# Humanize AI Text

> AI 生成文本人性化改写。将 ChatGPT、Claude、GPT 等生成的内容改写为自然流畅的表达，可通过 GPTZero、Turnitin、Originality.ai 等 AI 检测工具。基于维基百科"AI 写作特征"指南，让机械化的 AI 文本变得自然且不可检测。

- Skill: `alter123-zz/humanize-ai-text` (Agent Skill, multi-file: 6 files)
- Install (CLI): `npx skillmds@latest add alter123-zz/humanize-ai-text`
- Raw SKILL.md: https://api.skillmd.com/api/skills/alter123-zz/humanize-ai-text/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: alter123-zz (https://skillmd.com/u/alter123-zz)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/alter123-zz/humanize-ai-text

---


# Humanize AI Text

Comprehensive CLI for detecting and transforming AI-generated text to bypass detectors. Based on [Wikipedia's Signs of AI Writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing).

## Quick Start

```bash
# 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)
| 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 ``` |

### High Signal
| 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" |

### Medium Signal
| 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" |

### Style Signal
| 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" |

---

## Scripts

### detect.py — Scan for AI Patterns

```bash
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 — Rewrite Text

```bash
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 → "is/has"
- Filler phrases → simpler forms
- Curly → straight quotes

**Aggressive (-a):**
- Simplifies -ing clauses
- Reduces em dashes

### compare.py — Before/After Analysis

```bash
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

1. **Scan** for detection risk:
   ```bash
   python scripts/detect.py document.txt
   ```

2. **Transform** with comparison:
   ```bash
   python scripts/compare.py document.txt -o document_v2.txt
   ```

3. **Verify** improvement:
   ```bash
   python scripts/detect.py document_v2.txt -s
   ```

4. **Manual review** for AI vocabulary and promotional language (requires judgment)

---

## AI Probability Scoring

| 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 |

---

## Customizing Patterns

Edit `scripts/patterns.json` to add/modify:
- `ai_vocabulary` — words to flag
- `significance_inflation` — puffery phrases
- `promotional_language` — marketing speak
- `copula_avoidance` — phrase → replacement
- `filler_replacements` — phrase → simpler form
- `chatbot_artifacts` — phrases triggering sentence removal

---

## Batch Processing

```bash
# 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](https://en.wikipedia.org/wiki/Wikipedia: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."