AI Trace Removal Batch Processor

Problem

Batch-generated marketing copy often sounds mechanical: first/second/finally, rigid triadic structures, official boilerplate, over-parallel phrasing, and flat tone. Rewriting each piece by hand is slow, and careless edits can damage lead hooks or WeChat IDs. This skill turns “removing AI traces” into a repeatable batch pipeline.

How It Works

It wraps humanizer to process complete copy. It reads industry configuration, receives all generated content, then detects five AI-style patterns per piece: written-formulaic phrasing, mechanical sentence patterns, official boilerplate, excessive parallelism, and low emotional variation. It then rewrites the batch with more natural spoken phrasing, emotional variation, and looser sentence structure while keeping protected lead hooks and WeChat IDs unchanged.
A second pass checks that no obvious AI patterns remain, protected phrases are intact, banned words are absent, and length stays within platform limits. If the humanizer call fails, protected terms are altered, or meaning drifts, the skill falls back to manual replacement, auto-restoration, or reverting the original and flagging it for human review.

Boundaries

Input must be complete copy; batch limit is 50 pieces; protected terms cannot be changed. It is best as the final polishing step in a content pipeline, not for generating new copy or for highly regulated content where automatic rewriting may introduce risk.