Image Annotation QC
Security checks across static analysis, malware telemetry, and agentic risk
Overview
This appears to be a local image-annotation quality-control tool that reads user-selected datasets and writes local reports, with no evidence of credential use, networking, or hidden destructive behavior.
Before installing, be aware that this tool reads local image/annotation folders and writes report artifacts. Use it on a copy or intended dataset, set a clear output directory, and install the Python dependencies from trusted sources.
Static analysis
No static analysis findings were reported for this release.
VirusTotal
VirusTotal findings are pending for this skill version.
Risk analysis
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
The tool will inspect local dataset files and create report files; accidental use on the wrong directory could process or overwrite local QC outputs.
The skill instructs use of a local Python script that reads user-selected image and annotation paths and can write results to a selected output directory.
python3 scripts/qc_tool.py -i <image_dir> -a <annotation_dir> ... -o ./my_report
Run it only against intended datasets and choose an explicit `--output` directory if you want to control where reports are written.
Installing unpinned packages can lead to different dependency versions being installed over time.
The documented installation uses third-party Python packages without pinned versions. These packages are expected for image and Excel report handling, but the installation source/version is not constrained.
pip install Pillow openpyxl
Install dependencies from a trusted package index, preferably in a virtual environment, and consider pinning versions for reproducibility.