微信表情包制作工具

微信表情包制作工具。自动将六宫格、九宫格、十二宫格的原图裁剪并转换为符合微信表情包规范的格式（表情主图 240x240，聊天页图标 50x50）。

This skill appears to do what it claims, but take the following precautions before running: (1) Review requirements.txt (Pillow, rembg, onnxruntime) and consider installing in an isolated environment or container—run.sh creates a local .venv but pip will fetch packages from the internet. (2) If you enable --remove-bg, the rembg component may download ML model weights on first use; ensure you are comfortable with that network activity and have sufficient disk space. (3) The tool processes files you give it and writes output files to the chosen output directory—avoid passing sensitive images unless you intend to process them locally. (4) If you need stricter supply-chain guarantees, inspect the upstream PyPI packages or install dependencies from vetted sources. (5) There is no evidence of data exfiltration or secret access in the code, but if you are unsure, run the script in a sandbox or review the code yourself before use.

Type: OpenClaw Skill Name: wechat-sticker-maker Version: 1.0.0 The skill is designed to process images into WeChat stickers, including optional AI background removal using `rembg`. All code and documentation align with this stated purpose. The `run.sh` script safely sets up a virtual environment and installs dependencies from `requirements.txt`. The `make_stickers.py` script uses standard image processing and file system operations. While `rembg` downloads AI models, this is an expected and transparent behavior for its functionality, explicitly mentioned in `SKILL.md`. There is no evidence of malicious intent such as data exfiltration, backdoors, or prompt injection attempts against the agent to perform unauthorized actions. The dependencies listed in `requirements.txt` are legitimate libraries.