诊断生产力系统反复失效的根因,给出最小干预——容量测算、瓶颈定位、可靠的本地记录。
编程
AI Text Humanizer
试用Remove signs of AI-generated writing from text via the Claw0x API. Use when the user asks to humanize text, make AI writing sound natural, remove AI patterns...
它能做什么
Rewrite AI-generated text to remove robotic patterns and make it sound naturally human. Targets 24 known AI writing signatures including filler phrases, AI vocabulary, sycophantic tone, and formulaic structure.
技能文档
AI Text Humanizer
Rewrite AI-generated text to remove robotic patterns and make it sound naturally human. Targets 24 known AI writing signatures including filler phrases, AI vocabulary, sycophantic tone, and formulaic structure.
How It Works — Under the Hood
This skill uses a two-layer architecture to transform AI-generated text into human-sounding prose:
Layer 1: LLM Rewriting (Primary)
The primary path sends your text to a large language model (Gemini) with a carefully engineered system prompt derived from Wikipedia's WikiProject AI Cleanup guide. The LLM API key (GEMINI_API_KEY) is managed server-side by the Claw0x platform — callers do not need to provide or configure it. You only need a CLAW0X_API_KEY to authenticate through the Gateway. The system prompt instructs the model to:
- Scan the input for all 24 known AI writing patterns
- Rewrite the text to eliminate those patterns while preserving meaning
- Audit the rewritten output for any lingering AI-isms
- Revise a second time to catch patterns that survived the first pass
The LLM is also given personality rules: have opinions, vary sentence rhythm, acknowledge complexity, use "I" when natural, and let some structural imperfection through.
Layer 2: Regex Fallback (Deterministic)
If the LLM is unavailable (rate limit, timeout), the skill falls back to a deterministic regex engine that applies pattern-matched replacements across six categories:
- Chatbot artifacts — removes "I hope this helps!", "Let me know if..."
- Filler phrases — "in order to" → "to", "due to the fact that" → "because"
- Significance inflation — "marking a pivotal moment" → removed
- Copula avoidance — "serves as" → "is"
- AI vocabulary — 40+ word substitutions (e.g. "leverage" → "use")
- Emoji removal and em-dash normalization
The regex path is lower quality but instant, deterministic, and zero-cost.
Prerequisites
This skill requires a Claw0x API key:
- Sign up at claw0x.com
- Go to Dashboard → API Keys → Create Key
- Store the key securely using one of these methods:
- Add
CLAW0X_API_KEYto your agent's secure environment variables - Use your platform's secret manager (e.g. GitHub Secrets, Vercel env vars)
- Use a
.envfile excluded from version control via.gitignore
- Add
Security note: Never embed API keys in prompts, source code, or version-controlled files.
When to Use
- User says "humanize this", "make this sound more natural", "remove AI patterns"
- User wants text to pass AI detection tools (GPTZero, Originality.ai, etc.)
- Agent pipeline produces text that needs to sound human-written
- Content teams need to clean up AI-drafted blog posts, emails, or documentation
API Call
curl -s -X POST https://claw0x.com/v1/call \
-H "Authorization: Bearer $CLAW0X_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"skill": "humanizer",
"input": {
"text": "Your AI-generated text here..."
}
}'
Input
The input field accepts an object with one of these keys:
| Field | Type | Required | Description |
|---|---|---|---|
input.text | string | yes (one of) | Text to humanize |
input.content | string | yes (one of) | Alternative key for the text |
input.body | string | yes (one of) | Alternative key for the text |
Output Fields
| Field | Type | Description |
|---|---|---|
humanized_text | string | The rewritten text with AI patterns removed |
original_length | number | Character count of original text |
humanized_length | number | Character count of humanized text |
method | string | "llm" (AI rewrite) or "regex" (deterministic fallback) |
Example
Input:
{
"skill": "humanizer",
"input": {
"text": "Additionally, it is worth noting that this groundbreaking solution serves as a testament to the transformative power of innovation. The future looks bright for this pivotal technology. I hope this helps!"
}
}
Output:
{
"humanized_text": "This solution shows what good engineering looks like in practice. The technology has real potential, though how it plays out depends on adoption.",
"original_length": 204,
"humanized_length": 138,
"method": "llm"
}
Error Codes
400— Missing or empty text input500— Processing failed (not billed)
Pricing
Pay-per-successful-call only. Failed calls and 5xx errors are never charged.
相关技能
按用户明确指令,在得到大脑(Get笔记)中保存、搜索并管理笔记与知识库。
通过 use_figma MCP 在 Figma 文件中执行 Plugin API 代码时所需的规则与避坑清单。
按官方风格搭建与评审 ASP.NET Core 应用,覆盖从应用模型选型到上线部署的完整链路。
起草智能体技能,并通过带技能与基线的并行测试不断迭代改进。
为 Codex 搭一个可在任意目录下按命令名运行的长期 CLI,提供组合式子命令和稳定 JSON 输出。
kennyzir 的更多技能
浏览全部技能Meta-skill for AI agent self-improvement. Analyzes runtime logs to detect error patterns, regressions, and inefficiencies, then generates structured improvem...
Local skill for capturing learnings, errors, corrections, and patterns to enable continuous agent improvement. Processes events locally in your OpenClaw agen...
Scan AI agent skills for security vulnerabilities, dangerous code patterns, and undeclared permissions. Three-layer analysis: dependency CVE scanning, static...
Teach your OpenClaw agent new tricks by creating custom skills. Use when you want your agent to do something it can't do yet — like "read my Google Calendar"...
Validate email addresses with format checking and risk scoring. Use when users need to verify email format, check disposable emails, or validate bulk email l...
Advanced web search with precise date filtering and content type selection. Use when you need academic papers, GitHub repositories, research content, or spec...