Writing Anti Ai

Based on Wikipedia's "Signs of AI writing" guide, this detects and rewrites seven categories of AI slop: inflated symbolism ("serves as a testament"), promotional language, vague attributions ("experts believe"), superficial -ing constructions, AI vocabulary ("delve", "leverage"), negative parallelisms ("it's not just X, it's Y"), and excessive conjunctive phrases. Works in both English and Chinese. The interesting part is it goes beyond pattern removal to address rhythm and voice, because sterile rewriting is just as obviously artificial. Includes scoring rubrics and before/after examples. Honestly, this is more useful as a checklist for catching your own AI-isms than as an automated fixer, since good humanization requires judgment about when to break the rules.

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skills.sh installs: 782
GitHub stars: 6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add galaxy-dawn/claude-scholar --skill writing-anti-ai --agent claude-code

Installs into .claude/skills of the current project.

Files

Writing Anti-AI

Remove AI-generated writing patterns from text to make it sound natural and human-written. Supports both English and Chinese.

When editing academic prose, check the active installed skills/ml-paper-writing/references/knowledge/paper-miner-writing-memory.md under the current client's skill home for relevant source-attributed writing examples. Use it only to guide natural structure and rhythm. Keep the author's meaning, evidence, and target venue constraints intact. If the memory is absent or irrelevant, continue with this skill's own pattern references.

Overview

This skill identifies and eliminates predictable AI writing patterns from prose, based on Wikipedia: Signs of AI writing, maintained by WikiProject AI Cleanup.

Core insight: LLMs use statistical algorithms to predict what should come next. The result tends toward the most statistically likely outcome that applies to the widest variety of cases—creating detectable patterns.