yolo-vision-tools

What to consider before installing/using: - Review code: The repository includes scripts that run shell commands and probe the filesystem (searching for other Python interpreters and cached models). This is expected for an environment checker but read the scripts if you want reassurance. - Run in an isolated environment: Use a disposable VM or dedicated virtualenv/conda environment if you are worried about exposing environment details or interfering with system Python installs. - No secrets requested: The skill does not ask for API keys or credentials. Still, the scripts can reveal local paths, installed package versions, and GPU details — treat that information as potentially sensitive on shared machines. - Network behavior: SKILL.md examples show loading images from URLs and installing ultralytics with pip; when you run the skill, it may download models or fetch remote images if you pass URLs. Only use trusted model/image URLs. - Subprocess/shell usage: The check script uses subprocess.run with shell execution and executes other python interpreters to check for ultralytics. This is normal for a diagnostic tool but increases what the script can inspect. Avoid running it on systems where arbitrary command output must remain private. - Mitigations: Inspect/modify scripts to remove any checks you don't want, run them with restricted permissions, or run only the functions you trust. Prefer running 'pip install -U ultralytics' yourself and invoking well-known commands (yolo checks) rather than running every diagnostic script unmodified. If you want, I can point out the specific lines that probe your home directory, check other python interpreters, or execute shell commands so you can audit them more easily.