humanizer

Technical documentation

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 in src/auth/refresh.ts if you need to change the expiry windows.

Killed 9 AI patterns. Added real details. Cut word count by 40%.

Blog post

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.

LinkedIn post

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.

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Voice profiles

Every voice changes how the skill rewrites. Not just what words it picks, but the sentence structure, rhythm, and personality it injects.

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

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How it works

A 4-pass editing system. Each pass has one job and never does the others.

graph LR
    A["Pass 1: Detect<br/><sub>Scan for 43 AI patterns<br/>across 5 categories</sub>"] --> B["Pass 2: Strip<br/><sub>Remove significance inflation,<br/>AI vocabulary, filler</sub>"]
    B --> C["Pass 3: Inject<br/><sub>Apply voice profile,<br/>burstiness, perplexity</sub>"]
    C --> D["Pass 4: Verify<br/><sub>Sentence variance check,<br/>blacklist scan, final test</sub>"]

    style A fill:#f5f3ff,stroke:#8b5cf6,color:#1e1b4b
    style B fill:#ede9fe,stroke:#8b5cf6,color:#1e1b4b
    style C fill:#ddd6fe,stroke:#8b5cf6,color:#1e1b4b
    style D fill:#8b5cf6,stroke:#7c3aed,color:#ffffff

Your text goes in. Clean, human-sounding writing comes out. The skill auto-detects which patterns are present and applies the minimum transformation needed. Pass 1 is non-destructive: you can run --mode detect to get the report without rewriting anything.

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The science

AI detectors don't use magic. They measure two things, and both are well-documented in published research.

Burstiness is sentence length variation. Humans write a 3-word sentence, then a 40-word one, then a 12-word one. AI writes every sentence at roughly 18 words. Detectors measure this variance. Low variance = probably AI.

Perplexity is word predictability. AI picks the most statistically likely next word every time. Humans don't. We use surprising words, odd phrasing, personal references. High perplexity = probably human.

Word-swapping tools like QuillBot change individual words but leave the rhythm and predictability untouched. That's why they fail. You need structural transformation, not synonym replacement.

Technique	Source	Finding
Burstiness injection	GPTZero	Human sentence length varies wildly. AI doesn't.
Perplexity increase	GPTZero	AI picks the most statistically likely next word.
Vocabulary diversity	SSRN stylometric study	Human TTR: 55.3 vs AI: 45.5
Kill negative parallelism	Washington Post	"It's not X, it's Y" confirmed as #1 AI tell across 328K messages
Structural paraphrasing	RAID benchmark, ACL 2024	Drops DetectGPT accuracy from 70.3% to 4.6%
Intrinsic dimension	NeurIPS 2023	Human text ~9 dimensions vs AI ~7.5

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vs. alternatives

Feature	Humanizer	QuillBot	Undetectable.ai	Manual editing
Open source	Yes	No	No	N/A
Pattern detection	43	0	0	0
Voice profiles	5	0	3	Manual
Works offline	Yes	No	No	Yes
Burstiness injection	Yes	No	Partial	No
File editing mode	Yes	No	No	No
Explains changes	Yes	No	No	No
Price	Free	$20/mo	$10/mo	Free

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All 43 patterns

<b>Content Patterns (P1-P8)</b>

#	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"

<b>Language and Style (P9-P18)</b>

#	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"

<b>Communication (P19-P21)</b>

#	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!"

<b>Filler and Hedging (P22-P30)</b>

#	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

<b>Emerging Patterns (P31-P43)</b>

#	Pattern	What to look for
P31	Elegant Variation	"the artist", "the visionary creator", "the non-conformist painter" for the same person
P32	Collaborative Communication Leaking	"In this article, we will explore", "Let me walk you through"
P33	Placeholder Text / Mad Libs	[Your Name], [INSERT SOURCE URL], unfilled brackets
P34	Chatbot Reference Markup Leaking	citeturn0search0, oai_citation, broken footnote refs
P35	UTM Source Parameters	utm_source=chatgpt.com, utm_source=openai in URLs
P36	Sudden Style/Register Shift	Formal prose suddenly switching to casual, or vice versa
P37	Overattribution	"Featured in Wired, Refinery29, and other outlets" without substance
P38	Paragraph-Reshuffling Immunity	Paragraphs that could swap order without breaking the argument
P39	"Whether" Paragraph Closers	"Whether you prefer X or Y, the answer is..." as a paragraph wrap-up
P40	Symbolic Gloss / Meaning-Telling	"represents", "symbolizes", "speaks to broader" applied to mundane things
P41	Infomercial Engagement Hooks	"The catch?", "The kicker?", "Here's the thing.", "The brutal truth?"
P42	Erratic Inline Bolding	Random mid-sentence bold spans with no shared logic or category
P43	The Treadmill Effect	"In other words", "Put simply", "Essentially" looping the same point

All P38-P43 are 2026 community discoveries sourced from HackerNews threads, Wikipedia's evolving editorial guideline, and writing practitioner blogs. Sources cited inline in SKILL.md.

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Why not just...

"...use a better prompt?" Prompts help, but they can't enforce 43 specific pattern rules consistently. The skill has a checklist. It catches things you'd miss on your 50th revision.

"...use QuillBot or Undetectable.ai?" They swap words. The rhythm stays robotic, the sentence lengths stay uniform, the structure stays predictable. Detectors don't care about individual words. They care about patterns.

"...just edit it myself?" You absolutely can. But do you know all 43 patterns? Can you spot "copula avoidance" or "significance inflation" on sight? This skill is a ruthless editor that never gets tired and never misses a pattern.

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Model compatibility

The skill is a Markdown prompt, so it runs on whichever model your editor wires up. Tested working on:

Model	Detection accuracy	Rewrite quality	Notes
Claude Opus 4.x	Highest	Highest	Best for --iterate convergence and --aggressive mode
Claude Sonnet 4.x	High	High	Recommended default for daily use
Claude Haiku 4.x	High	Medium	Fast, good for --mode detect audits
GPT-4.x / GPT-5	High	High	Works via Codex CLI integration
Gemini 2.x	Medium	High	Works via Gemini CLI integration
Local models (Llama, Qwen)	Varies	Varies	Use longer prompts and --aggressive

The patterns are model-agnostic. The voice profiles are model-agnostic. The only thing that varies is how creatively each model handles the "soul injection" step.

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Trust

No telemetry. No data collection. No API calls. No cloud anything.

The entire skill is a single Markdown file (SKILL.md) that Claude Code reads locally. Your text never leaves your machine. There's nothing to audit because there's nothing running.

Note: Pure markdown skill. No JavaScript, no binaries, no network requests. Read the source yourself: it's one file.

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File structure

your-project/
  .claude/
    skills/
      humanizer/
        SKILL.md    # the entire skill, one file

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Contributing

Found a new AI pattern? Have a better fix? PRs welcome.

1. Fork the repo
2. Add your pattern to SKILL.md (follow the P1-P43 format)
3. Include a before/after example
4. Open a PR

See CONTRIBUTING.md for details, including the three-file lockstep update (badge count, CI threshold, CHANGELOG).

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Lineage and credit

This skill is part of a wider family of humanizer tools. Direct lineage:

• @blader/humanizer, the original Claude skill that named this category. Different patterns, no voice profiles, no edit mode, but it lit the path.
• @softaworks/agent-toolkit, the humanizer plugin that proved Markdown skill files were the right distribution format.
• Wikipedia: Signs of AI writing, the public, open, citation-backed reference list that ~70% of P1-P30 are derived from.

What this fork adds: 43 numbered patterns (largest open catalog), 5 named voice profiles, three operating modes (detect/rewrite/edit), 8-editor install matrix, CI that enforces its own rules (no em dashes in the skill that bans em dashes), and a research-first README that cites primary sources for every claim.

If you used the older humanizers, this one will feel familiar but tighter. If you're new to the category, @blader's repo is also worth a read.

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<b>Research sources (90+)</b>

• 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
• GPTZero detection methodology (perplexity + burstiness)
• SSRN stylometric studies (type-token ratio analysis)
• ICLR 2024 watermarking and detection papers
• Reddit r/ChatGPT, r/ArtificialIntelligence community pattern discoveries
• HackerNews discussions on AI detection and writing quality
• Professional editorial firms' AI content guidelines

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If this skill saved your writing from sounding like a chatbot, consider giving it a star.

It helps others find it.

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_{Built by Adam Boudjemaa · MIT License · No telemetry · No data collection}