據 AlphaMoat 統計,截至 2026-09,Humanizer Enhanced 累計下載 3,020 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 3,718 位,在「內容創作」分類(362 個)中排名第 246 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 75 | 2630 | - | - |
| SkillHub ↗ | 165 | 3020 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
該技能會按嚴重程度標記其認為類似 AI 寫作的表達,並可建議修改、調整可讀性和語氣。主文要求先向使用者確認再應用修復。技能卡提示改寫可能顯著改變原文語氣、格式、事實細節或歸屬;發布前應對照原文檢查來源、日期和主張,尤其核驗統計資訊及加密/Web3內容。
資料釋出於 2026-10-27
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 3020 | — | 1 |
| 2026-08 | 2548 | +6.7% | 1 |
| 2026-07 | 2388 | +17.1% | 1 |
| 2026-06 | 2040 | +7.3% | 1 |
| 2026-05 | 1902 | — | 1 |
| 2026-03 | 1272 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: humanizer-enhanced description: | Advanced AI text humanizer for blog content. Detects and removes 34 AI writing patterns, adds personality/soul, and handles crypto/Web3 specific tells. Use when user says /humanizer, "humanize this", "remove AI patterns", "make it sound human", or asks to clean up blog posts, articles, or drafts. Features: 28 base patterns from Wikipedia's "Signs of AI writing", 6 crypto/Web3 specific patterns, severity scoring (HIGH/MEDIUM/LOW), stat attribution fixer, soul/personality injection, batch mode.
metadata: version: 1.2.0 author: 0G Labs content team --- # Humanizer enhanced: remove AI writing patterns Identify and remove signs of AI-generated text. This enhanced version includes crypto/Web3 patterns and adds personality to make content sound genuinely human-written. ## Quick start ```text /humanizer # Humanize current file or selection /humanizer path/to/file.md # Humanize specific file /humanizer --scan # Scan only, don't edit (show issues) /humanizer --batch drafts/ # Process all .md files in directory ``` --- ## Process ### Step 1: Scan for patterns Identify all AI patterns in the text, categorize by severity: - **HIGH** — Obvious AI tells, must fix (negative parallelism, chatbot artifacts, em dash overuse, vague attributions, copula avoidance) - **MEDIUM** — Common AI patterns, should fix (rule of three, significance inflation, synonym cycling) - **LOW** — Minor tells, fix if time permits (title case headings, excessive bold) ### Step 2: Report findings Show user a summary: ```text ## Humanizer scan results HIGH (3 issues) - Line 45: Negative parallelism "isn't X. It's Y" - Line 89: Em dash overuse (5 instances) - Line 120: "Research shows" without attribution MEDIUM (5 issues) - Line 23: Rule of three pattern - Line 67: Copula avoidance "serves as" ... LOW (2 issues) - Line 12: Title case heading ... Total: 10 issues found Estimated humanization: ~15 edits needed ``` ### Step 3: Fix (with user approval) Ask user: "Fix all issues? Or review one by one?" ### Step 4: Add soul After fixing patterns, review for personality. Sterile writing is still obvious AI. See `references/communication-crypto-soul-patterns.md` for the full soul/personality guide. ### Step 5: Readability check Check Flesch-Kincaid readability. Target grade 10-12 for developer content, grade 8-10 for general audience. If score is too high (too complex), simplify longest sentences and replace jargon. ### Step 6: Em dash regression scan After all other fixes, run a final check for em dashes (—) across the text. Humanizer rewrites can reintroduce em dashes. Remove any that were added during the fix process. --- ## Pattern routing table All 34 patterns are documented with before/after examples in the reference files below. | Patterns | Severity | Reference file | |----------|----------|----------------| | 1. Significance inflation | MEDIUM | `references/content-patterns.md` | | 2. Promotional language | MEDIUM | `references/content-patterns.md` | | 3. Superficial -ing analyses | MEDIUM | `references/content-patterns.md` | | 4. Vague attributions | HIGH | `references/content-patterns.md` | | 5. Formulaic challenges sections | MEDIUM | `references/content-patterns.md` | | 6. Generic positive conclusions | MEDIUM | `references/content-patterns.md` | | 7. AI vocabulary words | MEDIUM | `references/language-style-patterns.md` | | 8. Copula avoidance | HIGH | `references/language-style-patterns.md` | | 9. Negative parallelism | HIGH | `references/language-style-patterns.md` | | 10. Rule of three | MEDIUM | `references/language-style-patterns.md` | | 11. Synonym cycling | MEDIUM | `references/language-style-patterns.md` | | 12. False ranges | LOW | `references/language-style-patterns.md` | | 13. Em dash overuse | HIGH | `references/language-style-patterns.md` | | 14. Excessive boldface | LOW | `references/language-style-patterns.md` | | 15. Inline-header lists | MEDIUM | `references/language-style-patterns.md` | | 16. Title case headings | LOW | `references/language-style-patterns.md` | | 17. Curly quotes | LOW | `references/language-style-patterns.md` | | 18. Chatbot artifacts | HIGH | `references/communication-crypto-soul-patterns.md` | | 19. Knowledge cutoff disclaimers | HIGH | `references/communication-crypto-soul-patterns.md` | | 20. Sycophantic tone | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 21. Excessive hedging | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 22. Filler phrases | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 23. Crypto hype language | HIGH | `references/communication-crypto-soul-patterns.md` | | 24. Vague "ecosystem" claims | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 25. Unsubstantiated stats | HIGH | `references/communication-crypto-soul-patterns.md` | | 26. "Seamless" and "frictionless" | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 27. Abstract "empowerment" language | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 28. Fake decentralization claims | HIGH | `references/communication-crypto-soul-patterns.md` | | 29. Meta-narration | HIGH | `references/communication-crypto-soul-patterns.md` | | 30. False audience range | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 31. Parenthetical definitions | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 32. Sequential numbering | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 33. "It's worth noting" filler | MEDIUM | `references/communication-crypto-soul-patterns.md` | | 34. Identical paragraph structure | HIGH | `references/communication-crypto-soul-patterns.md` | | Soul and personality guide | — | `references/communication-crypto-soul-patterns.md` | --- ## Severity reference | Severity | Patterns | Action | |----------|----------|--------| | HIGH | Negative parallelism, em dash overuse, chatbot artifacts, vague attributions, copula avoidance, crypto hype, unsubstantiated stats, meta-narration, identical paragraph structure, fake decentralization, knowledge cutoff disclaimers | Must fix | | MEDIUM | Rule of three, significance inflation, promotional language, -ing analyses, AI vocabulary, sycophantic tone, hedging, filler phrases, ecosystem claims, false audience range, parenthetical definitions, sequential numbering, "it's worth noting" filler, inline-header lists, "seamless"/"frictionless", abstract empowerment | Should fix | | LOW | Title case, curly quotes, excessive bold, false ranges | Fix if time permits | --- ## Quick reference: find and replace | Find | Replace | |------|---------| | `—` (em dash, multiple) | `, ` or `. ` | | `serves as` / `stands as` | `is` | | `isn't X. It's Y` | Rewrite as single statement | | `crucial` / `vital` / `pivotal` | `important` or `key` or delete | | `Furthermore,` / `Moreover,` | `Also,` or delete | | `It is important to note` | Delete | | `Research shows` | Add specific source | | `landscape` (abstract) | Be specific | | `revolutionizing` / `game-changing` | Describe what it actually does | | `seamless` / `frictionless` | Describe the actual UX | | `In this article, we'll explore` | Delete | | `Let's dive in` / `Let's take a look` | Delete | | `First,... Second,... Third,...` | Vary transitions | | `It's worth noting` / `Notably,` | Delete | | `delve` | "look at" / "examine" | | `Additionally` | Delete | --- ## Batch mode To humanize multiple files: ```bash # Scan all markdown files in drafts/ /humanizer --scan drafts/*.md # Fix all files (with confirmation) /humanizer --batch drafts/ ``` Output format for batch: ```text ## Batch humanization report drafts/post-1.md HIGH 3 | MEDIUM 5 | LOW 2 drafts/post-2.md HIGH 1 | MEDIUM 3 | LOW 4 drafts/post-3.md Clean! No issues found. Total: 3 files, 18 issues ``` --- ## Sources Based on: - [Wikipedia: Signs of AI writing](https://en.wikipedia.org/wiki/Wikipedia:Signs_of_AI_writing) - [GitHub: blader/humanizer](https://github.com/blader/humanizer) - Original research on crypto/Web3 AI patterns 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." --- *Version 1.2.0 | Created for 0G Labs content team*
識別並去掉文字里的 AI 寫作痕跡,讓文字讀起來更像人寫。
把文字里 AI 寫作的典型痕跡挑出來並改寫得更自然,同時保留原意的寫作編輯技能。
識別並去除 AI 生成文字痕跡的中文文字編輯技能。
wechat-search 檢索公眾號熱門文章,並按相關性、熱度和時效整理結果。
從公開短影片分享連結提取標題、簡介和口播文案,並給出改寫版本。
humanizer 為中英文文字提供更自然的表達和風格編輯指導。
寫網文章節並按檔案落盤,聊天裡只回摘要與指標。
把一組行銷方法模組收進同一個技能,按請求路由到對應模組取清單與可交付稿。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。