Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Communication & Collaboration
Humanize AI text
Humanize AI-generated text to bypass detection. This humanizer rewrites ChatGPT, Claude, and GPT content to sound natural and pass AI detectors like GPTZero,...
skill openclawclawhub Free
Humanize AI-generated text to bypass detection. This humanizer rewrites ChatGPT, Claude, and GPT content to sound natural and pass AI detectors like GPTZero,...
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0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, scripts/transform.py, scripts/patterns.json, scripts/detect.py, scripts/compare.py
Validation
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- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
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New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
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Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- moltbro
- Source page
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Documentation
Humanize AI Text
Comprehensive CLI for detecting and transforming AI-generated text to bypass detectors. Based on Wikipedia's Signs of AI Writing.
Quick Start
# Detect AI patterns python scripts/detect.py text.txt # Transform to human-like python scripts/transform.py text.txt -o clean.txt # Compare before/after python scripts/compare.py text.txt -o clean.txt
Detection Categories
The analyzer checks for 16 pattern categories from Wikipedia's guide:
Critical (Immediate AI Detection)
CategoryExamplesCitation Bugsoaicite, turn0search, contentReferenceKnowledge Cutoff"as of my last training", "based on available information"Chatbot Artifacts"I hope this helps", "Great question!", "As an AI"Markdown**bold**, ## headers, code blocks
High Signal
CategoryExamplesAI Vocabularydelve, tapestry, landscape, pivotal, underscore, fosterSignificance Inflation"serves as a testament", "pivotal moment", "indelible mark"Promotional Languagevibrant, groundbreaking, nestled, breathtakingCopula Avoidance"serves as" instead of "is", "boasts" instead of "has"
Medium Signal
CategoryExamplesSuperficial -ing"highlighting the importance", "fostering collaboration"Filler Phrases"in order to", "due to the fact that", "Additionally,"Vague Attributions"experts believe", "industry reports suggest"Challenges Formula"Despite these challenges", "Future outlook"
Style Signal
CategoryExamplesCurly Quotes"" instead of "" (ChatGPT signature)Em Dash OveruseExcessive use of โ for emphasisNegative Parallelisms"Not only... but also", "It's not just... it's"Rule of ThreeForced triplets like "innovation, inspiration, and insight"
detect.py โ Scan for AI Patterns
python scripts/detect.py essay.txt python scripts/detect.py essay.txt -j # JSON output python scripts/detect.py essay.txt -s # score only echo "text" | python scripts/detect.py Output: Issue count and word count AI probability (low/medium/high/very high) Breakdown by category Auto-fixable patterns marked
transform.py โ Rewrite Text
python scripts/transform.py essay.txt python scripts/transform.py essay.txt -o output.txt python scripts/transform.py essay.txt -a # aggressive python scripts/transform.py essay.txt -q # quiet Auto-fixes: Citation bugs (oaicite, turn0search) Markdown (**, ##, ```) Chatbot sentences Copula avoidance โ "is/has" Filler phrases โ simpler forms Curly โ straight quotes Aggressive (-a): Simplifies -ing clauses Reduces em dashes
compare.py โ Before/After Analysis
python scripts/compare.py essay.txt python scripts/compare.py essay.txt -a -o clean.txt Shows side-by-side detection scores before and after transformation
Workflow
Scan for detection risk: python scripts/detect.py document.txt Transform with comparison: python scripts/compare.py document.txt -o document_v2.txt Verify improvement: python scripts/detect.py document_v2.txt -s Manual review for AI vocabulary and promotional language (requires judgment)
AI Probability Scoring
RatingCriteriaVery HighCitation bugs, knowledge cutoff, or chatbot artifacts presentHigh>30 issues OR >5% issue densityMedium>15 issues OR >2% issue densityLow<15 issues AND <2% density
Customizing Patterns
Edit scripts/patterns.json to add/modify: ai_vocabulary โ words to flag significance_inflation โ puffery phrases promotional_language โ marketing speak copula_avoidance โ phrase โ replacement filler_replacements โ phrase โ simpler form chatbot_artifacts โ phrases triggering sentence removal
Batch Processing
# Scan all files for f in *.txt; do echo "=== $f ===" python scripts/detect.py "$f" -s done # Transform all markdown for f in *.md; do python scripts/transform.py "$f" -a -o "${f%.md}_clean.md" -q done
Reference
Based on Wikipedia's Signs of AI Writing, maintained by WikiProject AI Cleanup. Patterns documented from thousands of AI-generated text examples. Key insight: "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."
Category context
Messaging, meetings, inboxes, CRM, and teammate communication surfaces.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Scripts1 Docs1 Config
- SKILL.md
- scripts/compare.py
- scripts/detect.py
- scripts/transform.py
- scripts/patterns.json