Text Humanizer
A precision editor that identifies and removes 24 specific AI-writing patterns to create natural, human prose.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsText Humanizer
Example session with this skill installed
Humanize this text in casual mode: The implementation of this feature stands as a testament to our commitment to innovation, showcasing a vibrant tapestry of technical excellence.
- Read your context and instructions
- Compiled the text humanizer
Rewritten
I'm really proud of how this feature turned out. We spent a lot of time getting the technical details right, and it shows in the final build.
Changes
- Pattern 1: Removed "stands as a testament"
- Pattern 3: Removed "-ing" analysis ("showcasing")
- Pattern 7: Removed AI vocabulary ("vibrant tapestry")
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
AI-generated text often feels robotic, overly formal, and predictable. Readers easily spot "slop" through repetitive vocabulary, inflated significance, and formulaic structures that lack a human pulse.
What it does
- Identifies 24 specific markers of AI writing based on the WikiProject AI Cleanup taxonomy.
- Rewrites robotic prose into natural, rhythmic language while preserving the original meaning.
- Removes common AI-isms like "testament to," "vibrant tapestry," and "pivotal moment."
- Adjusts tone across six style modes including technical, academic, and marketing.
- Injects "soul" by varying sentence length, adding specific opinions, and using first-person perspective where appropriate.
Frameworks & tools
Includes Python scripts for batch processing (detect.py, transform.py, compare.py) and an editable patterns.json rulebook.
Why this beats prompting it yourself
Generic "make this sound human" prompts usually just trade one type of AI fluff for another. This skill uses a rigorous 24-point technical audit to strip away specific statistical artifacts that generic prompting misses.
Use cases
- Convert AI-drafted technical documentation into readable developer guides.
- Scrub "marketing slop" from AI-generated product descriptions and blog posts.
- Audit academic abstracts to remove tell-tale chatbot artifacts and disclaimers.
- Humanize internal business reports to sound like they came from a team member.
Known limitations
Requires Python for the optional batch scripts. Mechanical transforms cover 12 of 24 patterns, while complex style shifts require the LLM workflow.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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Recently published to Agensi
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Trust & safety
Security scanned
Verified clean 1 month ago
- Passed all security checks, Safe to install
Needs access to
Wikipedia