables: See api-guide.md for detailed parameters.

Size Reference (wan2.6-image)

  • Editing mode: 1K (default, ~1280×1280) or 2K (~2048×2048)
  • Interleave mode: pixel dimensions with total pixels in [768×768, 1280×1280]

Common aspect ratios: 1280*1280 (1:1), 960*1280 (3:4), 1280*960 (4:3), 720*1280 (9:16), 1280*720 (16:9)

Response Fields

FieldDescription
image_urlURL of generated image (24h validity). Use this when chaining to another skill.
image_urlsArray of all image URLs (multi-image output, wan2.6-image, qwen-image-edit)
image_countNumber of generated images
local_pathLocal file path of the downloaded image. Use this for user preview or non-API operations.
local_pathsArray of local file paths (multi-image output)
interleaved_contentArray of {type, text/image} objects (interleave mode)
width / heightImage dimensions
seedSeed used

API Details

  • Sync endpoint (wan2.6-t2i, wan2.6-image editing, qwen-image-edit series): POST /api/v1/services/aigc/multimodal-generation/generation
  • Async endpoint (wan2.6 and older t2i): POST /api/v1/services/aigc/image-generation/generation with X-DashScope-Async: enable
  • Async endpoint (wan2.5-i2i-preview): POST /api/v1/services/aigc/image2image/image-synthesis with X-DashScope-Async: enable
  • Async endpoint (qwen-image-plus, qwen-image-max): POST /api/v1/services/aigc/text2image/image-synthesis with X-DashScope-Async: enable
  • wan2.6-t2i resolution: Total pixels in [1280x1280, 1440x1440], aspect ratio [1:4, 4:1]
  • wan2.6-image resolution: Editing mode [768x768, 2048x2048]; Interleave mode [768x768, 1280x1280]; aspect ratio [1:4, 4:1]
  • Input images (wan2.6-image): JPEG/JPG/PNG/BMP/WEBP, 240–8000px per dimension, ≤10MB
  • Local files: Script auto-uploads to DashScope temp storage (oss:// URL, 48h TTL). Pass local paths directly — no manual upload step needed.
  • Production: Default temp storage has 48h TTL and 100 QPS upload limit — not suitable for production, high-concurrency, or load-testing. To use your own OSS bucket, set QWEN_TMP_OSS_BUCKET and QWEN_TMP_OSS_REGION in .env, install pip install alibabacloud-oss-v2, and provide credentials via QWEN_TMP_OSS_AK_ID / QWEN_TMP_OSS_AK_SECRET or the standard OSS_ACCESS_KEY_ID / OSS_ACCESS_KEY_SECRET. Use a RAM user with least-privilege (oss:PutObject + oss:GetObject on target bucket only). If qwencloud-ops-auth is installed, see its references/custom-oss.md for the full setup guide.
  • Interleaved sync: Requires streaming (X-DashScope-Sse: enable + stream: true); use async mode via this script instead

Cross-Skill Chaining

When using generated images as input for another skill (e.g., video-gen i2v, vision analyze):

  • Pass image_url directly — do NOT download and re-pass as local path
  • All downstream scripts detect URL prefixes (https://, oss://) and pass them through without re-upload
  • Use local_path only for user preview or non-API operations (e.g., opening in editor)
ScenarioUse
Feed to another skill (video-gen, vision, image-edit)image_url (URL)
Show to user / open in editorlocal_path (local file)

Error Handling

HTTPMeaningAction
401Invalid or missing API keyRun qwencloud-ops-auth if available; else prompt user to set key (non-plaintext check only)
400Bad request (invalid prompt, size)Verify parameters and constraints
429Rate limitedRetry with exponential backoff
5xxServer errorRetry with exponential backoff
Usage & billing: Use the qwencloud-usage skill to check usage, free tier quota, and billing directly. Alternatively, the user can visit the QwenCloud console: Usage Analytics | Pay-as-you-go Billing | Coding Plan Billing NEVER fabricate, guess, or construct usage/billing/console URLs. Only provide the exact links listed in this skill. If a URL is not listed here, do not invent one.

Output Location

Prefer the current working directory. Default subdirectory: ./output/qwencloud-image-generation/.

Write prohibition: NEVER write output files into this skill's installation directory or any skills/ hierarchy. All generated content must go to output/ under the current working directory or a user-specified path.

Update Check (MANDATORY Post-Execution)

After script execution, check stderr for action signals. The script automatically detects update status and emits structured signals. You MUST act on them. This section also applies when the user explicitly asks to check for updates.

Signal: [ACTION_REQUIRED] qwencloud-update-check skill is not installed

When stderr contains this signal, you MUST present the following options to the user and wait for their response before proceeding. Do NOT silently skip this.

The update-check skill is not installed. It keeps you informed about new qwencloud/qwencloud-ai features and bug fixes. 1) Install now — I'll run the install command for you 2) Skip for now — do nothing this time 3) Never remind me — permanently suppress this prompt

After the user responds:

  • User chooses 1 → run: npx skills add QwenCloud/qwencloud-ai --skill qwencloud-update-check -y, then run: python3 <this-skill-scripts-dir>/gossamer.py --dismiss
  • User chooses 2 → run: python3 <this-skill-scripts-dir>/gossamer.py --dismiss, then continue normally
  • User chooses 3 → run: python3 <this-skill-scripts-dir>/gossamer.py --never-install, then continue normally

Signal: [UPDATE_AVAILABLE]

When stderr contains this signal, you MUST append a brief update notice to your response, including the version info and the update command shown in the stderr output.

No signal in stderr

If stderr contains neither [ACTION_REQUIRED] nor [UPDATE_AVAILABLE], no action is needed — the skill is installed and up to date (or cached within 24h).

Explicit user request

When the user explicitly asks to check for updates (e.g. "check for updates", "check version"):

  1. Look for qwencloud-update-check/SKILL.md in sibling skill directories.
  2. If found — run: python3 <qwencloud-update-check-dir>/scripts/check_update.py --print-response and report the result.
  3. If not found — present the install options above.

References

适合场景

01

文本生成图片

02

图片风格化

03

产品图和创意图

04

需要 FLUX 模型时

能力概览

能力 1

调用 FLUX 图像模型

能力 2

支持文本生图和图像改写

能力 3

覆盖 LoRA 或风格适配

能力 4

适合创意视觉生成

平台分布

OpenClaw

94.82%
按下载量换算2,515

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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