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Claude Code Vision Skill
为 Claude Code 赋能多模态视觉能力,支持豆包、通义千问、GPT-4o 等模型,用于截图 / UI / 图表分析;适配 DeepSeek 等无视觉底座,搭配 browser-harness 可做前端布局自动化检查。
Übersicht
A reusable skill for Claude Code that adds multimodal vision capabilities for analyzing screenshots, UI, and charts using various models.
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Claude Code Vision Skill
为 Claude Code 提供多模态视觉能力,支持多种视觉模型分析截图、UI、图表。
专为使用 DeepSeek 等无多模态能力的模型作为 Claude Code 底座的用户设计。
截图直贴,所见即所析
遇到 UI 报错、设计稿或数据图表?直接 alt + v 截图粘贴到 Claude Code 对话中,自动调用视觉模型分析。无需记住任何命令,像聊天一样自然。
串联工具链,自动 UI 审查
配合 browser-harness 等工具,可实现自动截图 → AI 视觉分析 → 生成审查报告 → 修正页面的完整闭环。前端页面渲染后自动截图,由视觉模型检查布局、样式和交互问题。
支持的模型
| Provider | 模型 | API Key 环境变量 |
|---|---|---|
| 豆包 (Doubao) | doubao-seed-2-0-pro-260215 | DOUBAO_API_KEY |
| 通义千问 (Qwen) | qwen-vl-max | DASHSCOPE_API_KEY |
| OpenAI | gpt-4o | OPENAI_API_KEY |
| Claude (Anthropic) | claude-sonnet-5 | ANTHROPIC_API_KEY |
| 任意自定义 provider | 任意 | {NAME}_API_KEY |
不在上面四个内置厂商里的 --provider 名字,会按同一套命名约定动态解析:设置
{NAME}_API_KEY / {NAME}_BASE_URL / {NAME}_MODEL({NAME}_PROTOCOL 可选,
默认 openai,需要 Anthropic Messages API 形状时设为 anthropic),无需改一行代码即可接入任意 OpenAI 兼容端点(vLLM、Ollama、LiteLLM、OpenRouter、Azure OpenAI、自建代理等)。详见 vision/SKILL.md。
安装依赖
需要 Python 3.10+。
pip install -r requirements.txt
anthropic 包仅在使用 --provider anthropic 时才会被导入,其他 provider 不受影响。
Claude Code 安装流程(给 Claude Code 看的指令)
When the user asks you to install this skill, follow these steps IN ORDER. Do NOT skip any step.
Step 1 — 询问用户
使用 AskUserQuestion 询问以下信息:
- 选择 provider:doubao / qwen / openai / anthropic / 自定义(可多选;自定义需额外要 base URL、model,可选 protocol)
- API Key:每个 provider 的 API key
- 默认 provider(多选时):选哪个作为默认
Step 2 — 运行安装脚本
python install.py \
--api-key qwen:sk-xxx \
--default-provider qwen \
--merge-claude
--api-key 可重复,--merge-claude 必须带上。
如果用户选了自定义 provider,额外带上 --base-url / --model(--protocol 可选,默认 openai):
python install.py \
--api-key myapi:sk-xxx \
--base-url myapi:https://host/v1 \
--model myapi:my-vision-model \
--default-provider myapi \
--merge-claude
Step 3 — 合并 CLAUDE.md(如果 install.py 未自动完成)
如果未使用 `--merge-cla
Originaltext anzeigen
# Claude Code Vision Skill
为 Claude Code 提供多模态视觉能力,支持多种视觉模型分析截图、UI、图表。
专为使用 DeepSeek 等无多模态能力的模型作为 Claude Code 底座的用户设计。
## 截图直贴,所见即所析
遇到 UI 报错、设计稿或数据图表?**直接 alt + v 截图粘贴到 Claude Code 对话中,自动调用视觉模型分析**。无需记住任何命令,像聊天一样自然。
## 串联工具链,自动 UI 审查
配合 **browser-harness** 等工具,可实现**自动截图 → AI 视觉分析 → 生成审查报告 → 修正页面**的完整闭环。前端页面渲染后自动截图,由视觉模型检查布局、样式和交互问题。
## 支持的模型
| Provider | 模型 | API Key 环境变量 |
|----------|------|-----------------|
| 豆包 (Doubao) | doubao-seed-2-0-pro-260215 | `DOUBAO_API_KEY` |
| 通义千问 (Qwen) | qwen-vl-max | `DASHSCOPE_API_KEY` |
| OpenAI | gpt-4o | `OPENAI_API_KEY` |
| Claude (Anthropic) | claude-sonnet-5 | `ANTHROPIC_API_KEY` |
| **任意自定义 provider** | 任意 | `{NAME}_API_KEY` |
不在上面四个内置厂商里的 `--provider` 名字,会按同一套命名约定动态解析:设置
`{NAME}_API_KEY` / `{NAME}_BASE_URL` / `{NAME}_MODEL`(`{NAME}_PROTOCOL` 可选,
默认 `openai`,需要 Anthropic Messages API 形状时设为 `anthropic`),无需改一行代码即可接入任意 OpenAI 兼容端点(vLLM、Ollama、LiteLLM、OpenRouter、Azure OpenAI、自建代理等)。详见 [vision/SKILL.md](vision/SKILL.md#any-custom-provider)。
## 安装依赖
需要 Python 3.10+。
```bash
pip install -r requirements.txt
```
`anthropic` 包仅在使用 `--provider anthropic` 时才会被导入,其他 provider 不受影响。
---
## Claude Code 安装流程(给 Claude Code 看的指令)
> **When the user asks you to install this skill, follow these steps IN ORDER. Do NOT skip any step.**
### Step 1 — 询问用户
使用 AskUserQuestion 询问以下信息:
1. **选择 provider**:doubao / qwen / openai / anthropic / 自定义(可多选;自定义需额外要 base URL、model,可选 protocol)
2. **API Key**:每个 provider 的 API key
3. **默认 provider**(多选时):选哪个作为默认
### Step 2 — 运行安装脚本
```bash
python install.py \
--api-key qwen:sk-xxx \
--default-provider qwen \
--merge-claude
```
`--api-key` 可重复,`--merge-claude` **必须带上**。
如果用户选了自定义 provider,额外带上 `--base-url` / `--model`(`--protocol` 可选,默认 openai):
```bash
python install.py \
--api-key myapi:sk-xxx \
--base-url myapi:https://host/v1 \
--model myapi:my-vision-model \
--default-provider myapi \
--merge-claude
```
### Step 3 — 合并 CLAUDE.md(如果 install.py 未自动完成)
如果未使用 `--merge-claQuelle prüfen
Preis und Betriebskosten
- Skill beziehen
- Preis unbestätigt
- Ausführen
- Anforderungen unbestätigt. Agenten-, API- und Dienstkosten an der Quelle prüfen.
- Lizenz
- MIT
- Preis unbestätigt
- Der Preis ist noch nicht bestätigt. Vorhandene Quell- und Installationslinks bleiben verfügbar.
Kostenloser Bezug bedeutet nicht kostenlosen Betrieb. Preise sind keine Sicherheitsbewertung. Preisinformation einreichen →
Quellstruktur ungeprüft
Ein gelistetes Repository beweist keinen installierbaren Skill. Prüfe zuerst die Anleitungen.
Vor Installation prüfen: Automatische Installation vermeiden
Lizenz: MIT
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 92 GitHub stars
- Stars/forks activity: 92 stars, 5 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
Tools sind Metadatenhinweise, keine getestete Kompatibilität. Prompts sind Vorschläge.
Mit einer kleinen Aufgabe beginnen
- 1Quelle lesen und Eingaben, Ergebnisse, Abhängigkeiten sowie Berechtigungen prüfen.
- 2Agent um einen Plan bitten. Einrichtung und Kosten vor einem isolierten Test genehmigen.
- 3Ergebnisse und geänderte Dateien prüfen. Nur tatsächliche Ausführungen melden und die Quellrevision aufbewahren.
Prüfe Abhängigkeiten, API-Schlüssel und externe Kosten in der Quelle. Öffentliche Repositories bedeuten nicht, dass alle Dienste kostenlos sind.
Quelle und Nutzungshinweise
Metadaten und Prüfungen dienen der Orientierung. Beliebtheit, Quellenerfassung und erfolgreiche Ausführung sind verschiedene Fakten.
- Quell-Repository
- xiincs/claude-code-vision-skill
- Lizenz
- MIT
- Version
- 1.0.0
- Letzter GitHub-Push
- 31. Juli 2026
- Verzeichnis aktualisiert
- 1. Sept. 2026
- Anleitungspfad
- Quellstruktur ungeprüft
Version aus den Verzeichnismetadaten; Releases der Quelle prüfen.
Qualität
74/100
Stark
Vertrauen
62/100
Nur Sandbox
Audit
77/100
Prüfung nötig
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution
- GitHub adoption: 92 GitHub stars
- Stars/forks activity: 92 stars, 5 forks; issue activity unavailable in current metadata
- Dependency/runtime risk: command execution surface, credential or environment access
- Permission surface: secrets or environment access, shell or command execution
- Verified installs
- —
- Ergebnisse
- —
Kopieren ist keine Installation. Zahlen benötigen eine Erfolgsmeldung und garantieren keine allgemeine Qualität.
Agent-Zugang
Die Registry API stellt Entscheidungs-, Vertrauens-, Audit-, Use-Case- und Installationssignale ohne UI-Scraping bereit.
Weitere Details
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"notice": "Publication, static checks, AI review, and creator verification are independent facts. None guarantees runtime safety."
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"skill": {
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"Dependency/runtime risk: command execution surface, credential or environment access",
"Permission surface: secrets or environment access, shell or command execution"
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}Für Ersteller
Quelle des Eintrags
Community-indexiert
Dieser Eintrag wurde aus öffentlichen Quellen indexiert und ist erst nach Genehmigung eines Maintainer-Anspruchs offiziell.
- Ersteller
- xiincs
- Indexiert von
- OpenAgentSkill Community-Index
Die Zuordnung verlinkt auf das öffentliche Repository oder Creator-Profil. Creator können den Eintrag beanspruchen, um Eigentümersignale zu aktualisieren.
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Zeige den kanonischen Eintrag, aktuelle Vertrauens- und Audit-Signale sowie echte Agent-Proven-Evidenz dort, wo Entwickler das Repository bewerten.
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[](https://www.openagentskill.com/skills/xiincs-claude-code-vision-skill?ref=github&utm_source=github&utm_medium=referral&utm_campaign=creator_badge)Community-Signal
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