Sanger Chromatogram QA

Use sanger chromatogram qa for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.

This skill is coherent at a high level (Sanger QA + numpy + a script) but the implementation is incomplete and partly placeholder. Before installing or running: 1) Inspect scripts/main.py — it currently only implements a demo and does not parse AB1 files or perform mixed-signal detection. 2) Run python -m py_compile and python scripts/main.py --demo in an isolated/sandboxed environment to confirm behavior. 3) Do not run the script against sensitive data until it has proper AB1 parsing and input validation; add or verify input sanitization and path traversal protections if you or the integrator extend the script to accept file paths. 4) If you expect full QA functionality, request or implement the missing features (AB1 parsing, mixed-signal detection, configuration block, robust error handling) and an updated dependency list (e.g., biopython or abifpy) before trusting outputs. 5) If you need help assessing any code changes, have a developer or security reviewer audit the modifications.

Type: OpenClaw Skill Name: sanger-chromatogram-qa Version: 1.0.0 The skill bundle is a legitimate, albeit early-stage (draft), tool for Sanger sequencing quality assessment. The Python script (scripts/main.py) contains basic logic for calculating quality scores and identifying mutations using numpy, with no evidence of data exfiltration, malicious execution, or obfuscation. The SKILL.md instructions focus on structured execution and safety boundaries without any prompt-injection attempts.