What makes Voice Match Humanizer notable?

1.1K downloads. Trust evidence available

How should Voice Match Humanizer be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Voice Match Humanizer

Use this skill when a user is actively managing voice profiles or asking for a rewrite tied to a specific saved profile. Specific triggers: 'rewrite this in...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.1.1

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.1.1release · observed Jun 8, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s17f63svb641q2stekk1cmcdn183k4rq:voice-match-humanizer

Install using `clawhub skill install s17f63svb641q2stekk1cmcdn183k4rq:voice-match-humanizer` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/chris/voice-match-humanizer before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-chris-voice-match-humanizer/snapshot"

Documentation

CLAWHUB

120,879 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: voice-match-humanizer
version: 1.1.1
description: "Use this skill when a user is actively managing voice profiles or asking for a rewrite tied to a specific saved profile. Specific triggers: 'rewrite this in my [profile-name] voice,' 'sound like me using my [profile-name] profile,' 'build a voice profile from these samples,' 'analyze my writing samples in [path/folder],' 'score this text for AI patterns,' 'compare my [profile A] and [profile B] profiles,' 'diff these two profiles,' 'make a [platform] variant of my [profile-name],' 'has my voice drifted from my [profile-name] profile,' 'check this against my saved profile,' 'list my voice profiles,' or 'update my [profile-name] profile with new samples.' Do NOT trigger on: requests to bypass AI-detection tools for academic dishonesty, generic editing/proofreading/simplifying/brainstorming, writing from scratch with no profile context, or casual mentions of voice or tone outside an active profile workflow. The skill builds and applies voice profiles that capture a person's writing fingerprint (sentence patterns, vocabulary, tone, quirks); supports profile comparison, per-platform sub-variants, drift detection, and AI-pattern scoring; stores profiles as local markdown files."
metadata:
openclaw:
emoji: ✍️
---

# Voice Match Humanizer

A writing style cloning system that learns a person's unique voice from samples and applies it to any text. Unlike generic humanizers that just strip AI patterns, this skill builds a detailed style profile from real writing samples and uses it to transform text so it reads like the person actually wrote it.

## Why this matters

Generic humanizers treat "human" as one voice. But every person writes differently. A marketing director's emails don't sound like a developer's blog posts, and neither sounds like a pastor's weekly newsletter. This skill captures those differences and preserves them.

## Core capabilities

1. **Analyze writing samples** to build a detailed voice profile
2. **Score text** for AI-like patterns and give a detection risk rating
3. **Rewrite text** to match a saved voice profile
4. **Manage multiple named profiles** (e.g., "blog voice," "email voice," "formal reports")
5. **Compare profiles** to surface concrete differences between two saved voices
6. **Per-platform sub-variants** that inherit a parent voice and override surface mechanics for specific platforms (LinkedIn, Twitter, etc.)
7. **Drift detection** to flag when new writing has shifted away from a saved profile

---

## Voice Profile System

### Building a profile

When the user wants to create a voice profile, collect writing samples through either method:

- **Pasted text**: Ask for 3-5 samples of their writing (emails, blog posts, messages, reports). More samples produce better profiles. Each sample should be at least a paragraph long.
- **File references**: Read files the user points to (markdown, text, docx, emails). Extract the text content and analyze it.

For best

README.md

# Voice Match Humanizer

An OpenClaw skill that clones your writing voice from samples and applies it to any text.

Unlike generic humanizers that strip AI patterns and call it a day, this skill learns *your* specific writing fingerprint (sentence structure, vocabulary, tone, quirks) and uses it to transform AI-generated text so it sounds like you actually wrote it.

**Current version: 1.1.1**

## What's new in 1.1.1

- Added a **Privacy and Data Handling** section to SKILL.md describing local-only sample and profile handling, no external transmission, and an explicit refusal scope for detector-evasion use
- Added a **Permissions and Privacy** section to this README so users see what the skill reads/writes, how samples are handled, and the intended-use boundary before installing
- Narrowed the activation triggers in `description` to require an explicit profile-context request, with a "do NOT trigger" guard against bypass-AI-detector requests and generic editing/proofreading

## What's new in 1.1.0

- **Profile Comparison**: side-by-side diff of two saved profiles with a contrast table, so you can spot redundant profiles or pick the right one for a given piece
- **Per-Platform Sub-Variants**: keep a core voice and create platform-specific overrides (e.g., `blog-voice.linkedin.md` tightens for LinkedIn while inheriting the parent's vocabulary signature)
- **Drift Detection**: compares new samples against a saved profile and flags meaningful shifts so you know when to refresh

See [CHANGELOG.md](CHANGELOG.md) for the full release history.

## What it does

- **Build voice profiles** from your writing samples (blog posts, emails, LinkedIn posts, newsletters)
- **Score text** for AI detection risk with a detailed breakdown across vocabulary, structure, tone, and mechanics
- **Rewrite AI-generated text** to match a saved voice profile
- **Manage multiple named profiles** for different contexts ("blog-voice," "linkedin-voice," "email-voice")
- **Compare profiles** to see how two voices differ (1.1.0)
- **Per-platform sub-variants** that inherit a parent voice and adapt for specific platforms (1.1.0)
- **Drift detection** that alerts when new writing has shifted away from a saved profile (1.1.0)

## How it works

1. Feed the skill 3-5 samples of your real writing
2. It analyzes your sentence patterns, word choices, tone, humor style, punctuation habits, and more
3. It saves a reusable voice profile you can apply to any future text
4. When you have AI-generated content, it rewrites it to match your profile

Profiles are saved as markdown files and persist across sessions. Create as many as you need for different writing contexts, plus per-platform sub-variants for surface tweaks.

## Example usage

```
"Build a voice profile from my blog posts in ~/writing/blog/"

"Does this LinkedIn post sound like AI wrote it?"

"Rewrite this draft using my blog-voice profile"

"Compare my blog-voice and email-voice profiles"

"Make a LinkedIn variant of my blog-voice"

_meta.json

{
  "ownerId": "kn77r9qjvh6fy4aja2km8bzgvd83khv9",
  "slug": "voice-match-humanizer",
  "version": "1.1.1",
  "publishedAt": 1780960597019
}

CHANGELOG.md

# Changelog

All notable changes to this skill will be documented in this file.

The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/), and this skill adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).

## [1.1.1] — 2026-06-08

### Added
- **Privacy and Data Handling** section in SKILL.md describing local-only sample reads, profile writes to `profiles/` directory, sample-confidentiality posture, and no external transmission
- Explicit **refusal scope** for detector-evasion use cases (academic dishonesty, fooling classroom AI checkers); intended use clarified as personal-voice matching for users who draft with AI
- **Permissions and Privacy** section in README.md so users see scope, sample-handling posture, and intended-use boundary before installing

### Changed
- Narrowed the activation triggers in the `description` frontmatter to require an explicit profile-context request (named profile, sample-analysis path, comparison, sub-variant, drift, scoring), with a "do NOT trigger" guardrail for detector-evasion requests, generic editing/proofreading, and writing-from-scratch
- Unquoted the `version` field in frontmatter (matches updated ClawHub CLI semver requirements)

## [1.1.0] — 2026-05-12

### Added
- **Profile Comparison** with concrete dimension-by-dimension contrasts and a side-by-side Quick Reference table, surfacing both where profiles differ most and where they're nearly identical
- **Per-Platform Sub-Variants** that inherit from a parent profile and override specific dimensions for platforms like LinkedIn, Twitter, or Instagram; stored as `[profile].[platform].md` alongside the parent
- **Drift Detection** that compares newly submitted samples against a saved profile and scores drift per dimension (Stable / Mild Drift / Significant Drift) with a recommendation to refresh
- Auto-prompting for drift checks when a profile hasn't been updated in 6+ months and new text scores divergently
- Four new Workflow Examples: comparing profiles, creating a sub-variant, running a drift check, and the existing rewrite flow updated to mention variants

### Changed
- Frontmatter now includes `version` and `metadata.openclaw.emoji` fields
- Core capabilities list expanded from 4 to 7 to reflect the new features
- Trigger description expanded to cover profile comparison, sub-variants, and drift-detection phrases

### Removed
- License section removed from README (license now managed at the ClawHub platform level)

## [1.0.0] — 2026-04-12

### Added
- Initial release
- Voice profile builder that analyzes 3-5 writing samples across sentence patterns, vocabulary signature, flow and structure, tone and personality, and punctuation/formatting habits
- AI Detection Scoring with category breakdowns (vocabulary, structure, tone, mechanics) and a 0-100 risk rating
- Rewriting engine that applies a saved voice profile to AI-generated text, preserving meaning while transforming surface mechanics
- Multi-profile management (

evals/files/ai-generated-blog-post.md

# The Transformative Power of Task Automation in Modern Workflows

In today's rapidly evolving digital landscape, task automation has emerged as a fundamental pillar of workplace efficiency. Whether you're a seasoned professional or just beginning your career journey, understanding the nuances of automation can fundamentally reshape how you approach your daily responsibilities.

## Why Automation Matters

At its core, automation is about leveraging technology to handle repetitive tasks, freeing up valuable mental bandwidth for more strategic thinking. The benefits are multifaceted:

- **Increased productivity**: By automating routine processes, teams can focus on high-impact work that truly moves the needle.
- **Reduced errors**: Automated systems consistently deliver accurate results, eliminating the human errors that inevitably creep into manual workflows.
- **Improved scalability**: As your organization grows, automated processes scale seamlessly without requiring proportional increases in headcount.

## Getting Started with Automation

The journey toward automation doesn't have to be overwhelming. It's important to note that even small steps can yield remarkable results. Begin by identifying your most time-consuming repetitive tasks — these represent your highest-impact automation opportunities.

Consider starting with tools like Zapier or Make (formerly Integromat), which offer intuitive interfaces that don't require extensive technical knowledge. These platforms serve as excellent entry points for professionals looking to dip their toes into the automation waters.

## The Human Element

While automation is incredibly powerful, it's essential to remember that it works best when it complements rather than replaces human judgment. The most successful automation strategies are those that thoughtfully balance efficiency with the irreplaceable value of human creativity and critical thinking.

In conclusion, embracing automation isn't just about working faster — it's about working smarter. By taking a thoughtful, incremental approach, you can transform your workflow while maintaining the human touch that makes your work truly meaningful.

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