De-AI Writer — Chinese AI-Smell Removal

Overview

Chinese AI writing has its own tells, and they are not the English ones. English humanizers hunt delve, "it's not just X, it's Y" and em-dash overuse; a Chinese draft reads machine-written because of 赋能 / 闭环 / 抓手 / 底层逻辑 (pattern 15), 首先-其次-最后 scaffolding (pattern 30), 随着…的发展 openers (pattern 25), 拔高意义 endings (pattern 16), and 公文套话 (pattern 22). A translated English humanizer misses all of it.

This skill ships the pattern catalog plus the editing procedure: score a draft for AI smell, rewrite it against the specific patterns it hits, clone a reference style, and review the result. The full 35-pattern catalog lives in references/ai-patterns-zh.md and is plain Markdown — usable as a prompt by any assistant.

Note on the engine: this bundle is documentation only. A zero-dependency local rule engine is published in the source repository (see source_repo) as an optional external prerequisite — it is not included here.

When to Use This Skill

• Use when a Chinese draft "reads like AI" and needs to sound human-authored.
• Use when the user asks 去AI味, 改得像人写的, or 这段是不是AI写的 (is this AI-written?).
• Use when editing marketing copy, WeChat articles, product listings, or social posts written in Chinese.
• Use when asked to imitate a reference writing style (风格克隆) or to produce A/B variants of the same copy.
• Use when shifting tone: casual / formal / marketing / humor / direct.

How It Works

Step 1: Score the draft first (diagnose before editing)

Scan the text, record which patterns hit and where, then compute the AI-smell index with the deterministic formula below. Do not rewrite from vibes — the same phrases recur, and you need the hit list to verify the edit afterwards.

The AI-smell index (deterministic — the same formula must be used before and after)

1. Count hits per paragraph. For each pattern, count one hit per paragraph — repeats inside the same paragraph do not inflate the score.
2. Weight by evidence strength. 强模式 = 2 points; patterns the catalog marks 弱证据 (破折号 / 限定词 / 被动与无主语 / "的"-字堆叠 / 引号不统一) = 1 point.
3. Normalize by length. D = 加权总分 / max(1, 总字数 / 100) — weighted hits per 100 characters.
4. Index. AI味指数 = min(100, round(D × 10)).
5. Bands. 0–20 基本像人写 · 21–45 轻度 AI 味 · 46–75 明显 AI 味 · 76–100 一眼假.
6. Report three numbers, not one: 命中处数 / 加权总分 / AI味指数. After rewriting, recompute with the same formula so the delta is comparable. If a hit cannot be attributed to a catalogued pattern, report only the observable hit count and say the index is not computed — never invent a number.

Worked example (the sample below): 8 hits in 77 characters, 6 strong (6 × 2 = 12) + 2 weak (2 × 1 = 2) → 加权总分 14 → D = 14 / 0.77 ≈ 18.2 → 指数 = min(100, 182) = 100/100.

AI 味体检报告
总字数 77 ｜ 命中 8 处 ｜ 加权 14 ｜ AI味指数 100/100（一眼假）
机械连接 ×3   官方黑话 ×2   空洞拔高 ×2   夸张词 ×1

Step 2: Rewrite against the specific patterns, not in general

Work through the hit list one pattern at a time. Correct each pattern by its own rule (the catalog gives 识别特征 → 为什么假 → 改前/改后 for all 35). Two rules govern the whole pass:

• A single hit is not evidence. The catalog marks certain patterns (em-dash, hedges, passive voice, 的-stacking, quotation marks) as 弱证据 — only act when two or more appear in the same paragraph.
• Delete, don't decorate. Most patterns disappear by deleting the sentence that carries them: drop the negation half of 不是 X，而是 Y, drop the significance ending, drop the 开场铺垫, drop the assistant residue (希望对你有帮助).

The facts come from the source, never from the pattern list. A rewrite may delete packaging, reorder, and rephrase; it must not introduce a fact the source does not contain. If the rewrite would be clearer with a number or a specification (rotational speed, battery life, materials), and the source has none, ask the user for it — never supply one.

Step 3: Verify the rewrite

Re-score the rewritten text with the same Step 1 formula. The index should drop and the semantic content must be preserved — report the before/after triple (命中处数 / 加权总分 / 指数), how many patterns were cleared, and confirm that no fact was added or lost. A rewrite that lowers the score by deleting facts is a failed edit; so is one that raises the count of facts in the text.

Step 4: Optional — style clone, variants, tone, review

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