blader/humanizer: the 33-pattern skill that rewrites AI tells out of your text

23,500 stars. One file. No API calls. The entire contract is a single 621-line SKILL.md that teaches Claude Code (and OpenCode) to detect and rewrite 33 specific patterns that mark a piece of writing as machine-generated. Today it hit GitHub's trending list — here's what it actually does, how to wire it in, and where it falls short.

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What the skill does — mechanically

Most "humanizer" tools are blunt instruments: swap "utilize" for "use," delete adverbs, call it done. blader/humanizer takes a different approach. Its pattern catalog comes directly from Wikipedia's Signs of AI writing guide, maintained by WikiProject AI Cleanup after analyzing thousands of real AI-generated text samples. 1

The skill targets five categories of tells:

Content patterns (#1–6) — inflating importance ("pivotal moment in the evolution of..."), name-dropping credentials, promotional language ("nestled within the breathtaking region")
Language patterns (#7–13) — the AI vocabulary blacklist (additionally, crucial, delve, landscape, testament, vibrant, underscore), copula avoidance ("serves as" instead of "is"), the rule of three
Style patterns (#14–19, #26–33) — em dash overuse (treated as a hard constraint, not a "use sparingly" note), curly quotes, excessive bolding, sentence fragments for fake impact ("It had no preference. No prior. No nostalgia.")
Chatbot artifacts (#20–22) — "I hope this helps! Let me know if..." endings, truncation disclaimers, sycophantic openers
Filler and hedging (#23–25) — "It is important to note that," over-qualified statements, generic conclusions

Version v2.8.0 (current) added three patterns in the last update: #31 manufactured punchlines, #32 aphorism formulas, and #33 rhetorical dialogue openers. 1

The processing model runs two passes. First pass: apply the 33 rules and produce a draft rewrite. Second pass: the skill self-audits — "What makes this still obviously AI-generated?" — lists any residual tells, then produces the final output. 1

One nuance worth noting from the SKILL.md detection guide: the skill looks for clusters, not isolated signals. As the skill itself puts it:

"A single em dash means nothing; em dashes plus rule-of-three plus vibrant tapestry plus a 'Conclusion' section is a confession." 1

Ecosystem support and install

Officially supported: Claude Code, OpenCode. The SKILL.md frontmatter explicitly lists compatibility: claude-code opencode — Cursor and Cline are claimed by third-party aggregators but not confirmed in the repo itself. 1

Claude Code:

mkdir -p ~/.claude/skills && git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer

OpenCode (or both at once — OpenCode also scans ~/.claude/skills/):

mkdir -p ~/.config/opencode/skills && git clone https://github.com/blader/humanizer.git ~/.config/opencode/skills/humanizer

Via skills.sh ecosystem:

npx -y skills add blader/humanizer --skill humanizer --agent claude-code

No compile step, no dependency tree, no binary. Drop the directory and whichever runtime picks it up will start using it immediately. 2

Usage examples

Basic invocation — paste the AI-generated text directly:

/humanizer The company has established itself as a pivotal player in the vibrant
landscape of enterprise software, leveraging its testament-to-innovation approach
to deliver cutting-edge solutions that underscore its commitment to excellence.

Expected output removes the flagged patterns and returns something closer to: "The company sells enterprise software. Its main product line focuses on..."

Voice calibration — this is the feature that actually differentiates the skill from generic rewriters. Paste 2–3 paragraphs of your own writing before the target text:

/humanizer Here's a sample of my writing for voice matching:
[paste 2-3 paragraphs of your own prose]

Now humanize this:
[paste the AI-generated text]

The skill analyzes six dimensions of your sample: sentence length distribution, vocabulary register, paragraph opening patterns, punctuation habits, recurring phrases, and transition style. It then applies those patterns to the rewrite rather than defaulting to a generic "clean" baseline. One explicit rule in the SKILL.md: if your sample uses "stuff" and "things," the output keeps "stuff" and "things" — it does not upgrade them to "elements" and "components." 1

The author's framing on voice calibration is direct:

"Voice calibration is a downgrade by default, not an upgrade. The model wants to make everything more formal. The skill tells it not to." 1

Community signals

The repo crossed 23,500 stars as of today — roughly 3.5× growth from about 6,600 in February 2026, and 1,100 installs recorded on Claude Marketplaces since it was listed on May 16. 3 4

Nous Research bundled a fork (v2.5.1) as a built-in skill in their Hermes Agent, crediting the author as Siqi Chen. 5

On Reddit's r/ClaudeCode, user quang-vybe — who built their own equivalent skill — still pointed people to blader's version:

"https://github.com/blader/humanizer - best out there IMO, mine is a simpler version of that one" 6

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The community has also started merging humanizer with other writing skills rather than treating them as alternatives. Julz7727's Stop-Slop-v3 integrated humanizer's Wikipedia pattern catalog directly into the stop-slop-v2 editorial layer. 7 A separate project by apurvrdx1 ("Tagore") merged both into a six-stage pipeline with eight evaluation dimensions. 8

Honest limitations

English only. A request for Spanish support (Issue #138, June 2, 2026) received no response and there's no localization in progress. 9

It will not fool AI detectors. A Reddit user tested the output with GPTZero and reported 100% AI-generated detection. This is expected behavior — the skill was designed to make writing read more naturally to humans, not to defeat classifier-based tools. 10

Sterile output without voice calibration. Dann Waniéri (dev.to) put the core problem plainly:

"Humanizer checks your writing against a generic human baseline. It knows what AI writing looks like and flags the patterns... I can write a draft that passes every humanizer check and still sounds nothing like my published work. No AI tells, no voice. Sterile, voiceless prose is as detectable as slop — it just gets detected by different readers." 11

He went on to build voice-humanizer, which adds a CORPUS.md file for personal writing fingerprinting and checks voice first before applying pattern detection.

False positives on deliberate style choices. Waniéri also flagged that his own occasional em dash use gets flagged — because the skill treats em dashes as a hard constraint, not a signal to weigh contextually. If you use em dashes by choice, the skill will remove them regardless.

Zero maintainer responsiveness on GitHub Issues. Of the open issues checked — including a detailed 956-line npx installer proposal (Issue #105, sitting for 6+ weeks), a download-freeze bug (Issue #104), and multiple feature requests — none have received a maintainer response, assignment, or label. 12 13 Code commits remain active (last change 2 days ago), but issues go unanswered.

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When NOT to use this skill

Non-English copy — the pattern catalog is English-specific and will misfire on Spanish, French, or other languages
Technical documentation — many of the flagged patterns (structured headers, cautious hedging, numbered lists) are conventions in docs, not AI tells. The skill will over-correct
Writing that already has a distinct voice — if your draft sounds like you, running it through humanizer without voice calibration risks stripping that out and replacing it with a generic "clean" baseline
Detector bypass — if your goal is specifically to pass GPTZero or Turnitin, this skill does not do that and the author has not claimed it does

The skill's own framing is useful here:

"Avoiding AI patterns is only half the job. Sterile, voiceless writing is just as obvious as slop. Good writing has a human behind it." 1

That holds whether you're running the skill or skipping it.

Install: git clone https://github.com/blader/humanizer.git ~/.claude/skills/humanizer 2 License: MIT · Author: Siqi Chen (blader) · Version: v2.8.0 · Stars: ~23,500

Cover image: AI-generated illustration

blader/humanizer: the 33-pattern skill that rewrites AI tells out of your text

What the skill does — mechanically

Ecosystem support and install

Usage examples

Community signals

Honest limitations

When NOT to use this skill

참고 출처