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humanize-ai-text-cp3d人性化 ai 文本 cp3d

Agent Skill

humanize-ai-text-cp3d 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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下载量

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OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:humanize-ai-text-cp3d(人性化 ai 文本 cp3d)
来源仓库:https://github.com/cp3d1455926-svg/humanize-ai-text-cp3d
安装命令:
openclaw skills install humanize-ai-text-cp3d
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install humanize-ai-text-cp3d

简介

通过诊断报告和版本比较,检测并删除人工智能生成的书写模式,以重写文本,形成更自然、更人性化的书写风格。

SKILL.md

name
humanize-ai-text
description
Remove signs of AI-generated writing from text. Detects AI vocabulary, puffery, and chatbot artifacts.
author
@biostartechnology
version
1.0.0
license
MIT
metadata
{"clawdbot":{"emoji":"✍️","requires":{"bins":["python3"]}}}

Humanize AI Text

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written.

Based on Wikipedia's comprehensive "Signs of AI writing" guide.

Features

  • AI Detection: Identifies 16 pattern categories of AI-generated text
  • Pattern Categories:

- Citation bugs - Knowledge-cutoff phrases - Chatbot artifacts - Markdown/code remnants - AI-specific vocabulary - Filler phrases - Punctuation quirks - Stylistic parallelisms - Inflated symbolism - Promotional language - Superficial -ing analyses - Vague attributions - Em dash overuse - Rule of three - Negative parallelisms - Excessive conjunctive phrases

  • Diagnostic Reports: Generate detailed AI detection reports
  • Text Transformation: Rewrite text to sound more human
  • Comparison Mode: Compare original vs humanized versions

Usage

Detect AI Writing

# Basic detection
python skills/humanize-ai-text/scripts/detect.py text.txt

# JSON output
python skills/humanize-ai-text/scripts/detect.py text.txt -j

# Score only
python skills/humanize-ai-text/scripts/detect.py text.txt -s

# Pipe text directly
echo "This text might be AI-generated" | python skills/humanize-ai-text/scripts/detect.py

Transform Text

# Basic transformation
python skills/humanize-ai-text/scripts/transform.py text.txt

# Output to file
python skills/humanize-ai-text/scripts/transform.py text.txt -o clean.txt

# Aggressive mode (more changes)
python skills/humanize-ai-text/scripts/transform.py text.txt -a

# Quiet mode (no progress output)
python skills/humanize-ai-text/scripts/transform.py text.txt -q

Compare Versions

# Compare original and transformed
python skills/humanize-ai-text/scripts/compare.py text.txt

# Compare and save result
python skills/humanize-ai-text/scripts/compare.py text.txt -o document_v2.txt

Installation

The skill is already installed. To use it, ensure you have Python 3 installed.

Dependencies

No external dependencies required - uses Python standard library.

Pattern Detection

The detection script identifies these AI writing patterns:

1. Citation Bugs

  • Fake or unverifiable sources
  • "According to experts" without specifics
  • Generic study references

2. Knowledge Cutoff

  • "As of my last update"
  • "I don't have real-time information"
  • Date-stamped limitations

3. Chatbot Artifacts

  • "I'd be happy to help"
  • "Great question!"
  • "Let me break this down"
  • Excessive hedging

4. AI Vocabulary

  • "delve into"
  • "testament to"
  • "in conclusion"
  • "it's worth noting"
  • "important to understand"

5. Filler Phrases

  • Unnecessary introductions
  • Redundant summaries
  • Padding content

6. Stylistic Issues

  • Rule of three overuse
  • Negative parallelisms
  • Em dash overuse
  • Excessive conjunctive phrases

Best Practices

  1. Detect First: Run detection before transformation
  2. Review Changes: Always review transformed text
  3. Use Compare: Compare versions to understand changes
  4. Iterate: May need multiple passes for best results
  5. Custom Patterns: Edit patterns.json to add custom detections

Customization

Add Custom Patterns

Edit skills/humanize-ai-text/scripts/patterns.json:

{
  "custom_patterns": {
    "my_pattern": {
      "regex": "pattern_here",
      "replacement": "replacement_text",
      "description": "What this pattern detects"
    }
  }
}

Batch Processing

Process multiple files:

for f in *.md; do
  python skills/humanize-ai-text/scripts/detect.py "$f" -s
  python skills/humanize-ai-text/scripts/transform.py "$f" -a -o "${f%.md}_clean.md" -q
done

Output Formats

Detection Output

AI Detection Report
===================
File: text.txt
AI Probability: 73%

Patterns Detected:
- AI Vocabulary: 12 instances
- Filler Phrases: 8 instances
- Stylistic Parallelisms: 5 instances
...

Transformation Output

Original: "I'd be happy to delve into this important topic."
Humanized: "Let's explore this topic."

Security Notes

  • ✅ No external network calls
  • ✅ All processing done locally
  • ✅ No credential access
  • ✅ Safe file operations only
  • ✅ No data exfiltration

Integration

With Writing Workflow

  1. Write draft (AI-assisted or not)
  2. Run detection to check AI score
  3. Transform if score is high
  4. Compare versions
  5. Manual review and final edits

With Content Pipeline

# In CI/CD or pre-commit hook
python skills/humanize-ai-text/scripts/detect.py content.md -s
# Fail if AI score > threshold

Troubleshooting

False Positives

Some legitimate writing may trigger patterns. Review manually.

False Negatives

AI models evolve. Update patterns.json regularly.

Encoding Issues

Ensure files are UTF-8 encoded:

python skills/humanize-ai-text/scripts/detect.py file.txt --encoding utf-8

Examples

Example 1: Blog Post

# Check AI score
python skills/humanize-ai-text/scripts/detect.py blog_post.md -s
# Output: AI Probability: 68%

# Transform
python skills/humanize-ai-text/scripts/transform.py blog_post.md -o blog_post_clean.md -a

# Compare
python skills/humanize-ai-text/scripts/compare.py blog_post.md -o blog_post_clean.md

Example 2: Email

echo "I hope this email finds you well. I wanted to reach out regarding..." | \
  python skills/humanize-ai-text/scripts/detect.py

Example 3: Academic Writing

# Detect AI patterns in paper
python skills/humanize-ai-text/scripts/detect.py paper.md -j > report.json

# Transform with conservative settings
python skills/humanize-ai-text/scripts/transform.py paper.md -o paper_clean.md

Resources

  • Wikipedia: "Signs of AI writing"
  • Original research on AI text detection
  • Community pattern contributions

*For more info, visit: https://clawhub.ai/biostartechnology/humanizer*

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

77.68%
按下载量换算1,317

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VirusTotal

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可疑

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安装前确认

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