从主流新闻平台提取文章内容，输出 JSON 和 Markdown 格式。
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionnews-extractorExecute the skills CLI command in your project's root directory to begin installation:
Fetches news-extractor from nanmicoder/newscrawler and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate news-extractor. Access via /news-extractor in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
1
total installs
1
this week
324
GitHub stars
0
upvotes
Run in your terminal
1
installs
1
this week
324
stars
从主流新闻平台提取文章内容，输出 JSON 和 Markdown 格式。
独立可迁移：本 Skill 包含所有必需代码，无外部依赖，可直接复制到其他项目使用。
| 平台 | ID | URL 示例 |
|---|---|---|
| 微信公众号 | https://mp.weixin.qq.com/s/xxxxx |
|
| 今日头条 | toutiao | https://www.toutiao.com/article/123456/ |
| 网易新闻 | netease | https://www.163.com/news/article/ABC123.html |
| 搜狐新闻 | sohu | https://www.sohu.com/a/123456_789 |
| 腾讯新闻 | tencent | https://news.qq.com/rain/a/20251016A07W8J00 |
| 平台 | ID | URL 示例 |
|---|---|---|
| BBC News | bbc | https://www.bbc.com/news/articles/c797qlx93j0o |
| CNN News | cnn | https://edition.cnn.com/2025/10/27/uk/article-slug |
| Twitter/X | https://x.com/user/status/123456789 |
|
| Lenny's Newsletter | lenny | https://www.lennysnewsletter.com/p/article-slug |
| Naver Blog | naver | https://blog.naver.com/username/123456 |
| Detik News | detik | https://news.detik.com/internasional/d-123456/slug |
| Quora | quora | https://www.quora.com/question/answers/123456 |
本 skill 使用 uv 管理依赖。首次使用前需要安装：
cd .claude/skills/news-extractor
uv sync
重要: 所有脚本必须使用 uv run 执行，不要直接用 python 运行。
| 包名 | 用途 |
|---|---|
| pydantic | 数据模型验证 |
| requests | HTTP 请求 |
| curl_cffi | 浏览器模拟抓取 |
| tenacity | 重试机制 |
| parsel | HTML/XPath 解析 |
| demjson3 | 非标准 JSON 解析 |
# 提取新闻，自动检测平台，输出 JSON + Markdown
uv run .claude/skills/news-extractor/scripts/extract_news.py "URL"
# 指定输出目录
uv run .claude/skills/news-extractor/scripts/extract_news.py "URL" --output ./output
# 仅输出 JSON
uv run .claude/skills/news-extractor/scripts/extract_news.py "URL" --format json
# 仅输出 Markdown
uv run .claude/skills/news-extractor/scripts/extract_news.py "URL" --format markdown
# Twitter 受保护推文 (需要 Cookie)
uv run .claude/skills/news-extractor/scripts/extract_news.py "URL" --cookie "auth_token=xxx; ct0=yyy"
# 列出支持的平台
uv run .claude/skills/news-extractor/scripts/extract_news.py --list-platforms
脚本默认输出两种格式到指定目录（默认 ./output）：
{news_id}.json - 结构化 JSON 数据{news_id}.md - Markdown 格式文章{
"title": "文章标题",
"news_url": "原始链接",
"news_id": "文章ID",
"meta_info": {
"author_name": "作者/来源",
"author_url": "",
"publish_time": "2024-01-01 12:00"
},
"contents": [
{"type": "text", "content": "段落文本", "desc": ""},
{"type": "image", "content": "https://...", "desc": ""},
{"type": "video", "content": "https://...", "desc": ""}
],
"texts": ["段落1", "段落2"],
"images": ["图片URL1", "图片URL2"],
"videos": []
}
# 文章标题
## 文章信息
**作者**: xxx
**发布时间**: 2024-01-01 12:00
**原文链接**: [链接](URL)
---
## 正文内容
段落内容...
---
## 媒体资源
### 图片 (N)
1. URL1
2. URL2
uv run .claude/skills/news-extractor/scripts/extract_news.py \
"https://mp.weixin.qq.com/s/ebMzDPu2zMT_mRgYgtL6eQ"
uv run .claude/skills/news-extractor/scripts/extract_news.py \
"https://www.bbc.com/news/articles/c797qlx93j0o"
# 公开推文 (无需认证)
uv run .claude/skills/news-extractor/scripts/extract_news.py \
"https://x.com/BarackObama/status/896523232098078720"
# 受保护推文 (需要 Cookie)
uv run .claude/skills/news-extractor/scripts/extract_news.py \
"https://x.com/user/status/123456" --cookie "auth_token=xxx; ct0=yyy"
| 错误类型 | 说明 | 解决方案 |
|---|---|---|
无法识别该平台 |
URL 不匹配任何支持的平台 | 检查 URL 是否正确 |
平台不支持 |
非支持的站点 | 本 Skill 仅支持列出的 12 个平台 |
提取失败 |
网络错误或页面结构变化 | 重试或检查 URL 有效性 |
认证失败 |
Twitter Cookie 无效 | 重新获取 Cookie |
news-extractor/
├── SKILL.md # [必需] Skill 定义文件
├── pyproject.toml # 依赖管理
├── references/
│ └── platform-patterns.md # 平台 URL 模式说明
└── scripts/
├── extract_news.py # CLI 入口脚本
├── models.py # 数据模型
├── detector.py # 平台检测
├── formatter.py # Markdown 格式化
└── crawlers/ # 爬虫模块
├── __init__.py
├── base.py # BaseNewsCrawler 基类
├── fetchers.py # HTTP 获取策略
├── wechat.py # 微信公众号
├── toutiao.py # 今日头条
├── netease.py # 网易新闻
├── sohu.py # 搜狐新闻
├── tencent.py # 腾讯新闻
├── bbc.py # BBC News
├── cnn.py # CNN News
├── twitter.py # Twitter/X
├── twitter_client.py # Twitter API 客户端
├── twitter_types.py # Twitter 数据类型
├── lenny.py # Lenny's Newsletter
├── naver.py # Naver Blog
├── detik.py # Detik News
└── quora.py # Quora
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
Keeps context tight: news-extractor is the kind of skill you can hand to a new teammate without a long onboarding doc.
news-extractor has been reliable in day-to-day use. Documentation quality is above average for community skills.
news-extractor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added news-extractor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added news-extractor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Solid pick for teams standardizing on skills: news-extractor is focused, and the summary matches what you get after install.
news-extractor has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: news-extractor is focused, and the summary matches what you get after install.
Keeps context tight: news-extractor is the kind of skill you can hand to a new teammate without a long onboarding doc.
Keeps context tight: news-extractor is the kind of skill you can hand to a new teammate without a long onboarding doc.
showing 1-10 of 69