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Agent Skill · 开发

humanize(humanize 搜索)

humanize 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

humanize 是开发类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 18,691。

总安装 321周安装 13GitHub Stars 95下载 101核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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(humanize 搜索)
来源仓库:https://github.com/rfxlamia/claude-skillkit
仓库路径:skills/humanize
安装命令:
npx skills add https://github.com/rfxlamia/claude-skillkit --skill humanize
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/rfxlamia/claude-skillkit --skill humanize

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

humanize 用于处理 GitHub 仓库、Issue 和 Pull Request 协作信息,支持代码变更跟踪。适用于协作事项管理和代码状态同步场景。可通过 npx 命令从 claude-skillkit 仓库安装,建议查阅原始 README 了解详细用法。使用前需确认权限边界,避免访问受限仓库或敏感提交记录。

输出内容应基于公开协作数据,不擅自解读私有分支或非公开讨论。

来源仓库内路径:skills/humanize

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/rfxlamia/claude-skillkit --skill humanize;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

humanize 怎么安装?

在终端执行 npx skills add https://github.com/rfxlamia/claude-skillkit --skill humanize。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

humanize 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

humanize 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

humanize 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

humanize 用的人多吗?

公开数据是累计安装 321 次,近一周安装 13 次,下载 101 次,GitHub 95 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

humanize 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
humanize

humanize 搜索 · 本页

32195需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Humanize Docs

Overview

This skill transforms robotic AI-generated documentation into prose that sounds like an actual human wrote it. Think: destroying checkbox spam, dismantling perfect paragraph structures, and injecting the kind of conversational flow you'd get from a colleague explaining something over coffee.

The approach is aggressive deformalization - not just tweaking tone, but fundamentally restructuring how information flows to break AI's predictable patterns.

When You Need This

Clear signals you're dealing with AI-generated docs:

  • Checkbox overload: - [x] Task 1: Do the thing (AC: #1)
  • CAPS LOCK emphasis for CRITICAL IMPORTANT NOTES
  • 8+ code templates embedded in a single document
  • Every section has exactly 3 perfectly balanced paragraphs
  • Headers like "LLM Developer Guardrails" (literally instructions for robots)
  • Phrases: "Certainly, here is...", "It's important to note that...", "Furthermore..."

Examples from the wild:

  • AI agent documentation (like your Flutter Story example)
  • Auto-generated API specs
  • Claude Code project scaffolds
  • ChatGPT-written technical guides

Transformation Workflow

Step 1: Detect AI Patterns

Before transforming, confirm you're actually dealing with AI output. Load the detection checklist:

[See references/detection-patterns.md for complete list]

Quick test: Does the doc have 5+ of these?

  • Perfect structural symmetry (every section same length)
  • Zero sentence length variation (all 15-20 words)
  • Checkbox addiction
  • Template embedding mania
  • Emotional flatness (no "wait, why?" or "honestly...")

If yes → proceed. If no → might already be human-written, be careful.

Step 2: Apply Core Transformations

Execute transformations in order. Each pattern targets specific AI signatures:

[See references/core-transformations.md for detailed rules]

Quick reference:

  1. Burstiness Injection → Mix 5-word punches with 30-word reflections
  2. Structure Dismantling → Break perfect 3-paragraph blocks, add digressions
  3. Checkbox Annihilation → Convert to flowing prose with "anyway, you'll need..."
  4. Template Contextualization → Replace code dumps with "here's what worked for me..."
  5. Vocabulary Swap → Kill "utilize/leverage/facilitate", use "use/use/help"

Critical rule: Don't apply all transformations everywhere. Humans are inconsistent - some sections stay formal, others get playful. That's the point.

Step 3: Quality Check

Read the output aloud (or mouth the words). Does it sound like you'd actually say this to someone?

Red flags the transformation failed:

  • Still too even (every paragraph same vibe)
  • No variation in sentence rhythm
  • Feels like a "professional robot" instead of "casual robot"
  • You removed personality instead of adding it

Good signals:

  • Some sentences feel almost too casual (then you toned it back)
  • You had to resist adding MORE jokes
  • It reads faster than before
  • You can hear a specific person's voice

Step 4: Domain Adjustments (Optional)

Different doc types need different intensity levels:

High personality OK:

  • READMEs for open source projects
  • Internal team documentation
  • Tutorial blog posts
  • Onboarding guides

Moderate personality:

  • API documentation
  • User-facing help docs
  • Technical specifications

Gentle touch only:

  • Legal/compliance docs (seriously, be careful)
  • Medical/safety documentation
  • Financial reports

[See references/examples-gallery.md for before/after samples]

Quick Mode (30 seconds)

If you just need to make something readable without full transformation:

  1. Kill the checkboxes → flowing list with "you'll need: X, Y, and Z"
  2. Replace one CAPS LOCK section → italics with context
  3. Add one burstiness break → throw in a 5-word sentence after a long paragraph
  4. Swap 3-5 AI vocabulary words → utilize→use, leverage→use, facilitate→help

Done. Not perfect, but 70% better readability.

Examples

Input (AI-generated):

## Task 2: Configure Dependencies

**CRITICAL**: The following steps MUST be completed in order.

- [x] Install package A (required for Task 3)
- [x] Verify installation with command X
- [x] Proceed to next task only after confirmation

It is important to note that failure to follow these steps will result in errors.

Output (Humanized):

## Setting Up Dependencies

Okay, you'll need to install package A first - and yeah, this actually matters because
Task 3 depends on it. Run command X to verify it worked.

Once you get the confirmation, you're good to move on. If it errors out, the next step
will definitely break, so... don't skip this.

Notice:

  • Checkbox death ✅
  • "Okay" intro (conversational)
  • Sentence length variation (short → long → medium)
  • "yeah, this actually matters" (human aside)
  • "so... don't skip this" (trailing thought)
  • Kept the warning but made it sound real

Common Mistakes

Don't:

  • Remove ALL structure (humans still use headers)
  • Make everything casual (inconsistency is human)
  • Add emojis (that's a different kind of AI spam)
  • Force humor (spontaneous > trying hard)
  • Ignore domain context (legal docs stay formal)

Do:

  • Vary your transformation intensity
  • Keep some sections more formal for contrast
  • Read aloud to check naturalness
  • Preserve technical accuracy above all
  • Trust your instinct on "too much"

References

This skill uses reference documentation loaded into context:

core-transformations.md

The 5 core transformation patterns with detailed rules, examples, and edge cases. Load this for complex transformations or when you need to understand WHY a pattern works.

detection-patterns.md

Complete AI signature checklist with detection heuristics. Load when you're unsure if a doc needs transformation or want to explain what makes text feel "AI-generated".

examples-gallery.md

Before/after transformation showcase across different document types (technical guides, READMEs, API docs). Load for inspiration or to calibrate transformation intensity.

advanced-techniques.md

Future: Domain-specific adjustments for legal, academic, and specialized documentation.


Philosophy: AI writes like it's afraid to break rules. Humans write like they're explaining something to a friend while occasionally remembering they should probably sound professional. Capture that tension.

平台分布

Claude

32.87%
按下载量换算33

Codex

31.87%
按下载量换算32

Cursor

18.21%
按下载量换算18

Gemini CLI

10.25%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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