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Decision brief
humanizer is a tool designed to remove signs that identify text was generated by an AI system. It can be personalized using samples of the user's own writing.
Good fit when
- When you need to make AI-generated content more human-like without losing its original meaning or intent.
- If specific AI-isms identified in your document are known and need to be targeted directly, as humanizer uses a comprehensive list derived from Wikipedia's guide on signs of AI writing.
Avoid when
- When the exact structure, tone, or style of the AI text is intentionally maintained for particular purposes such as showcasing technological output.
- If the content requires legal review to ensure it adheres strictly to its original form without alterations that could change meaning or implications inadvertently.
Observed Jul 17, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Active (14d since push)
- As of 2w
- Provenance
- Not a fork · Personal account
- As of 2w
- Security (OSV)
- No lockfile
- As of 1mo
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install humanizerHow it fits your stack(1)
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Relationship graph
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Similar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
humanizer removes telltale signs that writing was generated by an AI and can personalize the output to match specific writing styles
Capability facts
- Languages
- python
Source: github.language · Aug 6, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Aug 6, 2026)
npx skills add blader/humanizer --globalSource link
Tags
README
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 globally with the cross-agent skills CLI so Humanizer is available in every project:
npx skills add blader/humanizer --global
Update an existing install:
npx skills update humanizer --global
To install globally into every supported agent harness:
npx skills add blader/humanizer --global --agent '*'
To target one configured harness, pass its agent name:
npx skills add blader/humanizer --global --agent <agent-name>
Omit --global for a project-local install that can be committed and shared with collaborators. Start a new agent session or reload skills after installation.
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]
Point it at a file and the skill rewrites it in place:
Humanize the prose in docs/launch-post.md
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.
Rewrites follow a no-fabrication rule: they never add facts, names, dates, or citations that aren't in the source text. Specificity has to come from the source or the author, not from the rewrite.
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 as part of a wider decentralization" |
| 2 | Notability name-dropping | "cited in NYT, BBC, FT, and The Hindu" | Trim the list; keep only sourced context |
| 3 | Superficial -ing analyses | "symbolizing... reflecting... showcasing..." | Remove, or keep only what the source supports |
| 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" | Name a real source or cut the claim |
| 6 | Formulaic challenges | "Despite challenges... continues to thrive" | Keep the s |
For agents
This page has a .md twin and JSON over the API.