Western Blot Quantifier

Automatically identify Western Blot gel bands, perform densitometric analysis, and calculate normalized values relative to loading controls (GAPDH, β-actin,...

Do not install or run this skill in a production environment yet. The repository appears to be a draft: class and function names in SKILL.md/__init__.py do not match main.py, the documented API (analyze(), save(), CSV/figure output, CLI flags) is missing, and import errors will likely occur. Suggested next steps before trusting or using the skill: 1) Ask the author for a corrected release where exported names match implementation and the documented API/CLI are implemented. 2) Run the package in an isolated sandbox (e.g., ephemeral VM or container) to confirm there are no unexpected file/network operations. 3) Inspect and/or run unit tests that exercise real image input, CSV export, and plotting to verify behavior. 4) If you need to use it now, patch or extend main.py to implement the documented interface and add explicit file-path validation (prevent ../ traversal), then run on non-sensitive sample images first. The current inconsistencies look like incomplete packaging rather than deliberate malicious behavior, but do not proceed until fixed and reviewed.

Type: OpenClaw Skill Name: western-blot-quantifier Version: 0.1.0 The skill bundle is a benign tool for Western Blot image analysis. The code in scripts/main.py implements basic band detection and normalization logic using numpy without any risky system calls, network activity, or data exfiltration. The documentation in SKILL.md is consistent with the stated purpose and does not contain any prompt injection attempts or malicious instructions.