AlphaMoatによると、2026-09時点でHumanizer Enhancedのダウンロード数は3,020、スター数は1で、AIスキル全体5,078件中3,718位、コンテンツ制作では362件中246位です。
| プラットフォーム | インストール数 | ダウンロード数 | スター数 | コメント |
|---|---|---|---|---|
| ClawHub ↗ | 75 | 2630 | - | - |
| SkillHub ↗ | 165 | 3020 | 1 | — |
プラットフォームごとに集計方法と集計時点が異なります。
このスキルはAI文体に似ていると判断した表現を重大度別に示し、読みやすさや語調を改善する編集案を提示できます。主文では修正を適用する前にユーザーの承認を求めています。カードによると、改稿によって語調、書式、事実のニュアンス、帰属が大きく変わる可能性があります。公開前に原文と照合して出典、日付、主張を確認し、特に統計や暗号資産・Web3に関する記述を検証してください。
資料公開日 2026-10-27
スキルのドキュメントをもとに生成した例であり、実際の実行結果ではありません。
2026-09 から集計方法を変更し、同名スキルを作者ごとに分けて集計し、全スキルを対象にしました。破線は変更前の月で、変更後のデータとは直接比較せず、変更をまたぐ増減も計算していません。
| 月 | ダウンロード数 | 前月比 | スター数 |
|---|---|---|---|
| 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 | — | - |
作者が公開した元のファイルをテキストのまま表示しています。AlphaMoat による編集や審査はしていません。リンクはクリックできません。コマンドは内容を確認してから実行してください。取得日 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*
文章に残る AI らしさを見つけて取り除き、人が書いたように読める文章にします。
AI が書いた文章の典型的な痕跡を見つけ、意味を保ったまま自然な文章に書き直す文章編集スキルです。
AI が生成した文章の痕跡を見つけて取り除く中国語の編集スキルです。
wechat-search は WeChat の人気記事を検索し、関連度、人気、鮮度で結果を整理します。
公開された短編動画の共有リンクからタイトル、概要、口播テキストを抽出し、改写版も作ります。
humanizer は中国語と英語の文章を自然な表現に整えるための編集ガイドです。
Web 小説の各章をファイルに書き、会話では要約と位置だけを返します。
複数のマーケティング手法をひとつのスキルにまとめ、依頼内容に合うモジュールへ振り分けるスキルです。
データ月:2026-09 · ダウンロード数、スター数、インストール数は公開スキルレジストリ(ClawHub、SkillHub)から月単位で集計しています。詳しくはデータの方法論をご覧ください。