Text Humanize — 中英文去 AI 味檢測 + 改寫
📖 技能介紹
name: text-humanize description: > Audit and de-AI text for social platforms — bilingual (English + 中文). Auto-detects language, then detects AI-generated patterns: structural tells, opening/closing clichés, surface signals, and platform-specific red flags. Rewrites text to sound like a real human wrote it. Use when checking text for "AI smell" before posting to HN, Twitter/X, Reddit, Facebook, LinkedIn, Dev.to, 微信公眾號, 知乎, 小紅書, 即刻, 微博, 抖音, B站, or any public forum.
- Version: 1.0.0
- License: MIT
- Author: Evan Song · github.com/Songhonglei
- Repository: https://github.com/Songhonglei/text-humanize
Text Humanize — 中英文去 AI 味檢測 + 改寫
Bilingual AI-smell auditor and humanizer. Auto-detects whether input is English or Chinese, then applies the right detection patterns and rewrite rules. Built from real flagged data on English platforms (HN, Reddit) and Chinese platforms (公眾號, 知乎, 小紅書).
Language Auto-Detection
Before starting any audit, detect the input language:
- Count CJK characters (Unicode range U+4E00–U+9FFF, U+3400–U+4DBF, U+F900–U+FAFF).
- Count Latin characters (a-z, A-Z).
- Rule: If CJK characters > 50% of total letters → Chinese mode. Otherwise → English mode.
- If the user explicitly says "用中文最佳化" or "用英文最佳化", override auto-detection.
- For mixed text (e.g., Chinese with English code blocks), detect based on the natural-language portions only, ignoring code.
How It Works — Two Modes
Both modes work identically for English and Chinese; just the pattern catalog differs.
Mode A: Audit Only (trigger: "check", "audit", "檢查", "看看")
- Auto-detect language.
- Load the appropriate reference:
references/ai-smells-en.mdfor English,references/ai-smells-cn.mdfor Chinese. - Scan the text against all 5 smell categories (Structural, Opening, Body, Closing, Surface).
- Produce a concise audit report listing every detected smell with:
- The smell code (e.g., S1, O-CN1, B-CN3, SS-CN1)
- The specific phrase/pattern triggering it
- A 1-line fix suggestion (in the text's language)
- Give an overall "AI smell score":
- 🟢 Green (1-2 smells): Looks human. Minor suggestions only.
- 🟡 Yellow (3-5 smells): Some AI patterns. Consider fixes.
- 🔴 Red (6+ smells): High risk of flagging. Strongly recommend rewriting.
Mode B: Audit + Rewrite (trigger: "humanize", "rewrite", "fix", "最佳化", "改一下", "去AI味")
- Run the full audit (Mode A).
- Produce a rewritten version following language-specific rules (see below).
- Show the original and rewrite side-by-side with a brief summary of what changed.
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- Ask the user which version to use (or if they want further tweaks).
English Mode
Refer to references/ai-smells-en.md for the complete English pattern catalog. Summary of categories:
| Category | Code | Key Signals |
|---|---|---|
| Structural | S1-S3 | 4+ paragraphs, numbered lists, quote-then-respond |
| Opening | O1-O3 | "This resonates...", "From building X...", "As someone who..." |
| Body | B1-B6 | Balanced argumentation, feature listing, insight formula, example cascading, collective "we", formal connectors |
| Closing | C1-C3 | Polished conclusion, "Curious what others think", forced positivity |
| Surface | SS1-SS5 | Zero typos, em-dashes, no filler words, uniform sentence length, semantic punctuation |
English Rewriting Principles
- Structure killer. Destroy essay structure. 1-2 paragraphs max. No intro-body-conclusion.
- Opinion injector. Take a side. "i think X is wrong" beats "X has merits but also drawbacks."
- Human fingerprint. Add at least: 1 typo (missing apostrophe), 1 filler word, 1 moment of uncertainty.
- Experience, not features. Express a specific struggle, not a feature list.
- Stop early. End with uncertainty or trail off. No polished conclusion.
English Platform Rules
| Platform | Max Length | Tone | Special Rules |
|---|---|---|---|
| HN | 1-3 paragraphs, 5-6 lines | Technical, opinionated, humble | Strictest AI detection. No self-linking. Self-deprecation is currency. |
| Twitter/X | 1-2 sentences or punchy thread | Punchy, informal, voice-driven | Numbered threads (1/9) = AI flag. Each tweet stands alone. |
| 1-3 paragraphs | Smart-friend-chat | Subreddit-dependent. r/programming ≈ HN. | |
| 1-2 short paragraphs | Casual, personal | Tech groups: HN rules. Personal feed: be human. | |
| 1-2 paragraphs | Casual professional | Avoid "thought leader" tone. | |
| Dev.to | 2-3 paragraphs | Technical but conversational | Slightly more length-tolerant than HN. |
If no English platform is specified, default to HN rules (strictest baseline).
中文模式 (Chinese Mode)
Refer to references/ai-smells-cn.md for the complete Chinese pattern catalog. Summary of categories:
| 類別 | 程式碼 | 關鍵訊號 |
|---|---|---|
| 結構 | S-CN1~S-CN4 | 議論文三段式、"首先其次最後"、編號列表、引用原文再回復 |
| 開頭 | O-CN1~O-CN3 | "這個問題很有啟發性…"、"作為一個…"、"有道理但是…" |
| 正文 | B-CN1~B-CN7 | 書面連線詞過頻、對稱辯證、金句提煉、舉例論證、"我們"濫用、中英混雜、功能羅列 |
| 結尾 | C-CN1~C-CN3 | 昇華式收尾、開放式互動、正能量用力過猛 |
| 表面 | SS-CN1~SS-CN6 | 零錯別字、句式工整、缺少語氣詞、句號強迫症、破折號"——"、翻譯腔 |
中文改寫黃金規則
- 結構打碎。 不要開頭-中間-結尾。1-2 段，直接亮態度。
- 加語氣詞。 至少 1-2 個：吧、嘛、呢、啊、就、還挺、講真、說實話。
- 加 1-2 個「錯」。 的/地/得混用，或在/再混用。不要太刻意，2 個就夠了。
- 短句為主，偶爾混長句。 節奏參差不齊才像人。
- 有態度。 敢說"我覺得不對"、"試過就知道坑"。不要和稀泥。
- 結尾不升華。 用不確定感收尾或戛然而止。不要"值得深思"。
- 個人經驗 > 通用道理。 講自己踩過的坑，不講放之四海而皆準的道理。
- 寧可碎一點。 半句話、反問句、語氣詞結尾都行，不要追求「完整」。
中文平臺特定規則
| 平臺 | 長度限制 | 語氣 | 特別注意 |
|---|---|---|---|
| 微信公眾號 | 正文 500-1500 字；評論 1-3 句 | 可稍正式但有個性 | AI 檢測最嚴。致命傷：標題黨 + 三段式 + 昇華結尾 |
| 知乎 | 回答不限；評論 2-5 句 | 有態度，不怕槓 | 致命傷："謝邀"開頭 + 分點論述 + "以上"結尾 |
| 小紅書 | 正文 50-200 字；評論 1-3 句 | 輕鬆、口語化 | 善用 emoji 但別每句都加。標籤區和正文分開 |
| 即刻 | 1-3 句 | 極隨意 | 語氣詞決定生死。不要長篇大論 |
| 微博 | 1-3 句 | 直接、有梗 | 可用網路用語，但不堆砌 |
| B站評論區 | 1-3 句 | 彈幕風格 | 語氣詞 + emoji 友好 |
| 抖音評論區 | 1 句，最多 2 句 | 極短 | 超過 3 句 = 直接判 AI |
| 朋友圈 | 1-3 句 | 熟人聊天感 | 不要"通知"語氣，不要排比句 |
如果沒有指定中文平臺，預設按知乎評論區規則處理（適中長度 + 有態度的口語）。
Edge Cases
- Very short text (under 20 words / 30 字): Almost certainly human. Only check surface smells. Don't over-audit.
- Technical code-heavy text: Code blocks are exempt. Only audit the natural language portions.
- User wants formal tone: Skip typo/錯別字 injection. Still de-structure and remove academic openers.
- Text already has human markers: If 3+ human fingerprints already present, focus on structural smells only. Don't over-humanize.
- Mixed EN/CN content: Audit each language block separately against its own catalog. If truly bilingual, note it and ask the user which language to prioritize.
- Quoted text / retweets: Only audit the user's own added text. Quoted/retweeted content is exempt.
🤖 AI 評測
這個 Skill 的設計思路很實用，能幫助檢測和改寫帶「AI味」的文本，支援中英文。不過目前只是個半成品：文件不完整，缺少實際可執行的程式碼。如果開發者後續補全程式碼和文件，質量會是不錯的。現在直接使用的話，基本功能無法執行。
