humanize-chinese

# Humanize Chinese

Use this skill when you need to detect AI-like Chinese writing, rewrite it to feel less synthetic, reduce AIGC signals in academic prose, or convert the text into a more specific Chinese writing style.

## When to Use

- Use when the user says `去AI味`, `降AIGC`, `去除AI痕迹`, `让文字更自然`, `改成人话`, or `降低AI率`
- Use when the user wants a Chinese text checked for AI-writing patterns or suspicious phrasing
- Use when the user wants academic-paper-specific AIGC reduction for CNKI, VIP, or Wanfang-style checks
- Use when the user wants Chinese text rewritten into a different style such as `zhihu`, `xiaohongshu`, `wechat`, `weibo`, `literary`, or `academic`

## Core Workflow

### 1. Detect Before Rewriting

Start by identifying the most obvious AI markers instead of rewriting blindly:

- rigid `first/second/finally` structures
- mechanical connectors such as `综上所述`, `值得注意的是`, `由此可见`
- abstract grandiose wording with low information density
- repeated sentence rhythm and paragraph length
- academic prose that sounds too complete, too certain, or too template-driven

If the user provides a short sample, call out the suspicious phrases directly before rewriting.

### 2. Rewrite in the Smallest Useful Pass

Prefer targeted rewrites over total regeneration:

- remove formulaic connectors rather than paraphrasing every sentence
- vary sentence length and paragraph rhythm
- replace repeated verbs and noun phrases
- swap abstract summaries for concrete observations where possible
- keep the original claims, facts, citations, and terminology intact

### 3. Validate the Result

After rewriting, verify that the text:

- still says the same thing
- sounds less templated
- uses more natural rhythm
- does not introduce factual drift
- stays in the correct register for the target audience

For academic text, preserve a scholarly tone. Do not over-casualize.

## Optional CLI Flow

If the user has a local clone of the source toolkit, these examples are useful:

```bash
python3 scripts/detect_cn.py text.txt -v
python3 scripts/compare_cn.py text.txt -a -o clean.txt
python3 scripts/academic_cn.py paper.txt -o clean.txt --compare
python3 scripts/style_cn.py text.txt --style xiaohongshu -o out.txt
```

Use this CLI sequence when available:

1. detect and inspect suspicious sentences
2. rewrite or compare
3. rerun detection on the cleaned file
4. optionally convert into a target style

## Manual Rewrite Playbook

If the scripts are unavailable, use this manual process.

### Common AI Markers

- numbered or mirrored structures that feel too symmetrical
- filler transitions that add no meaning
- repeated stock phrases
- overly even sentence length
- conclusions that sound final, polished, and risk-free

### Rewrite Moves

- delete weak transitions first
- collapse repetitive phrases into one stronger sentence
- split sentences at natural turns instead of forcing long balanced structures
- merge choppy sentences when they feel robotic
- replace generic abstractions with concrete wording
- introduce light variation in cadence so the prose does not march at a constant tempo

## Academic AIGC Reduction

For papers, reports, or theses:

- keep discipline-specific terminology unchanged
- replace AI-academic stock phrases with more grounded scholarly phrasing
- reduce absolute certainty with measured hedging where appropriate
- vary paragraph structure so each section does not read like the same template
- add limitations or uncertainty if the conclusion feels unnaturally complete

Examples of safer direction changes:

- `本文旨在` -> `本文尝试` or `本研究关注`
- `具有重要意义` -> `值得关注` or `有一定参考价值`
- `研究表明` -> `前人研究发现` or `已有文献显示`

Do not invent citations, evidence, or data.

## Style Conversion

Use style conversion only after the base text is readable and natural.

Supported style directions from the source workflow:

- `casual`
- `zhihu`
- `xiaohongshu`
- `wechat`
- `academic`
- `literary`
- `weibo`

When switching style, keep the user's meaning stable and change only tone, structure, and surface wording.

## Output Rules

- Show the main AI-like patterns you found
- Explain the rewrite strategy in 1-3 short bullets
- Return the rewritten Chinese text
- If helpful, include a short note on remaining weak spots

## Source

Adapted from the `voidborne-d/humanize-chinese` project and its CLI/script workflow for Chinese AI-text detection and rewriting.