Reducing Aigc Detection

This is a structured system for reducing AI detection scores in academic papers. It analyzes reports from platforms like 维普, 知网, and Turnitin, then applies tiered rewriting strategies based on detection rates: structural changes for sections over 80%, targeted rewrites for 40-80%, surgical edits below that. The approach focuses on injecting variance (burstiness, sentence length variation,论证深度 curves) rather than simple synonym swaps, which the source correctly notes are ineffective. It preserves footnotes and formatting through careful docx manipulation. Worth noting it explicitly avoids humanizer tools since Turnitin can now detect them. The skill includes platform-specific tactics like prioritizing abstract rewrites for 维普's 1.8x weighting. Best for when you have a detection report and need systematic remediation, not one-off edits.

Install to Claude Code

npx -y skills add telagod/code-abyss --skill reducing-aigc-detection --agent claude-code