Western Blot Quantifier

Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls.

This package appears incomplete or inconsistently packaged rather than obviously malicious, but it will likely fail if run as-is. Before installing or running it: 1) Inspect scripts/main.py locally — run python -m py_compile scripts/main.py and run the demo (--demo) in an isolated virtualenv to observe behavior. 2) Do not run this on sensitive systems or with production data; use an isolated environment. 3) Note the API mismatches: SKILL.md expects a WesternBlotQuantifier class and richer outputs, but the code defines WBQuantifier and a minimal CLI. 4) If you need the claimed features, request an updated package from the author or fix the package: align exported names in scripts/__init__.py, implement the missing classes/methods, and/or reduce the documentation to reflect actual functionality. 5) If you cannot validate these fixes, treat the skill as untrusted or incomplete and avoid using it on important data. If you want, provide me with the output of running the demo or py_compile errors and I can help identify exactly what to change.

Type: OpenClaw Skill Name: western-blot-quantifier-1 Version: 1.0.0 The skill bundle provides a legitimate utility for Western Blot image analysis and quantification. The core logic in `scripts/main.py` performs basic peak detection and intensity normalization using NumPy, and the documentation in `SKILL.md` is strictly task-oriented without any signs of prompt injection or malicious instructions. No indicators of data exfiltration, unauthorized network access, or suspicious execution patterns were found.