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Virtual Try On
作者
wangyang-youloft
· GitHub ↗
· v1.0.0
· MIT-0
148
总下载
0
收藏
0
当前安装
1
版本数
在 OpenClaw 中安装
/install virtual-try-on
功能描述
Convert clothing images into professional e-commerce photos by virtually dressing AI models with up to four garment images for online retail use.
安全使用建议
This skill will send any submitted image URLs and an API key to an external service (api.ngmob.com). Before installing or using it: (1) ask the author to declare the required env var (API_KEY) in the skill metadata and explain the key's required scope/permissions; (2) verify the service provenance (official homepage, company, support/contact info) and confirm api.ngmob.com is the legitimate endpoint; (3) avoid uploading private/sensitive images; use public or anonymized examples; (4) create a limited-scope API key (least privilege) and monitor its usage; (5) ask the author to document data retention, privacy, and whether images are stored or used to train models; and (6) prefer skills with consistent owner metadata and non-placeholder author fields. The current metadata inconsistencies (missing required credential declaration, no homepage, mismatched owner IDs/placeholder author) are the primary reasons for caution.
功能分析
Package: virtual-try-on (xpi)
Version: 1.0.0
Description: Transform clothing images into e-commerce product photos with AI models wearing the garments
The package is a declarative configuration for an AI-powered 'Virtual Try-On' workflow. It defines API endpoints, request structures, and polling mechanisms for interacting with the Pixify AI service (api.ngmob.com). It contains no executable code, shell scripts, or logic for exfiltrating sensitive data.
能力评估
Purpose & Capability
The skill description and SKILL.md describe an API-based virtual try-on service (api.ngmob.com), which reasonably requires an API key. However, the registry metadata declares no required environment variables or primary credential while the manifest and SKILL.md explicitly use Authorization: Bearer {{API_KEY}} / $API_KEY. Additionally there is no homepage/source and owner IDs/authorship are inconsistent (manifest/_meta/registry show mismatched or placeholder values), reducing provenance and trust.
Instruction Scope
Instructions are scoped to sending user-provided clothing image URLs to https://api.ngmob.com and polling for results — this matches the declared purpose. However the instructions require an API_KEY (curl examples) that is not declared elsewhere, and they will transmit user images to an external service (data exfiltration/privacy risk if images are sensitive). The skill does not document data retention, privacy, or what is sent beyond the image URLs.
Install Mechanism
This is an instruction-only skill with no install spec and no code files, so it does not write code to disk or download external binaries. That lowers installation risk.
Credentials
The manifest and SKILL.md expect an API key (Authorization: Bearer {{API_KEY}} / $API_KEY) but requires.env/primary credential fields are empty. This mismatch is problematic: the skill will fail or will silently rely on an implicitly provided key. The skill asks for a high-sensitivity secret (API_KEY) without declaring scope, usage, or least-privilege recommendations.
Persistence & Privilege
always is false and disable-model-invocation is not set; the skill does not request persistent system-wide privileges or modify other skills. There is no install-time persistence specified.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install virtual-try-on - 安装完成后，直接呼叫该 Skill 的名称或使用
/virtual-try-on触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
Initial release of the virtual-try-on skill:
- Transform up to 4 clothing images into AI-generated product photos on professional models.
- Uses the Pixify engine, combining garment analysis and model try-on generation.
- Ideal for fashion e-commerce, design visualization, and rapid catalog creation.
- Clearly outlined API usage with sample workflows and status polling.
- No dependency on upload order; workflow automatically combines garment components.
元数据
常见问题
Virtual Try On 是什么？
Convert clothing images into professional e-commerce photos by virtually dressing AI models with up to four garment images for online retail use. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 148 次。
如何安装 Virtual Try On？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install virtual-try-on」即可一键安装，无需额外配置。
Virtual Try On 是免费的吗？
是的，Virtual Try On 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Virtual Try On 支持哪些平台？
Virtual Try On 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Virtual Try On？
由 wangyang-youloft（@wangyang-youloft）开发并维护，当前版本 v1.0.0。
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