据 AlphaMoat 统计,截至 2026-09,Humanize AI 累计下载 4,096 次、获 8 个星标,在全部 5,078 个 AI 技能中排名第 2,469 位,在「内容创作」分类(362 个)中排名第 171 位。
| 平台 | 累计安装 | 累计下载 | 星标 | 评论 |
|---|---|---|---|---|
| ClawHub ↗ | 109 | 3,438 | 8 | - |
| SkillHub ↗ | 360 | 4,096 | 8 | — |
各平台的计数口径不同,统计时间不一致。
报告套路词汇、夸张措辞和聊天机器人用语,可替换赘语、统一引号,并可选调整破折号。规则清单可定制,分析输出可为文本或 JSON。应先分析、另存修改、保留备份,替换原件前人工检查含义与语气。模式匹配不能判断作者身份,也不保证检测器结果。
资料发布于 2026-10-27
以下是根据技能文档生成的示例,不代表实际运行结果。
2026-09 起统计方法调整:同名技能按作者分别统计,并覆盖全部技能。图中虚线为调整前的月份,与之后的数据不直接比较,也不计算跨越调整的增长。
| 月份 | 累计下载 | 环比 | 星标 |
|---|---|---|---|
| 2026-09 | 4,096 | — | 8 |
| 2026-08 | 3,520 | +5.8% | 8 |
| 2026-07 | 3,327 | +8.2% | 8 |
| 2026-06 | 3,075 | +4.9% | 8 |
| 2026-05 | 2,932 | — | 8 |
| 2026-03 | 2,443 | — | 8 |
以下是作者发布的原始文件,按纯文本显示,本站未做修改或审核;其中的链接不可点击,命令请核实后再运行。抓取于 2026-10-23。
--- name: humanize-ai description: Humanize AI content by detecting and auto-fixing AI generated content. Humanize AI text using Python scripts. Scans for AI vocabulary, puffery, chatbot artifacts, and auto-replaces filler phrases. Use when you want to analyze text in AI detector and bypass it in future, batch-process files, run automated cleanup, or get a report before manual humanizing. allowed-tools: - Read - Write - StrReplace - Shell - Glob ---
# Humanize CLI Command-line tools for detecting and auto-fixing AI writing patterns. ## Scripts ### analyze.py — Detect AI Patterns Scans text and reports AI vocabulary, puffery, chatbot artifacts, and auto-replaceable phrases. ```bash # Analyze a file python scripts/analyze.py input.txt # Analyze from stdin echo "This serves as a testament to our commitment" | python scripts/analyze.py # JSON output for programmatic use python scripts/analyze.py input.txt --json ``` **Output example:** ``` ================================================== AI PATTERN ANALYSIS - 5 issues found ================================================== AI VOCABULARY: • testament: 1x • crucial: 2x AUTO-REPLACEABLE: • "serves as" → "is": 1x • "in order to" → "to": 1x ``` --- ### humanize.py — Auto-Replace Patterns Performs automatic replacements for common AI-isms. ```bash # Humanize and print to stdout python scripts/humanize.py input.txt # Write to output file python scripts/humanize.py input.txt -o output.txt # Include em dash replacement python scripts/humanize.py input.txt --fix-dashes # Quiet mode (no change log) python scripts/humanize.py input.txt -q ``` **What it fixes automatically:** - Filler phrases: "in order to" → "to", "due to the fact that" → "because" - Copula avoidance: "serves as" → "is", "boasts" → "has" - Sentence starters: removes "Additionally,", "Furthermore,", "Moreover," - Curly quotes → straight quotes - Chatbot artifacts: removes "I hope this helps", "Let me know if", etc. --- ## Workflow 1. **Analyze first** to see what needs fixing: ```bash python scripts/analyze.py document.txt ``` 2. **Auto-fix** safe replacements: ```bash python scripts/humanize.py document.txt -o document_clean.txt ``` 3. **Manual review** for AI vocabulary and puffery flagged by analyze (these require human judgment) 4. **Re-analyze** to confirm improvements: ```bash python scripts/analyze.py document_clean.txt ``` --- ## Customizing Patterns Edit `scripts/patterns.json` to add/remove: - `ai_words` — vocabulary that flags but doesn't auto-replace - `puffery` — promotional language to flag - `replacements` — phrase → replacement mappings (empty string = delete) - `chatbot_artifacts` — phrases to auto-remove - `hedging_phrases` — excessive hedging to flag --- ## Batch Processing Process multiple files: ```bash # Analyze all markdown files for f in *.md; do echo "=== $f ===" python scripts/analyze.py "$f" done # Humanize all txt files in place for f in *.txt; do python scripts/humanize.py "$f" -o "$f.tmp" && mv "$f.tmp" "$f" done ``` ---
识别并去掉文本里的 AI 写作痕迹,让文字读起来更像人写。
把文本里 AI 写作的典型痕迹挑出来并改写得更自然,同时保留原意的写作编辑技能。
识别并去除 AI 生成文本痕迹的中文文字编辑技能。
wechat-search 检索公众号热门文章,并按相关性、热度和时效整理结果。
从公开短视频分享链接提取标题、简介和口播文案,并给出改写版本。
humanizer 为中英文文本提供更自然的表达和风格编辑指导。
写网文章节并按文件落盘,聊天里只回摘要与指针。
把一组营销方法模块收进同一个技能,按请求路由到对应模块取清单与可交付稿。
数据月份:2026-09 · 下载/星标/安装数聚合自公开技能注册库(ClawHub、SkillHub),按月更新。口径说明见数据方法。