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humanizerlisted

Humanize text: strip AI-isms and add real voice. Improves genuine writing quality; does NOT reliably evade trained neural detectors (see Threat Model). TRIGGER when: user invokes "/humanize" or asks to "humanize", "remove AI writing patterns", "de-slop", "strip AI-isms", or make prose that reads as AI-generated sound natural and human. DO NOT TRIGGER when: user wants voice calibration in a specific author's style (use writing-voice skill), is writing code, generating commit messages, or producing technical documentation where voice is irrelevant.
DROOdotFOO/agent-skills · ★ 0 · AI & Automation · score 76
Install: claude install-skill DROOdotFOO/agent-skills
# Humanizer: Remove AI Writing Patterns Identify and remove signs of AI-generated text to make writing sound natural and human. Based on Wikipedia's "Signs of AI writing" guide (maintained by WikiProject AI Cleanup), derived from observations of thousands of AI-generated text instances. **Key insight:** LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely completion, which is how the telltale patterns below get baked in. ## What You Get - A catalog of 29 AI writing patterns (vocabulary, structure, punctuation, tone) with concrete before/after rewrites - An honest threat model: what humanizing reliably beats (readers, statistical detectors) and what it does not (trained neural detectors like Pangram 4) - Editing passes to strip AI-isms and restore genuine voice, cadence, and specificity - Guidance on when word-level rewriting is insufficient and provenance is the only real lever ## THREAT MODEL: what this skill can and cannot do Read this before you assume "humanized" means "undetectable." It does not. **This skill reliably beats:** human readers, and cheap statistical detectors (perplexity/burstiness tools like GPTZero-classic, DetectGPT). Removing the 29 patterns below genuinely makes writing better and harder for a person to flag. **This skill does NOT beat trained neural detectors.** The Pangram 4 Technical Report (arXiv:2607.27183, Glickenhaus et al.) evaluates a classifier at AUROC 0.9916 / 0.004% f