MCPInstall

humanize-it

对指定文档进行去 AI 味的改写。自动选择最合适的人性化策略(humanizer-zh / humanize-chinese / technical-writing), 迭代改写直到效果达标或迭代 42 次为止。适用于中文文本的去 AI 化处理,包括通用文章、技术文档、学术论文等。 Use when user says: "humanize this", "去AI味", "降AIGC", "人性化改写", "改成人话", "去除AI痕迹", "humanize document", "make text human-like", "去机器味", "降低AI率", "过AIGC检测"

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Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/smallnest/goal-workflow --skill humanize-it
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads humanize-it automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

Humanize-It: 迭代式去 AI 味改写

对指定文档进行去 AI 味的改写。根据文本类型和内容,从三个子 skill 中自动选择最合适的一个开始改写。如果改写效果不满意,换用另一个 skill 继续迭代,直到效果达标或达到 42 次迭代上限。

子 Skill 能力矩阵

Skill适用场景核心能力改写风格
humanizer-zh通用文本、文章、博客、文案识别 24+ AI 写作模式,注入个性与灵魂,节奏变化自然、有温度、带观点
humanize-chinese通用 + 学术 + 长文本20+ 规则检测 + 统计特征 + LR 融合评分,CLI 工具链多种风格可选(知乎/小红书/学术/文学等)
technical-writing技术文档、架构说明、设计稿、评审文档去除技术黑话,证据先行,消除主持腔平实、严谨、可论证

工作流程

第一步:读取文档并分析

  1. 读取用户指定的文档内容
  2. 判断文档类型:
    • 技术文档(技术方案、架构说明、设计文档、评审稿)→ 优先使用 technical-writing
    • 学术论文(论文、研究文章)→ 优先使用 humanize-chinese(学术模式)
    • 通用文本(博客、文案、文章)→ 优先使用 humanizer-zh
    • 长文本(≥1500 字)→ 优先使用 humanize-chinese(长文本模式)

第二步:改写策略选择

根据文档类型选择第一个改写 skill:

文档类型判断:
├── 技术文档 → technical-writing → humanizer-zh → humanize-chinese
├── 学术论文 → humanize-chinese(academic) → humanizer-zh → technical-writing
├── 通用文本 → humanizer-zh → humanize-chinese → technical-writing
└── 长文本(≥1500字) → humanize-chinese(longform) → humanizer-zh → technical-writing

第三步:迭代改写循环

iteration = 0
MAX_ITERATIONS = 42

while iteration < MAX_ITERATIONS:
    iteration += 1

    # 使用当前 skill 进行改写
    result = humanize(current_text, current_skill)

    # 评估改写效果
    score = evaluate(result)

    if score >= PASS_THRESHOLD:
        # 改写效果达标,输出最终结果
        output(result)
        break

    # 效果不达标,切换到下一个 skill
    current_skill = next_skill(skill_order)
    current_text = result  # 在上次改写基础上继续优化

    if all_skills_exhausted():
        # 所有 skill 都用过一轮,从头开始新一轮组合
        current_skill = first_skill(skill_order)

第四步:质量评估

每次改写后,按以下维度评估效果(百分制):

维度权重评估标准
AI 痕迹去除30%三段式、套话、机械连接词是否消除
自然度25%读起来是否像人写的,节奏是否自然
信息完整20%核心信息是否保留,没有丢失关键内容
风格一致15%语气是否前后统一,符合文档类型
可读性10%句子是否通顺,逻辑是否清晰

评分标准:

  • ≥ 80 分:通过,输出结果
  • 60-79 分:尚可,再迭代一轮看能否提升
  • < 60 分:不达标,必须继续改写

第五步:输出结果

输出最终改写结果,附带:

  1. 改写后的完整文本(写入原文件或指定输出文件)
  2. 改写摘要(使用了哪些 skill,迭代了几次,最终评分)
  3. 主要改动点列表

具体执行指令

调用 humanizer-zh 时

使用 Skill 工具调用 humanizer-zh,将文档内容传入,让其按 24 种 AI 写作模式进行检测和改写。重点关注:

  • 删除填充短语
  • 打破公式结构
  • 变化节奏
  • 信任读者
  • 删除金句
  • 注入个性与灵魂

改写后按其 50 分制质量评分进行初步评估(≥ 40 分为达标)。

调用 humanize-chinese 时

使用 Skill 工具调用 humanize-chinese,根据文档类型选择对应模式:

  • 通用文本:使用 detect + rewrite 流程
  • 学术论文:使用 academic 模式
  • 长文本:使用 --scene novel 或 --scene auto

如果 CLI 工具可用,优先使用 CLI 进行量化检测和改写;否则按其 LLM 使用指南手动执行。

改写后按其 0-100 分评分体系评估(≤ 35 分为 LOW 区间,达标)。

调用 technical-writing 时

使用 Skill 工具调用 technical-writing,主要用于技术文档的改写。重点关注:

  • 去除 buzzword 黑名单中的词汇
  • 消除主持腔和评价腔
  • 按「条件 → 对象 → 判断」重写句子
  • 证据先行,减少无支撑的强判断
  • 去除过场句

迭代策略细节

何时切换 Skill

  1. 同一个 skill 连续改写 3 次评分无提升 → 切换到下一个 skill
  2. 评分下降 → 回退到上一个版本,切换 skill
  3. 所有 skill 都用完一轮但未达标 → 从第一个 skill 重新开始,但使用上一轮的改写结果作为输入
  4. 达到 42 次迭代 → 输出当前最佳结果

组合策略

不同 skill 的改写侧重不同,组合使用可以互补:

  • humanizer-zh → humanize-chinese:先注入个性灵魂,再做量化去 AI 模式
  • humanize-chinese → humanizer-zh:先做系统化去 AI,再注入温度
  • technical-writing → humanizer-zh:先保证技术严谨性,再增加自然度
  • humanizer-zh → technical-writing:先去除通用 AI 痕迹,再调整技术语气

用户交互

如果用户提供了明确的偏好(如"保持学术风格"、"要更口语化"、"技术文档不要太随意"),在改写时遵循用户偏好,并优先选择对应的 skill。

如果用户未指定文档类型,可以通过 AskUserQuestion 询问:

  • 文档类型(通用 / 技术 / 学术)
  • 期望的改写风格(自然随意 / 平实严谨 / 学术规范)
  • 是否需要写入原文件还是输出到新文件

FAQ

What does the humanize-it skill do?

对指定文档进行去 AI 味的改写。自动选择最合适的人性化策略(humanizer-zh / humanize-chinese / technical-writing), 迭代改写直到效果达标或迭代 42 次为止。适用于中文文本的去 AI 化处理,包括通用文章、技术文档、学术论文等。 Use when user says: "humanize this", "去AI味", "降AIGC", "人性化改写", "改成人话", "去除AI痕迹", "humanize document", "make text human-like", "去机器味", "降低AI率", "过AIGC检测"

How do I install humanize-it?

Run npx skills add https://github.com/smallnest/goal-workflow --skill humanize-it in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/humanize-it/ (personal) or .claude/skills/humanize-it/ (project).

Which AI agents can use humanize-it?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is humanize-it safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains humanize-it?

It is published by smallnest in smallnest/goal-workflow. It has 534 recorded installs.

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