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Agent Skill · 研究检索

qwencloud-vision(qwencloud 视觉)

qwencloud-vision 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

qwencloud-vision 是研究检索类 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,按安装量在研究检索类的 73,675 个 Skill 里排第 24,178。

总安装 4,080周安装 170GitHub Stars 公开资料未说明下载 1,360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-vision(qwencloud 视觉)
来源仓库:https://github.com/cuixiaoyang123/qwencloud-vision
安装命令:
openclaw skills install qwencloud-vision
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-vision

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

使用 Qwen 视觉模型分析图像和视频内容,提取关键信息并生成结构化描述。适合在需要从视觉素材中识别对象、理解场景或辅助内容审核的任务中使用。支持对静态图片或视频帧进行语义解析,返回标签、位置和关系等元数据。涉及人物肖像或敏感信息时应注意隐私与版权边界,避免用于未授权分发。

安装命令:openclaw skills install qwencloud-vision

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-vision;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-vision 怎么安装?

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

qwencloud-vision 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-vision 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-vision 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-vision 用的人多吗?

公开数据是累计安装 4,080 次,近一周安装 170 次,下载 1,360 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-vision 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。
  • 需要处理研究检索类任务、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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
qwencloud-vision

qwencloud 视觉 · 本页

4,080—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-vision
description
[QwenCloud] Understand images and videos with Qwen vision models. TRIGGER when: user wants to analyze, describe, or extract information from images or videos, OCR text extraction, chart/table reading, visual reasoning, multi-image comparison, screenshot understanding, video comprehension, or explicitly invokes this skill by name (e.g. use qwencloud-vision). DO NOT TRIGGER when: user wants to generate/create images (use qwencloud-image-generation), generate videos (use qwencloud-video-generation), text-only tasks without visual input, or non-Qwen vision 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 Vision (Image & Video Understanding)

Analyze images and videos using Qwen VL and QVQ models. 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/analyze.pyImage/video understanding, multi-image, thinking mode
scripts/reason.pyVisual reasoning (QVQ, chain-of-thought, streaming)
scripts/ocr.pyOCR text extraction
scripts/vision_lib.pyShared helpers (base64, upload, streaming)
references/execution-guide.mdFallback: curl, code generation
references/curl-examples.mdCurl for base64, multi-image, video, OCR
references/visual-reasoning.mdQVQ and thinking mode details
references/prompt-guide.mdQuery prompt templates by task, thinking mode decision
references/ocr.mdOCR parameters and examples
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 for direct API calls and do not support dedicated vision models (qwen3-vl-plus, qvq-max, etc.). The scripts detect sk-sp- keys at startup and print a warning. If qwencloud-ops-auth is installed, see its references/codingplan.md for full details.

Model Selection

ModelUse Case
qwen3.6-plusPreferred — latest flagship, unified multimodal (text+image+video). Thinking on by default. Best balance of quality, speed, cost.
qwen3.5-plusUnified multimodal (text+image+video). Thinking on by default.
qwen3.5-flashFast multimodal — cheaper, faster. Thinking on by default.
qwen3-vl-plusHigh-precision — object localization (2D/3D), document/webpage parsing.
qwen3-vl-flashFast vision — lower latency, 33 languages.
qvq-maxVisual reasoning — chain-of-thought for math, charts. Streaming only.
qwen-vl-ocrOCR — text extraction, table parsing, document scanning.
qwen-vl-maxQwen2.5-VL — best-performing in 2.5 series.
qwen-vl-plusQwen2.5-VL — faster, good balance of performance and cost, 11 languages.
  1. User specified a model → use directly.
  2. Consult the qwencloud-model-selector skill when model choice depends on requirement, scenario, or pricing.
  3. No signal, clear task → qwen3.6-plus. Use qwen3-vl-plus for precise localization or 3D detection.
⚠️ 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. qwen3.6-plus → https://www.qwencloud.com/models/qwen3.6-plus). 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

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. Shared infrastructure lives in scripts/vision_lib.py.

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

Discovery: Run python3 <this-skill-dir>/scripts/analyze.py --help (or reason.py, ocr.py) first to see all available arguments.

ScriptPurposeDefault Model
scripts/analyze.pyImage understanding, multi-image, video, thinking mode, high-resqwen3.6-plus
scripts/reason.pyVisual reasoning with chain-of-thought, video reasoning (always streaming)qvq-max
scripts/ocr.pyOCR text extraction from documents, receipts, tablesqwen-vl-ocr

Input type fields (use exactly one in --request JSON):

FieldUse forExample
"image"Single image (URL or local path)"image": "photo.jpg"
"images"Multi-image comparison (array)"images": ["a.jpg", "b.jpg"]
"video"Video file (URL or local path)"video": "clip.mp4"
"video_frames"Video as frame array"video_frames": ["f1.jpg", "f2.jpg"]
⚠️ Common mistake: Do NOT use "image" for video files — use "video" instead.
# Image analysis
python3 <this-skill-dir>/scripts/analyze.py \
  --request '{"prompt":"What is in this image?","image":"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241022/emyrja/dog_and_girl.jpeg"}' \
  --output output/qwencloud-vision/result.json --print-response

# Video analysis (local file — add --upload-files for files >= 7 MB)
python3 <this-skill-dir>/scripts/analyze.py \
  --request '{"prompt":"Describe what happens in this video","video":"clip.mp4"}' \
  --upload-files --print-response

python3 <this-skill-dir>/scripts/reason.py \
  --request '{"prompt":"Solve this math problem step by step","image":"problem.png"}' \
  --print-response

python3 <this-skill-dir>/scripts/ocr.py \
  --request '{"image":"invoice.jpg"}' \
  --print-response
ArgumentDescription
--request '{...}'JSON request body
--file path.jsonLoad request from file
--output pathSave response JSON to path
--print-responsePrint response to stdout
--streamEnable streaming (auto for thinking/QVQ)
--upload-filesUpload local files to temp storage (for files > 7 MB)
--schema path.jsonJSON Schema for structured extraction

Verify Result

  • Exit code 0 + output contains valid JSON with choices field → success
  • Non-zero exit, HTTP error, empty response, or JSON with "code"/"message" error → fail
  • Post-execution check: When --output is used, verify the response JSON file exists and contains expected content
  • 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 scripts fail, 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), 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

File Input

The API accepts: HTTP/HTTPS URL, Base64 data URI, and oss:// URL. Local file paths are NOT directly supported — scripts handle conversion automatically. Pass local paths directly; no manual upload step needed.

Large file rule: If the local file is >= 7 MB, always add --upload-files. Base64 encoding inflates size by ~33% and will exceed the 10 MB API limit. Small files (including short video clips < 7 MB) can use the default base64 path.

MethodWhen to useHow
Online URLFile already hostedPass URL directly — preferred for large files
Base64 (default)Local files < 7 MB (images or short video clips)Script auto-converts to data: URI
Temp uploadLocal files >= 7 MBAdd --upload-files flag → uploads to DashScope temp storage (oss:// URL, 48h TTL)
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). The --upload-files flag is still required for vision scripts to trigger upload. If qwencloud-ops-auth is installed, see its references/custom-oss.md for the full setup guide.

Input from Other Skills

When the input file comes from another skill's output (e.g., image-gen, video-gen):

  • Pass the URL directly (e.g., "image": "<image_url from image-gen>") — do NOT download the URL first
  • Downloading and re-passing as a local path wastes bandwidth and triggers unnecessary base64 encoding or OSS upload
  • All URL types are supported: https://, oss://, data:

Thinking Mode

ModelThinking DefaultNotes
qwen3.6-plusOnLatest flagship. Disable with enable_thinking: false for simple tasks.
qwen3.5-plus / qwen3.5-flashOnDisable with enable_thinking: false for simple tasks.
qwen3-vl-plus / qwen3-vl-flashOffEnable with enable_thinking: true.
qvq-maxAlways onStreaming output required.

See visual-reasoning.md for details.

OCR (qwen-vl-ocr)

Optimized for text extraction. Supports multi-language, skewed images, tables, formulas. See ocr.md for parameters and examples.

Input Limits

Images: BMP/JPEG/PNG/TIFF/WEBP/HEIC. Min 10px sides, aspect ratio <= 200:1. Max 20 MB (URL, Qwen3.5) / 10 MB (others).

Videos: MP4/AVI/MKV/MOV/FLV/WMV. Duration 2s–2h (Qwen3.5) / 2s–10min (others). Max 2 GB (URL) / 10 MB (base64). fps range [0.1, 10], default 2.0.

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 format)Verify messages format and image URL/format
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-vision/.

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

平台分布

OpenClaw

91.99%
按下载量换算1,251

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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