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content-harvest内容收获

Agent Skill

用于辅助前端页面、组件、样式和交互逻辑的开发与维护。它适合让 Agent 生成或审查 React、Next.js、Vue、Tailwind、CSS 等相关代码,整理组件结构,或定位布局和性能问题。使用时需要结合项目现有设计系统、路由和构建方式,避免只生成孤立片段;涉及页面改动时,应配合本地预览和构建检查确认视觉效果。

总安装

1,812

周安装

74

GitHub Stars

5

下载量

580
CodexClaudeCursorGemini CLI

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

3

许可证

MIT

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:content-harvest(内容收获)
来源仓库:https://github.com/qodex-ai/ai-agent-skills
仓库路径:skills/content-harvest
安装命令:
npx skills add https://github.com/qodex-ai/ai-agent-skills --skill content-harvest
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/qodex-ai/ai-agent-skills --skill content-harvest

简介

用于从文章或博客页面提取纯净文本内容,去除导航与广告干扰。

  • 自动识别并清理订阅弹窗、侧边栏等非正文元素。
  • 支持多种解析工具回退机制,确保高成功率获取可读文本。
  • 安装方式:通过 GitHub 仓库安装,命令为 npx skills add https://github.com/qodex-ai/ai-agent-skills --skill content-harvest。
  • 注意:仅适用于单篇内容提取,不适合批量下载或多页聚合场景。

SKILL.md

Article Extractor

This skill extracts the main content from web articles and blog posts, removing navigation, ads, newsletter signups, and other clutter. Saves clean, readable text.

When to Use This Skill

Activate when the user:

  • Provides an article/blog URL and wants the text content
  • Asks to "download this article"
  • Wants to "extract the content from [URL]"
  • Asks to "save this blog post as text"
  • Needs clean article text without distractions

How It Works

Priority Order:

  1. Check if tools are installed (reader or trafilatura)
  2. Download and extract article using best available tool
  3. Clean up the content (remove extra whitespace, format properly)
  4. Save to file with article title as filename
  5. Confirm location and show preview

Installation Check

Check for article extraction tools in this order:

Option 1: reader (Recommended - Mozilla's Readability)

command -v reader

If not installed:

npm install -g @mozilla/readability-cli
# or
npm install -g reader-cli

Option 2: trafilatura (Python-based, very good)

command -v trafilatura

If not installed:

pip3 install trafilatura

Option 3: Fallback (curl + simple parsing)

If no tools available, use basic curl + text extraction (less reliable but works)

Extraction Methods

Method 1: Using reader (Best for most articles)

# Extract article
reader "URL" > article.txt

Pros:

  • Based on Mozilla's Readability algorithm
  • Excellent at removing clutter
  • Preserves article structure

Method 2: Using trafilatura (Best for blogs/news)

# Extract article
trafilatura --URL "URL" --output-format txt > article.txt

# Or with more options
trafilatura --URL "URL" --output-format txt --no-comments --no-tables > article.txt

Pros:

  • Very accurate extraction
  • Good with various site structures
  • Handles multiple languages

Options:

  • --no-comments: Skip comment sections
  • --no-tables: Skip data tables
  • --precision: Favor precision over recall
  • --recall: Extract more content (may include some noise)

Method 3: Fallback (curl + basic parsing)

# Download and extract basic content
curl -s "URL" | python3 -c "
from html.parser import HTMLParser
import sys

class ArticleExtractor(HTMLParser):
    def __init__(self):
        super().__init__()
        self.in_content = False
        self.content = []
        self.skip_tags = {'script', 'style', 'nav', 'header', 'footer', 'aside'}
        self.current_tag = None

    def handle_starttag(self, tag, attrs):
        if tag not in self.skip_tags:
            if tag in {'p', 'article', 'main', 'h1', 'h2', 'h3', 'h4', 'h5', 'h6'}:
                self.in_content = True
        self.current_tag = tag

    def handle_data(self, data):
        if self.in_content and data.strip():
            self.content.append(data.strip())

    def get_content(self):
        return '\n\n'.join(self.content)

parser = ArticleExtractor()
parser.feed(sys.stdin.read())
print(parser.get_content())
" > article.txt

Note: This is less reliable but works without dependencies.

Getting Article Title

Extract title for filename:

Using reader:

# reader outputs markdown with title at top
TITLE=$(reader "URL" | head -n 1 | sed 's/^# //')

Using trafilatura:

# Get metadata including title
TITLE=$(trafilatura --URL "URL" --json | python3 -c "import json, sys; print(json.load(sys.stdin)['title'])")

Using curl (fallback):

TITLE=$(curl -s "URL" | grep -oP '<title>\K[^<]+' | sed 's/ - .*//' | sed 's/ | .*//')

Filename Creation

Clean title for filesystem:

# Get title
TITLE="Article Title from Website"

# Clean for filesystem (remove special chars, limit length)
FILENAME=$(echo "$TITLE" | tr '/' '-' | tr ':' '-' | tr '?' '' | tr '"' '' | tr '<' '' | tr '>' '' | tr '|' '-' | cut -c 1-100 | sed 's/ *$//')

# Add extension
FILENAME="${FILENAME}.txt"

Complete Workflow

ARTICLE_URL="https://example.com/article"

# Check for tools
if command -v reader &> /dev/null; then
    TOOL="reader"
    echo "Using reader (Mozilla Readability)"
elif command -v trafilatura &> /dev/null; then
    TOOL="trafilatura"
    echo "Using trafilatura"
else
    TOOL="fallback"
    echo "Using fallback method (may be less accurate)"
fi

# Extract article
case $TOOL in
    reader)
        # Get content
        reader "$ARTICLE_URL" > temp_article.txt

        # Get title (first line after # in markdown)
        TITLE=$(head -n 1 temp_article.txt | sed 's/^# //')
        ;;

    trafilatura)
        # Get title from metadata
        METADATA=$(trafilatura --URL "$ARTICLE_URL" --json)
        TITLE=$(echo "$METADATA" | python3 -c "import json, sys; print(json.load(sys.stdin).get('title', 'Article'))")

        # Get clean content
        trafilatura --URL "$ARTICLE_URL" --output-format txt --no-comments > temp_article.txt
        ;;

    fallback)
        # Get title
        TITLE=$(curl -s "$ARTICLE_URL" | grep -oP '<title>\K[^<]+' | head -n 1)
        TITLE=${TITLE%% - *}  # Remove site name
        TITLE=${TITLE%% | *}  # Remove site name (alternate)

        # Get content (basic extraction)
        curl -s "$ARTICLE_URL" | python3 -c "
from html.parser import HTMLParser
import sys

class ArticleExtractor(HTMLParser):
    def __init__(self):
        super().__init__()
        self.in_content = False
        self.content = []
        self.skip_tags = {'script', 'style', 'nav', 'header', 'footer', 'aside', 'form'}

    def handle_starttag(self, tag, attrs):
        if tag not in self.skip_tags:
            if tag in {'p', 'article', 'main'}:
                self.in_content = True
        if tag in {'h1', 'h2', 'h3'}:
            self.content.append('\n')

    def handle_data(self, data):
        if self.in_content and data.strip():
            self.content.append(data.strip())

    def get_content(self):
        return '\n\n'.join(self.content)

parser = ArticleExtractor()
parser.feed(sys.stdin.read())
print(parser.get_content())
" > temp_article.txt
        ;;
esac

# Clean filename
FILENAME=$(echo "$TITLE" | tr '/' '-' | tr ':' '-' | tr '?' '' | tr '"' '' | tr '<>' '' | tr '|' '-' | cut -c 1-80 | sed 's/ *$//' | sed 's/^ *//')
FILENAME="${FILENAME}.txt"

# Move to final filename
mv temp_article.txt "$FILENAME"

# Show result
echo "✓ Extracted article: $TITLE"
echo "✓ Saved to: $FILENAME"
echo ""
echo "Preview (first 10 lines):"
head -n 10 "$FILENAME"

Error Handling

Common Issues

1. Tool not installed

  • Try alternate tool (reader → trafilatura → fallback)
  • Offer to install: "Install reader with: npm install -g reader-cli"

2. Paywall or login required

  • Extraction tools may fail
  • Inform user: "This article requires authentication. Cannot extract."

3. Invalid URL

  • Check URL format
  • Try with and without redirects

4. No content extracted

  • Site may use heavy JavaScript
  • Try fallback method
  • Inform user if extraction fails

5. Special characters in title

  • Clean title for filesystem
  • Remove: /, :, ?, ", <, >, |
  • Replace with - or remove

Output Format

Saved File Contains:

  • Article title (if available)
  • Author (if available from tool)
  • Main article text
  • Section headings
  • No navigation, ads, or clutter

What Gets Removed:

  • Navigation menus
  • Ads and promotional content
  • Newsletter signup forms
  • Related articles sidebars
  • Comment sections (optional)
  • Social media buttons
  • Cookie notices

Tips for Best Results

1. Use reader for most articles

  • Best all-around tool
  • Based on Firefox Reader View
  • Works on most news sites and blogs

2. Use trafilatura for:

  • Academic articles
  • News sites
  • Blogs with complex layouts
  • Non-English content

3. Fallback method limitations:

  • May include some noise
  • Less accurate paragraph detection
  • Better than nothing for simple sites

4. Check extraction quality:

  • Always show preview to user
  • Ask if it looks correct
  • Offer to try different tool if needed

Example Usage

Simple extraction:

# User: "Extract https://example.com/article"
reader "https://example.com/article" > temp.txt
TITLE=$(head -n 1 temp.txt | sed 's/^# //')
FILENAME="$(echo "$TITLE" | tr '/' '-').txt"
mv temp.txt "$FILENAME"
echo "✓ Saved to: $FILENAME"

With error handling:

if ! reader "$URL" > temp.txt 2>/dev/null; then
    if command -v trafilatura &> /dev/null; then
        trafilatura --URL "$URL" --output-format txt > temp.txt
    else
        echo "Error: Could not extract article. Install reader or trafilatura."
        exit 1
    fi
fi

Best Practices

  • ✅ Always show preview after extraction (first 10 lines)
  • ✅ Verify extraction succeeded before saving
  • ✅ Clean filename for filesystem compatibility
  • ✅ Try fallback method if primary fails
  • ✅ Inform user which tool was used
  • ✅ Keep filename length reasonable (< 100 chars)

After Extraction

Display to user:

  1. "✓ Extracted: [Article Title]"
  2. "✓ Saved to: [filename]"
  3. Show preview (first 10-15 lines)
  4. File size and location

Ask if needed:

  • "Would you like me to also create a Ship-Learn-Next plan from this?" (if using ship-learn-next skill)
  • "Should I extract another article?"

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Claude Code

26.38%
按下载量换算153

trae

23.16%
按下载量换算134

Codex

16.68%
按下载量换算97

Antigravity

12.47%
按下载量换算72

windsurf

7.4%
按下载量换算43

github-copilot

3.1%
按下载量换算18

安全审计

Gen Agent Trust Hub

未通过

Socket

通过

Snyk

可疑

权限和风险

可写文件

该 Skill 可能写入或修改本地文件,使用前需要确认目标目录和修改范围。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。

来源信息

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