# Avoid AI Writing

Audit and rewrite content to remove AI writing patterns ("AI-isms").

- Repository: https://github.com/conorbronsdon/avoid-ai-writing (5364 stars)
- Category: Writing
- License: MIT
- Last updated: 2026-11-01
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add conorbronsdon/avoid-ai-writing --skill avoid-ai-writing -g -a claude-code -y`
Codex: `npx skills add conorbronsdon/avoid-ai-writing --skill avoid-ai-writing -g -a codex -y`
Cursor: `npx skills add conorbronsdon/avoid-ai-writing --skill avoid-ai-writing -g -a cursor -y`
Gemini CLI: `npx skills add conorbronsdon/avoid-ai-writing --skill avoid-ai-writing -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add conorbronsdon/avoid-ai-writing`

## Description

Audit and rewrite content to remove AI writing patterns ("AI-isms"). Use this skill when asked to "remove AI-isms," "clean up AI writing," "edit writing for AI patterns," "audit writing for AI tells," or "make this sound less like AI." Supports a detect-only mode, an edit-in-place mode for files, an optional voice profile (casual / professional / technical / warm / blunt), and an iterate-to-convergence pass.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# Avoid AI Writing, Audit & Rewrite

You are editing content to remove AI writing patterns ("AI-isms") that make text sound machine-generated.

## What this skill is and isn't

These rules and the project's detector are calibrated for English; applying them to another language requires language-specific rules and evidence.

This is a **writing-quality tool**, not a verdict. The patterns flagged here are statistically more common in LLM output, but humans on autopilot, especially writing under deadline pressure, in unfamiliar genres, or in a second language, produce the same shapes. Independent audits of commercial AI detectors have found false-positive rates above 60% on non-native English writers (Liang et al., Stanford, *Patterns* 2023) and overall misclassification rates above 70% on open-source detectors (Jabarian & Imas, BFI Working Paper 2025-116, 2025). Adversarial paraphrase reduces detection accuracy by ~88% across every method tested (arXiv:2506.07001, 2025).

The patterns are useful as a signal, both for cleaning up your own writing and for assessing whether a piece reads as AI-generated. Just don't make them the sole basis for a consequential decision (academic integrity, hiring, publication, attribution). Several rules here also fire on second-language writing, deadline-pressed humans, and technical genres that compress vocabulary by design. Pair the signal with context: who wrote it, what genre, what the writer's normal voice looks like, what other evidence you have.

In short: signals, not proof. Worth acting on; not worth ruining someone's day over.

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Before auditing or rewriting any text, read [references/patterns.md](references/patterns.md) in full. It contains the word tiers, pattern catalog, and context/voice profiles. These rules and their exceptions are required for quick passes as well as full audits. Resolve bundled command and example paths from this skill directory.
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The rest: https://github.com/conorbronsdon/avoid-ai-writing/blob/HEAD//SKILL.md