by 安全扫描
OpenClaw
可疑
medium confidenceThe skill's description promises a full multi‑modal labeling studio, but the provided files and runtime instructions are inconsistent (missing modules/scripts and unnecessary listed dependencies), so the package appears incomplete or misleading and deserves caution before installation.
评估建议
This package looks internally inconsistent rather than blatantly malicious: it promises a full multi‑modal 'labeling_studio' with many helper scripts and model integrations, but the archive only contains an image annotator script, a quality checker, example/test mocks, and a requirements.txt. Before installing or running anything:
- Don't pip install the requirements into your main environment. Use a disposable virtualenv or container to avoid pulling heavy packages unnecessarily.
- Inspect or ...详细分析 ▾
⚠ 用途与能力
The skill claims multi‑modal support (image, text, audio, video) and an importable package 'labeling_studio', but the bundle only includes scripts for image annotation and quality checks. Several scripts referenced in SKILL.md (annotate_text.py, annotate_audio.py, annotate_video.py, export_dataset.py) and the labeling_studio module used in examples are not present. Declared requirements (librosa, OpenCV, Pillow, scikit‑learn) are heavier than what the included scripts actually use.
⚠ 指令范围
SKILL.md instructs running scripts and doing pip install -r requirements.txt which is expected, but many example commands and APIs reference missing files/modules (labeling_studio import, scripts that aren't in the manifest). The runtime instructions also enable 'active learning' and 'pre_annotate' but the included code only contains mock/simulated behavior rather than actual model integration — this is scope creep / mismatch between promised capabilities and real instructions.
ℹ 安装机制
There is no formal install spec (instruction-only), which is low risk. However SKILL.md and README suggest running 'pip install -r requirements.txt' which will pull several heavy third‑party packages; because the project is incomplete, installing those deps may be unnecessary and should be done in an isolated environment if attempted.
✓ 凭证需求
The skill requests no environment variables, no credentials, and no config paths. The code reads only local file paths supplied by the user. There is no evidence of attempts to access unrelated secrets or network endpoints in the provided files.
✓ 持久化与权限
The skill is not always-enabled and does not request persistent system privileges or modify other skills. It does not include an installer that writes to system locations; it is run on demand as scripts.
安全有层次，运行前请审查代码。
运行时依赖
无特殊依赖
版本
latestv1.0.02026/4/17
Initial release of Data Labeling Studio. - Supports intelligent data labeling and annotation for images, text, audio, and video - Includes active learning suggestions and quality control checks - Multiple annotation formats supported: COCO, YOLO, Pascal VOC, TFRecord, HuggingFace, and more - Tools provided for annotation, quality checking, and dataset export - Example usage and script files included for all major features
● 无害
安装命令
点击复制官方npx clawhub@latest install data-labeling-studio
镜像加速npx clawhub@latest install data-labeling-studio --registry https://cn.longxiaskill.com 镜像可用