humanizer

Humanizer

A portable agent skill that removes signs of AI-generated writing from text, making it sound more natural and human. It is plain Markdown, so it can run in any harness that supports skill-style instructions.

Installation

Skills CLI

Install with the cross-agent skills CLI:

npx skills add blader/humanizer

Update an existing install:

npx skills update humanizer

To install into every supported agent harness:

npx skills add blader/humanizer --agent '*'

To target one configured harness, pass its agent name:

npx skills add blader/humanizer --agent <agent-name>

Claude Code plugin

Claude Code users can also install Humanizer as a plugin:

/plugin marketplace add blader/humanizer
/plugin install humanizer@humanizer

The skill is then invoked as /humanizer:humanizer.

Manual

Any agent harness can use the skill directly because the runtime artifact is SKILL.md. Install it wherever your harness expects skill directories, or copy SKILL.md into an existing skill folder.

For example:

git clone https://github.com/blader/humanizer.git /path/to/your/skills/humanizer

Or, if you already have this repo cloned:

mkdir -p /path/to/your/skills/humanizer
cp SKILL.md /path/to/your/skills/humanizer/

Usage

Invoke the skill however your agent harness exposes installed skills. Common forms include a slash command or a direct request:

/humanizer

[paste your text here]

Please humanize this text: [your text]

Voice Calibration

To match your personal writing style, provide a sample of your own writing:

/humanizer

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

Now humanize this text:
[paste AI text to humanize]

The skill will analyze your sentence rhythm, word choices, and quirks, then apply them to the rewrite instead of producing generic "clean" output.

Overview

Based on Wikipedia's "Signs of AI writing" guide, maintained by WikiProject AI Cleanup. This comprehensive guide comes from observations of thousands of instances of AI-generated text.

The skill also includes a final "obviously AI generated" audit pass and a second rewrite, to catch lingering AI-isms in the first draft.

Key Insight from Wikipedia

"LLMs use statistical algorithms to guess what should come next. The result tends toward the most statistically likely result that applies to the widest variety of cases."

33 Patterns Detected (with Before/After Examples)

Content Patterns

#	Pattern	Before	After
1	Significance inflation	"marking a pivotal moment in the evolution of..."	"was established in 1989 to collect regional statistics"
2	Notability name-dropping	"cited in NYT, BBC, FT, and The Hindu"	"In a 2024 NYT interview, she argued..."
3	Superficial -ing analyses	"symbolizing... reflecting... showcasing..."	Remove or expand with actual sources
4	Promotional language	"nestled within the breathtaking region"	"is a town in the Gonder region"
5	Vague attributions	"Experts believe it plays a crucial role"	"according to a 2019 survey by..."
6	Formulaic challenges	"Despite challenges... continues to thrive"	Specific facts about actual challenges

Language Patterns

#	Pattern	Before	After
7	AI vocabulary	"Actually... additionally... testament... landscape... showcasing"	"also... remain common"
8	Copula avoidance	"serves as... features... boasts"	"is... has"
9	Negative parallelisms / tailing negations	"It's not just X, it's Y", "..., no guessing"	State the point directly
10	Rule of three	"innovation, inspiration, and insights"	Use natural number of items
11	Synonym cycling	"protagonist... main character... central figure... hero"	"protagonist" (repeat when clearest)
12	False ranges	"from the Big Bang to dark matter"	List topics directly
13	Passive voice / subjectless fragments	"No configuration file needed"	Name the actor when it helps clarity

Style Patterns