Protocol Deviation Classifier

Determine whether an incident in a clinical trial is a "major deviation" or "minor deviation". Function: Automatically classify protocol deviations in clinic...

This skill appears internally consistent and runs locally without requesting credentials or remote installs, but before using it on real clinical data: (1) review the full scripts/main.py file (the provided file was truncated in the listing) to ensure there are no hidden network calls or subprocess invocations, (2) test the classifier on known examples and perform clinical/regulatory review—do not rely solely on automated outputs for regulatory decisions, (3) avoid sending personally identifiable or protected health information to unfamiliar environments; run the tool in a controlled environment or sanitize inputs, and (4) if you plan to integrate this into workflows, add logging, auditing, and human review gates to meet GCP/regulatory requirements.

Type: OpenClaw Skill Name: protocol-deviation-classifier Version: 0.1.0 The protocol-deviation-classifier skill bundle is a legitimate tool designed for clinical trial quality management. The core logic in `scripts/main.py` uses rule-based scoring and regular expressions to classify protocol deviations according to GCP/ICH E6 standards. The code relies solely on the Python standard library, contains no network requests, and performs no suspicious file system operations or command executions. The documentation in `SKILL.md` is well-structured and lacks any instructions that could be interpreted as prompt injection or malicious intent.