Humanizer skill for OpenClaw
What this skill does
Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 24 pattern detectors, 500+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
The Humanizer skill is part of the Developer Tools category — developer tools that help your agent write, review, debug, and ship code. You can install it on its own or alongside other developer tools skills from the OpenClaw catalog.
How to install the Humanizer skill
The easiest path is via the OpenClaw Easy desktop app — one click, no terminal required:
- Download OpenClaw Easy for macOS or Windows (free, one-click installer, ~30 seconds).
- Open the in-app Skills panel.
- Search for
ai-humanizerand click Install. - The skill activates automatically when an incoming message matches its description.
Install from the command line
If you already run the OpenClaw CLI, add the Humanizer skill with a single command:
openclaw skills add ai-humanizer
This pulls ai-humanizer from ClawHub and installs it into ~/.openclaw/skills/ai-humanizer/. Restart the OpenClaw gateway afterwards so the new skill is discovered.
How to use the Humanizer skill
Once installed, the Humanizer skill activates on its own: when an incoming message on WhatsApp, Telegram, Slack, Discord, Feishu or Line matches the skill's description, your OpenClaw agent loads it and runs the workflow. You can also trigger it explicitly by describing the task in chat. No extra configuration is required after install.
Putting audio in front of an audience
Humanizer works with audio. Getting from there to something postable is a separate job: ViralMint — an open-source video pipeline — pairs audio with footage or generated visuals, burns synced captions, and exports a finished short.
It runs as an MCP server, so an OpenClaw agent can drive it from the same chat you already use: ask for a short, and the render comes back finished. See how to connect a video pipeline to your agent.
Manual install (advanced)
If you prefer manual installation:
- Click the Download skill .zip button above to grab
ai-humanizer-2.1.0.zipdirectly from our S3 mirror. - Unzip into
~/.openclaw/skills/ai-humanizer/(create the directory if it does not exist). - Restart OpenClaw Easy (or the OpenClaw CLI gateway) so the new skill is discovered.
Frequently asked questions
How do I install Humanizer?
Install Humanizer in the OpenClaw Easy desktop app by opening the Skills panel, searching for ai-humanizer, and clicking Install. From a terminal you can run: openclaw skills add ai-humanizer. Either way the skill is placed in ~/.openclaw/skills/ai-humanizer/.
Is the Humanizer skill free?
Yes. It is free to download and run through ClawHub, with no account or payment required. Each skill is published by its own author under its own licence — see its ClawHub page for the licence and source.
What does Humanizer do?
Humanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human.
Related: more developer tools skills
If the Humanizer skill looks useful, you may also want to check out other developer tools skills in the OpenClaw catalog:
Skills in this catalog are community-contributed integrations published on ClawHub and distributed under their own open-source licences. Product and company names, and any third-party service a skill connects to, are trademarks of their respective owners; a listing here does not imply affiliation with, sponsorship by, or endorsement from them. This page does not distribute any third-party application. Rights holders can reach us at hello@openclaw-easy.com.
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Free, open-source · Apache-2.0 · Works with Claude, ChatGPT, Gemini, or local Ollama models