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humanize-ai-writingAI 写作人性化

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

3,096

周安装

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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-writing(AI 写作人性化)
来源仓库:https://github.com/anderskev/humanize-ai-writing
安装命令:
openclaw skills install humanize-ai-writing
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-writing

简介

humanize-ai-writing 将 AI 生成的开发文档重写为自然语言,修复夸大与填充内容。

  • 适合在 OpenClaw 中审查技术文档、代码注释或说明材料时使用。
  • 可识别并替换同义反复与空洞表述,提升专业性与实用性。
  • 安装命令为 openclaw skills install humanize-ai-writing,具体用法请参考原始 README。
  • 使用时需保留原有事实与路径,避免引入未经验证的技术断言。

SKILL.md

name
humanize-ai-writing
description
Rewrite AI-generated developer text to sound human — fix inflated language, filler, tautological docs, and robotic tone. Use after review-ai-writing identifies issues.
disable-model-invocation
true
user-invocable
true
dependencies

Humanize

Apply fixes from a previous review-ai-writing run with automatic safe/risky classification.

Usage

/beagle-docs:humanize-ai-writing [--dry-run] [--all] [--category <name>]

Flags:

  • --dry-run - Show what would be fixed without changing files
  • --all - Fix entire codebase (runs review with --all first)
  • --category <name> - Only fix specific category: content|vocabulary|formatting|communication|filler|code_docs

Instructions

1. Parse Arguments

Extract flags from $ARGUMENTS:

  • --dry-run - Preview mode only
  • --all - Full codebase scan
  • --category <name> - Filter to specific category

2. Pre-flight Safety Checks

# Check for uncommitted changes
git status --porcelain

If working directory is dirty, warn:

Warning: You have uncommitted changes. Creating a git stash before proceeding.
Run `git stash pop` to restore if needed.

Create stash if dirty:

git stash push -u -m "beagle-docs: pre-humanize backup"

3. Load Review Results

Check for existing review file:

cat .beagle/ai-writing-review.json 2>/dev/null

If file missing:

  • If --all flag: Run /beagle-docs:review-ai-writing --all first
  • Otherwise: Fail with: "No review results found. Run /beagle-docs:review-ai-writing first."

If file exists, validate freshness:

# Get stored git HEAD from JSON
stored_head=$(jq -r '.git_head' .beagle/ai-writing-review.json)
current_head=$(git rev-parse HEAD)

if [ "$stored_head" != "$current_head" ]; then
  echo "Warning: Review was run at commit $stored_head, but HEAD is now $current_head"
fi

If stale, prompt: "Review results are stale. Re-run review? (y/n)"

4. Load Reference Material

Read the appropriate reference files based on the findings being fixed:

  • Read references/vocabulary-swaps.md when applying ai_vocabulary_high or ai_vocabulary_low fixes
  • Read references/fix-strategies.md for strategy details and before/after examples for any category
  • Read references/developer-voice.md for tone/register guidance when rewriting prose

Only load what you need — if fixing only vocabulary, skip the voice guide.

5. Filter Findings

If --category is set, filter findings to that category only.

Partition remaining findings by fix_safety:

Safe Fixes (auto-apply):

  • chat_leak - Delete conversational artifacts
  • cutoff_disclaimer - Delete knowledge cutoff references
  • filler_phrase - Delete filler phrases
  • heading_restatement - Delete restating first sentence
  • emoji_decoration - Remove emoji from technical text
  • boldface_overuse - Remove excessive bold formatting
  • ai_vocabulary_high - Swap high-signal AI words
  • narrating_obvious - Delete obvious code comments
  • synthetic_opener - Delete "In today's..." openers
  • sycophantic_tone - Delete or neutralize praise
  • vague_authority - Delete unattributed claims
  • excessive_hedging - Remove qualifiers
  • generic_conclusion - Delete summary padding
  • copula_avoidance - Use "is/are" naturally
  • rhetorical_device - Delete rhetorical questions
  • em_dash_overuse - Replace formulaic em dashes with commas, parentheses, or colons
  • thematic_break - Remove horizontal rules before headings
  • title_case_heading - Convert AI title-case headings to sentence case
  • curly_quotes - Normalize curly quotes/apostrophes to straight
  • negative_parallelism - Delete "Not just X, but also Y" filler constructions
  • challenges_and_prospects - Delete "Despite its... faces challenges..." formulaic wrappers

Needs Review Fixes (require confirmation):

  • promotional_language - Rewrite with specifics
  • formulaic_structure - Restructure sections
  • synonym_cycling - Pick consistent term
  • commit_inflation - Rewrite commit scope
  • tautological_docstring - Rewrite or delete docstring
  • exhaustive_enumeration - Trim parameter docs
  • this_noun_verbs - Rewrite docstring voice
  • ai_vocabulary_low - Reduce cluster density
  • apologetic_error - Rewrite error message
  • rule_of_three - Simplify three-item lists used as filler comprehensiveness
  • inline_header_list - Restructure boldfaced inline-header vertical lists
  • unnecessary_table - Convert small tables to prose
  • regression_to_mean - Restore specific facts replaced by vague praise

6. Apply Safe Fixes

If --dry-run:

## Safe Fixes (would apply automatically)

| # | File | Line | Type | Action |
|---|------|------|------|--------|
| 1 | README.md | 3 | synthetic_opener | Delete "In today's rapidly evolving..." |
| 2 | src/auth.py | 15 | narrating_obvious | Delete "# Check if user exists" |
| 3 | README.md | 42 | ai_vocabulary_high | Replace "utilize" with "use" |
...

Otherwise, apply fixes grouped by file to minimize file I/O:

  1. Sort findings by file, then by line number (descending, to avoid offset drift)
  2. For each file, apply all safe fixes in reverse line order
  3. For git artifacts (git:commit:*, git:pr:*), skip — these can't be auto-fixed. Report them for manual attention.

7. Handle Needs Review Fixes

If --dry-run, list them:

## Needs Review Fixes (would prompt interactively)

| # | File | Line | Type | Original | Suggested |
|---|------|------|------|----------|-----------|
| 4 | README.md | 8 | promotional_language | "powerful, enterprise-grade solution" | "authentication library" |
...

Otherwise, for each fix, prompt interactively:

[README.md:8] Promotional language: "powerful, enterprise-grade solution"
Suggested: "authentication library"
(y)es / (n)o / (e)dit / (s)kip all:

Track user choices:

  • y - Apply this fix as suggested
  • n - Skip this fix
  • e - User provides custom replacement
  • s - Skip all remaining interactive fixes

8. Validate Results

For each modified markdown file, verify basic validity:

# Check for broken markdown (unclosed code blocks, broken links)
# Simple check: matching ``` pairs
grep -c '```' "$file" | awk '{print ($1 % 2 == 0) ? "OK" : "WARNING: odd number of code fences"}'

For modified source files, check syntax is still valid:

Python:

python3 -c "import ast; ast.parse(open('$file').read())"

TypeScript/JavaScript:

npx -y acorn --ecma2020 "$file" > /dev/null 2>&1

If validation fails for any file, revert that file:

git checkout -- "$file"
echo "Reverted $file due to validation failure"

9. Report Results

## Humanize Summary

### Applied Fixes
- [x] README.md:3 - Deleted synthetic opener
- [x] README.md:42 - Replaced "utilize" with "use"
- [x] src/auth.py:15 - Deleted obvious comment

### Interactive Fixes
- [x] README.md:8 - Rewrote promotional language (user approved)
- [ ] docs/guide.md:22 - Skipped by user

### Skipped (Git Artifacts)
- [ ] git:commit:abc1234 - Chat leak in commit message (amend manually)

### Validation
- README.md: OK
- src/auth.py: OK

### Diff Summary
git diff --stat

10. Cleanup

On successful completion (all validations pass):

rm .beagle/ai-writing-review.json

If any validation fails, keep the file and report:

Review file preserved at .beagle/ai-writing-review.json
Fix issues and re-run, or restore with: git stash pop

Core Principles

  1. Delete first, rewrite second. Most AI patterns are padding. Removing them improves the text.
  2. Use simple words. Replace "utilize" with "use", "facilitate" with "help", "implement" with "add".
  3. Keep sentences short. Break compound sentences. One idea per sentence.
  4. Preserve meaning. Never change what the text says, only how it says it.
  5. Match the register. Commit messages are terse. READMEs are conversational. API docs are precise. Read references/developer-voice.md for the full register guide.
  6. Don't overcorrect. A slightly formal sentence is fine. Only fix patterns that read as obviously AI-generated.
  7. Understand regression to the mean. LLMs produce the most statistically likely output. Specific, unusual facts get replaced with generic, positive descriptions. When humanizing, restore specificity — replace vague praise with concrete details.
  8. Score density, not individual words. AI vocabulary words co-occur. One or two may be coincidental; a cluster of 3+ is a strong AI tell.

Example

# Preview all fixes without applying
/beagle-docs:humanize-ai-writing --dry-run

# Fix only vocabulary issues
/beagle-docs:humanize-ai-writing --category vocabulary

# Full codebase scan and fix
/beagle-docs:humanize-ai-writing --all

# Preview filler fixes only
/beagle-docs:humanize-ai-writing --category filler --dry-run

Rules

  • Always load reference material before applying fixes (step 4)
  • Never modify files without a stash or clean working directory
  • Apply safe fixes in reverse line order to avoid offset drift
  • Never auto-fix git artifacts (commits, PRs) — report them for manual action
  • Validate every modified file before considering it done
  • Revert files that fail validation
  • Write JSON report before displaying summary
  • Clean up JSON report only on full success

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