dorukardahan

Humanizer Enhanced

内容创作v1.0.0
作者:dorukardahan更新于 2026-05-17humanizer-enhanced@clawhub_dorukardahan/humanizer-enhanced
文章写作内容改写#Batch#Crypto

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。

累计安装
165
累计下载
3,020
星标
1
全站排名
#3,718
全站前 74% · 「内容创作」前 68%
平台累计安装累计下载星标评论
ClawHub ↗752,630--
SkillHub ↗1653,0201—

各平台的计数口径不同,统计时间不一致。

这个技能是做什么的

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

可以用来做什么

  • 扫描博客、文章或草稿中的写作模式
  • 查看按严重程度整理的问题和修改建议
  • 在审核后改进可读性与表达

什么时候用

  • 需要审阅草稿并获得可选编辑建议时
  • 应用批量或实质性改写前已检查修改范围,并计划复核事实、引用和作者语气时

示例提示词

以下是根据技能文档生成的示例,不代表实际运行结果。

先扫描这份草稿并列出问题,不要修改文件;逐项说明可能影响的语气或事实归属,等待我确认后再应用任何改写。

月度数据趋势

累计下载3,020
1,1322,1463,1602026-03 · 累计下载 1,2722026-05 · 累计下载 1,9022026-06 · 累计下载 2,0402026-07 · 累计下载 2,3882026-08 · 累计下载 2,5482026-09 · 累计下载 3,02026-0326-09
星标1
0112026-03 · 星标 -2026-05 · 星标 12026-06 · 星标 12026-07 · 星标 12026-08 · 星标 12026-09 · 星标 126-0326-09

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
2026-093,020—1
2026-082,548+6.7%1
2026-072,388+17.1%1
2026-062,040+7.3%1
2026-051,902—1
2026-031,272—-

SKILL.md 原文

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。

8.2 KB · ClawHub v1.0.0
---
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.
展开全部(共 204 行)
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*

「内容创作」分类下的热门技能

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。