China Id Photo
v1.2.1生成中国标准证件照。Use when the user needs to create an ID photo, passport photo, visa photo, or any standard photo with specific size and background color. Supports...
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by@tobewin
MIT-0
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LicenseMIT-0 · Free to use, modify, and redistribute. No attribution required.
Security Scan
OpenClaw
Benign
medium confidencePurpose & Capability
Name and description (generate Chinese ID photos) match the instructions: image processing with OpenCV, background removal, resizing and cropping to specified sizes. Required binary (python3) and Python libraries (rembg, pillow, opencv-python-headless) are appropriate for this task.
Instruction Scope
Instructions operate on a user-provided image path, create an output directory (uses OPENCLAW_WORKSPACE if set), and run an embedded Python script to process images. They do not instruct reading unrelated system files or transmitting results to external endpoints. One caveat: the skill claims 'completely local processing, no upload', but the rembg library often auto-downloads model weights from the network on first use unless a local model is provided — this means network activity may occur even though the script itself does not call remote APIs.
Install Mechanism
This is an instruction-only skill with no install spec. It tells the user to run 'pip install rembg pillow opencv-python-headless', which will fetch packages from PyPI (normal for Python tools). There is no download from unknown servers in the skill files, but the pip step and potential rembg model download imply network I/O and installation into the system Python environment unless the user uses a virtualenv.
Credentials
No environment variables or credentials are required. The only environment reference is OPENCLAW_WORKSPACE (optional) used to choose the output folder; that is proportionate to the task.
Persistence & Privilege
The skill is user-invocable and not always-enabled. It does not request persistent system-wide configuration changes or access to other skills' configs.
Assessment
This skill appears to do what it claims (local image processing to produce standard China ID photos). Before installing or running: 1) Run the pip installs inside a dedicated virtualenv to avoid modifying system Python packages. 2) Expect the rembg library to possibly download ML model weights the first time it runs — that involves network activity (no evidence the skill uploads user photos). 3) Confirm you are comfortable with images being written to the workspace/output directory (OPENCLAW_WORKSPACE or current directory). 4) If you need strict offline guarantees, verify rembg's model availability offline or use an explicitly offline background-removal model. 5) As always, avoid using highly sensitive identity images unless you trust the runtime environment.Like a lobster shell, security has layers — review code before you run it.
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License
MIT-0
Free to use, modify, and redistribute. No attribution required.
Runtime requirements
📷 Clawdis
Binspython3