beat-writer
Channel-agnostic writer for any piece of content that doesn't yet belong to a specific channel. Use when you have something to…
Anti-AI detection pass for any written text. Hard rules that strip the statistical fingerprints AI writing leaves behind — em-dash density, contrastive formula ("not X, it's Y"), nuclear phrases, copula inflation, sycophantic filler, uniform contractions, colon overuse, register
Claude Code
$ npx -y skills add travsteward/openwriter --skill anti-ai --agent claude-code
Codex
$ npx skills add travsteward/openwriter --skill anti-ai -a codex -y
Cursor
$ npx skills add travsteward/openwriter --skill anti-ai -a cursor -y
Gemini CLI
$ npx skills add travsteward/openwriter --skill anti-ai -a gemini-cli -y
GitHub Copilot
$ npx skills add travsteward/openwriter --skill anti-ai -a github-copilot -y
OpenCode
$ npx skills add travsteward/openwriter --skill anti-ai -a opencode -y
Windsurf
$ npx skills add travsteward/openwriter --skill anti-ai -a windsurf -y
name: anti-ai
description: |
Anti-AI detection pass for any written text. Hard rules that strip the
statistical fingerprints AI writing leaves behind — em-dash density,
contrastive formula ("not X, it's Y"), nuclear phrases, copula inflation,
sycophantic filler, uniform contractions, colon overuse, register
monotony. Two tiers: hard rules (always fix) and voice-gated checks
(verify against voice profile if present).
Use when: "/anti-ai", "anti-ai pass", "anti-ai check", "strip ai signals",
"does this sound like ai", "ai detection check", "humanize this",
"remove ai fingerprints".
metadata:
author: travsteward
version: "0.1.0"
license: MITTwo tiers. Tier 1 rules are **hard rules** — fix unconditionally, no voice profile override. These patterns are so statistically associated with AI that detectors flag them regardless of context. Tier 2 rules are **voice-gated** — check against the voice profile before fixing.
---
**Em-dashes — eliminate, then calibrate.** AI uses em-dashes at 5-10x human density. This is one of the strongest AI signals.
**Contrastive formula — never use.** These constructions are AI fingerprints:
Rewrite without the formula. State the point directly.
**Nuclear phrases — kill on sight.** These phrases are 100-900x more frequent in AI text than human text. No human writes them at this density:
**Copula avoidance — use simple verbs.** AI replaces "is" with "serves as", "has" with "boasts", "shows" with "underscores." This is a telltale pattern. Use the simple verb.
**Sycophantic filler — cut unconditionally.** "Interestingly", "It's worth noting", "Notably", "It is important to note that", "It's crucial to understand" — these are AI padding. Delete them. They add nothing.
**Contraction consistency — mix intentionally.** Uniform contraction use (100% contractions OR 100% expanded) is an AI signal. Real humans are inconsistent. Use "don't" in one sentence and "does not" three sentences later. The inconsistency IS the authenticity signal. Check the voice profile (if present) for specific guidance.
**Colon density — cap usage.** AI overuses colons. Cap at 1 per 400-500 words for long-form prose; short punchy formats (social posts, taglines) get zero. If a voice profile specifies a colon budget, use that instead.
**Register uniformity — break it.** AI maintains a single consistent register throughout. Real writing mixes formal vocabulary with casual asides, academic precision with colloquial reactions. Intentionally vary register within a piece. This is the "bidirectional sophistication" principle from empirical testing (GPTZero 100% → 3%).
---
These patterns are suspicious but may match the author's voice. Check the profile before fixing.
---
Re-read the complete output: 1. Count em-dashes. No profile: should be zero. With profile: does the count match the author's observed frequency? Convert any excess 2. Scan for any contrastive formula. Rewrite if found 3. Grep for nuclear phrases. Kill any survivors 4. Check contraction consistency. Are contractions mixed inconsistently (not 100% one way)? 5. Count colons. Within the frame's limit? 6. Check register variation. Is the tone monotonously consistent, or does it mix naturally? 7. Scan for cop
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