据 AlphaMoat 统计,截至 2026-09,Humanizer Enhanced 累计下载 3,020 次、获 1 个星标,在全部 5,078 个 AI 技能中排名第 3,718 位,在「内容创作」分类(362 个)中排名第 246 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 75 | 2,630 | - | - |
| SkillHub ↗ | 165 | 3,020 | 1 | — |
各平台的计数口径不同,统计时间不一致。
该技能会按严重程度标记其认为类似 AI 写作的表达,并可建议修改、调整可读性和语气。主文要求先向用户确认再应用修复。技能卡提示改写可能显著改变原文语气、格式、事实细节或归属;发布前应对照原文检查来源、日期和主张,尤其核验统计信息及加密/Web3内容。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 3,020 | — | 1 |
| 2026-08 | 2,548 | +6.7% | 1 |
| 2026-07 | 2,388 | +17.1% | 1 |
| 2026-06 | 2,040 | +7.3% | 1 |
| 2026-05 | 1,902 | — | 1 |
| 2026-03 | 1,272 | — | - |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 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*
识别并去掉文本里的 AI 写作痕迹,让文字读起来更像人写。
把文本里 AI 写作的典型痕迹挑出来并改写得更自然,同时保留原意的写作编辑技能。
识别并去除 AI 生成文本痕迹的中文文字编辑技能。
wechat-search 检索公众号热门文章,并按相关性、热度和时效整理结果。
从公开短视频分享链接提取标题、简介和口播文案,并给出改写版本。
humanizer 为中英文文本提供更自然的表达和风格编辑指导。
写网文章节并按文件落盘,聊天里只回摘要与指针。
把一组营销方法模块收进同一个技能,按请求路由到对应模块取清单与可交付稿。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。