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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Comprehensive CLI for detecting and transforming AI-generated text to bypass detectors. Based on Wikipedia's Signs of AI Writing.
# 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
The analyzer checks for 16 pattern categories from Wikipedia's guide:
| Category | Examples |
|---|---|
| Citation Bugs | oaicite, turn0search, contentReference |
| Knowledge 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 |
| Category | Examples |
|---|---|
| AI Vocabulary | delve, tapestry, landscape, pivotal, underscore, foster |
| Significance Inflation | "serves as a testament", "pivotal moment", "indelible mark" |
| Promotional Language | vibrant, groundbreaking, nestled, breathtaking |
| Copula Avoidance | "serves as" instead of "is", "boasts" instead of "has" |
| Category | Examples |
|---|---|
| Superficial -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" |
| Category | Examples |
|---|---|
| Curly Quotes | "" instead of "" (ChatGPT signature) |
| Em Dash Overuse | Excessive use of — for emphasis |
| Negative Parallelisms | "Not only... but also", "It's not just... it's" |
| Rule of Three | Forced triplets like "innovation, inspiration, and insight" |
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:
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:
Aggressive (-a):
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
| Rating | Criteria |
|---|---|
| Very High | Citation bugs, knowledge cutoff, or chatbot artifacts present |
| High | >30 issues OR >5% issue density |
| Medium | >15 issues OR >2% issue density |
| Low | <15 issues AND <2% density |
Edit scripts/patterns.json to add/modify:
# 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
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."
No automatic installation available. Please visit the source repository for installation instructions.
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