Chinese Technical Writing
leter/zh-tech-writing
Sets writing rules for Chinese technical docs: short plain sentences, consistent typography and a checklist for removing AI-sounding filler.
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。
Install Humanize It
$ npx skills add smallnest/goal-workflow --skill humanize-it -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install smallnest/goal-workflow humanize-it --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/humanize-it .claude/skills/humanize-it && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .claude/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-itType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add smallnest/goal-workflow --skill humanize-it -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install smallnest/goal-workflow humanize-it --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/humanize-it .agents/skills/humanize-it && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .agents/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add smallnest/goal-workflow --skill humanize-it -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install smallnest/goal-workflow humanize-it --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/humanize-it .cursor/skills/humanize-it && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .cursor/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/smallnest/goal-workflow.git --path skills/humanize-it--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add smallnest/goal-workflow --skill humanize-it -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install smallnest/goal-workflow humanize-it --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/humanize-it .gemini/skills/humanize-it && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .gemini/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install smallnest/goal-workflow humanize-itInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add smallnest/goal-workflow --skill humanize-it -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/humanize-it .github/skills/humanize-it && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .github/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add smallnest/goal-workflow --skill humanize-it -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install smallnest/goal-workflow humanize-it --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/smallnest/goal-workflow.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/humanize-it .opencode/skills/humanize-it && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "humanize-it" agent skill from https://github.com/smallnest/goal-workflow/tree/master/skills/humanize-it into .opencode/skills/humanize-it/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "humanize-it", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
humanize-it- GitHub stars
- 288
- Token cost
- ~957 tokens
- SKILL.md length
- 232 words
- Files
- 1
- Skills in repo
- 20
- Repo updated
- First seen
- Licence
- MIT
At a glance
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。
- Works in 2 steps: 读取用户指定的文档内容 → 判断文档类型
- User says: humanize this
- SKILL.md covers 子 Skill 能力矩阵, 工作流程, 具体执行指令 and 迭代策略细节, plus 1 more section
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Humanize It is an agent skill from smallnest/goal-workflow. 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"
Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Writing & Content, covering Humanizing AI text and Technical writing. The repository describes itself as: AI-driven development workflow with /prd, /goal, /review-it and /ship-it skills. The licence is MIT.
When your agent uses it
- User says: humanize this
- Humanize document
- Make text human-like
Example prompts
- “humanize this”
- “去除AI痕迹”
- “humanize document”
- “/humanize-it”
Requirements
- Pre-approved tools (allowed-tools): Read, Write, Edit, AskUserQuestion, Skill
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- 读取用户指定的文档内容
- 判断文档类型
What it can do on your machine
Read from SKILL.md and the folder at commit b06ab3c. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditAskUserQuestionSkill
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Humanize It loads about 957 tokens when it runs. Until then it costs about 77 tokens; SKILL.md has 232 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from smallnest/goal-workflow at commit b06ab3c, republished under its MIT licence (© smallnest). 232 words, ~957 tokens.
Download SKILL.mdSave it as
.claude/skills/humanize-it/SKILL.md (or your agent's skills folder).- name
- humanize-it
- description
- 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"
- allowed-tools
- Read, Write, Edit, AskUserQuestion, Skill
- user-invocable
- true
- metadata.trigger
- 去AI味改写文档、humanize document、降AIGC、人性化文本
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
- 读取用户指定的文档内容
- 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）
- 技术文档（技术方案、架构说明、设计文档、评审稿）→ 优先使用
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：
- 改写后的完整文本（写入原文件或指定输出文件）
- 改写摘要（使用了哪些 skill，迭代了几次，最终评分）
- 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
- 同一个 skill 连续改写 3 次评分无提升 → 切换到下一个 skill
- 评分下降 → 回退到上一个版本，切换 skill
- 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
- 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
© smallnest, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/humanize-it of smallnest/goal-workflow.
Open the folder on GitHubat commit b06ab3c
Compare with similar skills
Humanize It next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Humanize It this skillsmallnest/goal-workflow | 288 | — | ~957 | Automated safety check: Pass | MIT | |
| Chinese Technical Writingleter/zh-tech-writing | 332 | — | ~656 | Automated safety check: Pass | MIT | |
| evlog Content Writingevloghq/evlog | 1.9k | — | ~2.9k | Automated safety check: Pass | MIT | |
| Declaudingoaustegard/claude-skills | 150 | — | ~5.1k | Automated safety check: Pass | MIT | |
| Vibe WritingYiShu5/claude-skills | 132 | — | ~985 | Automated safety check: Pass | MIT | |
| Natural Writing Enmizchi/skills | 356 | — | ~3.9k | Automated safety check: Pass | None |
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Categories
Questions about Humanize It
What does Humanize It 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。. Humanize It is an agent skill from smallnest/goal-workflow.
When should I use Humanize It?
Humanize It fits situations like: user says: humanize this; humanize document; make text human-like.
How do I install Humanize It in Claude Code?
Run `npx skills add smallnest/goal-workflow --skill humanize-it -a claude-code`. Or copy the skill folder (skills/humanize-it in smallnest/goal-workflow) into .claude/skills/humanize-it in your project. Claude Code loads it when a task matches its description.
How do I install Humanize It in Codex?
Run `npx skills add smallnest/goal-workflow --skill humanize-it -a codex`. Or copy the skill folder (skills/humanize-it in smallnest/goal-workflow) into .agents/skills/humanize-it in your project. Codex loads it when a task matches its description.
Can I use Humanize It in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add smallnest/goal-workflow --skill humanize-it -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/humanize-it, .gemini/skills/humanize-it, .github/skills/humanize-it and .opencode/skills/humanize-it in your project.
What does Humanize It need to run?
SKILL.md names no scripts, command-line tools or credentials: Humanize It is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, AskUserQuestion, Skill.
Does Humanize It access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Humanize It safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Humanize It use?
Humanize It is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Humanize It use?
About 957 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Humanize It?
Skills that share tags, products or a category with Humanize It: Chinese Technical Writing (leter/zh-tech-writing, 332 stars), evlog Content Writing (evloghq/evlog, 1.9k stars), Declauding (oaustegard/claude-skills, 150 stars) and Vibe Writing (YiShu5/claude-skills, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Humanize It?
smallnest (a GitHub user) maintains it in smallnest/goal-workflow, which has 288 GitHub stars. The repository holds 20 skills in this directory. The repository was last updated on September 13, 2026.
Source: smallnest/goal-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.