The open-source skill that makes AI text undetectable.
Drop-in Claude Code skill • 30 AI patterns • 5 voice profiles • Zero dependencies
"AI detectors don't catch good writing. They catch lazy writing."
Most "humanizers" swap words. This one rewrites with a pulse. It injects the burstiness, perplexity, and voice that make text read like a thinking human wrote it.
Built from 90+ research sources including Wikipedia's Signs of AI Writing, academic papers from NeurIPS/ICLR/ACL 2024, the Washington Post's 328,744-message ChatGPT analysis, and battle-tested techniques from Reddit, HackerNews, and professional editorial firms.
Every AI detector measures the same things:
| Signal | Human | AI | What it means |
|---|---|---|---|
| Perplexity | >85 (surprising words) | <85 (predictable) | AI picks the most likely next word. Humans don't. |
| Burstiness | HIGH (3-word sentence, then 40) | LOW (every sentence ~18 words) | AI writes in monotone rhythm. |
| Type-Token Ratio | 55.3 (diverse vocab) | 45.5 (repetitive) | AI recycles the same words. |
Word-swapping tools don't fix these. You need structural transformation. That's what this does.
Tip
The skill is a single file. No config, no setup, no dependencies. Claude Code picks it up automatically.
Option 1: Project-scoped (recommended, travels with your repo):
git clone https://github.com/Aboudjem/humanizer-skill.git
cp -r humanizer-skill/skills/humanizer .claude/skills/
rm -rf humanizer-skillOption 2: Global (available in every project):
mkdir -p ~/.claude/skills/humanizer
curl -sL https://raw.githubusercontent.com/Aboudjem/humanizer-skill/main/skills/humanizer/SKILL.md \
-o ~/.claude/skills/humanizer/SKILL.mdOption 3: Inside an existing plugin:
cp -r skills/humanizer /path/to/your-plugin/skills/Note
Claude Code detects skills in .claude/skills/, ~/.claude/skills/, or any plugin's skills/ directory. No restart needed.
# Rewrite AI-sounding text (default)
/humanizer "Your AI-generated text here"
# Scan for AI patterns without changing anything
/humanizer "text" --mode detect
# Edit a file in place
/humanizer --mode edit --file docs/blog-post.md
# Pick a voice
/humanizer "text" --voice casual
/humanizer "text" --voice blunt --aggressive
Before: This comprehensive guide delves into the intricacies of our authentication system. The platform leverages cutting-edge JWT technology to provide a seamless, secure, and robust authentication experience. Additionally, it features a pivotal role-based access control system that serves as a testament to our commitment to security.
After (
--voice technical): The auth system uses JWTs. Tokens expire after 15 minutes; refresh tokens last 7 days. Role-based access control restricts API endpoints by user role: admin, editor, and viewer each see different data. The token rotation logic is insrc/auth/refresh.tsif you need to change the expiry windows.
Killed 9 AI patterns. Added real details. Cut word count by 40%.
Before: In today's rapidly evolving technological landscape, artificial intelligence is reshaping how we think about creativity. This groundbreaking shift represents a pivotal moment in human history, one that underscores the intricate interplay between innovation and artistic expression.
After (
--voice casual): I've been messing around with AI image generators for about six months now, and I still can't decide if I love them or if they make me uneasy. The outputs are technically impressive. I got a portrait last week that looked better than anything I could paint in a year. But there's something missing. It's like eating a perfect-looking meal that has no flavor.
Replaced abstract commentary with personal experience. Sentence lengths: 8, 31, 22, 4, 13 words. That's burstiness.
Before: Excited to announce that I've taken on a pivotal new role at TechCorp! This incredible opportunity represents a significant milestone in my professional journey. I'm deeply grateful to my amazing network for their unwavering support. #NewBeginnings #Innovation #Leadership #Grateful
After (
--voice professional): Started a new job at TechCorp this week. I'm leading their developer tools team, 12 engineers building internal tooling that currently serves about 400 developers. First week has been drinking from the firehose: new codebase, new faces, new coffee machine I can't figure out. Nervous and excited in roughly equal measure.
No emojis. No hashtags. Real details instead of "pivotal milestone." The coffee machine line is more human than any amount of gratitude signaling.
Input text
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v
[1. DETECT] ── Scan for 30 AI patterns across 5 categories
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[2. STRIP] ─── Remove significance inflation, AI vocabulary,
| filler phrases, chatbot artifacts
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[3. INJECT] ── Apply voice profile, burstiness variation,
| perplexity increase, soul injection
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[4. VERIFY] ── Sentence variance, blacklist words,
| parallel structure, "who wrote this?" test
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Output + change summary
| Mode | What it does | When to use |
|---|---|---|
rewrite |
Full transformation with voice injection | Content creation, blog posts, social media |
detect |
Scan-only report with pattern counts and severity | Auditing existing content, learning what to fix |
edit |
In-place file editing with minimal changes | Documentation cleanup, README polishing |
Important
rewrite is the default mode. You don't need to specify it.
| Voice | Personality | Best for |
|---|---|---|
casual |
Contractions, first person, fragments, "And" starters | Blog posts, social media, community docs |
professional |
Selective contractions, dry wit, concrete examples | Business comms, reports, formal docs |
technical |
Precise terms, code-like clarity, deadpan humor | API docs, READMEs, architecture docs |
warm |
"We/our" language, empathy, shorter paragraphs | Tutorials, onboarding, support content |
blunt |
Shortest sentences, no hedging, active voice only | Reviews, internal comms, direct feedback |
Content Patterns (P1-P8), the worst offenders
| # | Pattern | What to look for |
|---|---|---|
| P1 | Significance Inflation | "marking a pivotal moment", "is a testament to" |
| P2 | Notability Name-Dropping | "featured in", "active social media presence" |
| P3 | Superficial -ing Phrases | "highlighting", "ensuring", "fostering" |
| P4 | Promotional Language | "cutting-edge", "seamless", "world-class", "nestled" |
| P5 | Vague Attributions | "Experts argue", "Research suggests" (no citation) |
| P6 | Formulaic Challenges | "Despite challenges, continues to thrive" |
| P7 | AI Vocabulary | "delve", "leverage", "multifaceted", "tapestry" |
| P8 | Copula Avoidance | "serves as" instead of "is" |
Language & Style (P9-P18), structural tells
| # | Pattern | What to look for |
|---|---|---|
| P9 | Negative Parallelisms | "It's not just X, it's Y" |
| P10 | Rule of Three | Forced triads: "innovation, inspiration, and insights" |
| P11 | Synonym Cycling | "protagonist" then "main character" then "central figure" |
| P12 | False Ranges | "From X to Y" on non-spectrums |
| P13 | Em Dash Ban | Zero em dashes allowed, replace with commas/hyphens |
| P14 | Boldface Overuse | Bold on every noun, emoji headers |
| P15 | Structured List Syndrome | **Header:** description bullets for prose content |
| P16 | Title Case Headings | "Strategic Negotiations And Global Partnerships" |
| P17 | Typographic Tells | Curly quotes, consistent Oxford comma |
| P18 | Formal Register Overuse | "it should be noted that", "it is essential to" |
Communication (P19-P21), chatbot residue
| # | Pattern | What to look for |
|---|---|---|
| P19 | Chatbot Artifacts | "I hope this helps!", "Certainly!" |
| P20 | Knowledge-Cutoff Disclaimers | "As of [date]", "based on available information" |
| P21 | Sycophantic Tone | "Great question!", "That's an excellent point!" |
Filler & Hedging (P22-P30), dead weight
| # | Pattern | What to look for |
|---|---|---|
| P22 | Filler Phrases | "In order to", "Due to the fact that", "It's worth noting" |
| P23 | Excessive Hedging | "could potentially possibly" |
| P24 | Generic Conclusions | "The future looks bright", "poised for growth" |
| P25 | Hallucination Markers | Fabricated-feeling dates, phantom citations |
| P26 | Perfect/Error Alternation | Inconsistent quality = partial AI edit |
| P27 | Question-Format Titles | "What makes X unique?", "Why is Y important?" |
| P28 | Markdown Bleeding | **bold** in emails, Word docs, social posts |
| P29 | "Comprehensive Overview" | "This guide delves into...", "Let's dive in" |
| P30 | Uniform Sentence Length | Every sentence 15-25 words, no variation |
Note
Every technique in this skill is grounded in published research. No guesswork.
| Technique | Source | Finding |
|---|---|---|
| Burstiness injection | GPTZero1 | Human sentence length varies wildly. AI doesn't. |
| Perplexity increase | GPTZero1 | AI picks the most statistically likely next word. |
| Vocabulary diversity | SSRN stylometric study2 | Human TTR: 55.3 vs AI: 45.5 |
| Kill negative parallelism | Washington Post3 | "It's not X, it's Y" confirmed as #1 AI tell across 328K messages |
| Structural paraphrasing | RAID benchmark, ACL 20244 | Drops DetectGPT accuracy from 70.3% to 4.6% |
| Intrinsic dimension | NeurIPS 20235 | Human text ~9 dimensions vs AI ~7.5 |
| Feature | Humanizer | QuillBot | Undetectable.ai | Prompt hacks |
|---|---|---|---|---|
| Open source | Yes | No | No | N/A |
| Pattern detection | 30 | 0 | 0 | 0 |
| Voice profiles | 5 | 0 | 3 | Manual |
| Works offline | Yes | No | No | No |
| Burstiness injection | Yes | No | Partial | No |
| Works in English | Yes | Multi | Multi | Manual |
| File editing mode | Yes | No | No | No |
| Explains changes | Yes | No | No | No |
| Price | Free | $20/mo | $10/mo | Free |
your-project/
.claude/
skills/
humanizer/
SKILL.md # <- the entire skill, one file
Tip
The skill works in .claude/skills/ (project), ~/.claude/skills/ (global), or any plugin's skills/ directory.
Found a new AI pattern? Have a better fix? PRs welcome.
- Fork the repo
- Add your pattern to
SKILL.md(follow the P1-P30 format) - Include a before/after example
- Open a PR
See CONTRIBUTING.md for details.
Built from 90+ sources across academic research, editorial expertise, and community intelligence:
- Wikipedia: Signs of AI writing, 24 pattern categories with real examples
- Wikipedia FR: Identifier l'usage d'une IA generative, additional AI pattern research
- RAID Benchmark (ACL 2024), 6M+ generations, 12 detectors evaluated
- NeurIPS 2023, intrinsic dimension analysis (Tulchinskii et al.)
- Washington Post, 328,744 ChatGPT message analysis
- Stanford HAI, ESL false positive study
- Max Planck Institute, AI vocabulary frequency spikes
- Softaworks agent-toolkit humanizer by @blader
- William Strunk Jr., The Elements of Style
- Gary Provost, David Ogilvy, Ann Handley, professional writing craft
If this skill saved your writing from sounding like a chatbot, consider giving it a star.
It helps others find it.
Footnotes
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GPTZero detection methodology: perplexity and burstiness as core signals ↩ ↩2
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SSRN stylometric study comparing type-token ratios across human and AI corpora ↩
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Washington Post analysis of 328,744 ChatGPT messages identifying distinctive AI constructs ↩
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RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors (ACL 2024, 6M+ generations) ↩
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Tulchinskii et al., NeurIPS 2023: Intrinsic dimensionality estimation for AI text detection ↩