News Extractor

What it does

When your agent uses it

• Tasks that involve Newsletters
• Tasks that involve Markdown

Example prompts

• “/news-extractor”

Requirements

• Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

1. 1接收 URL - 用户提供新闻链接
2. 2平台检测 - 自动识别平台类型
3. 3内容提取 - 调用对应爬虫获取并解析内容
4. 4格式转换 - 生成 JSON 和 Markdown
5. 5输出文件 - 保存到指定目录

What it can do on your machine

Read from SKILL.md and the folder at commit 25fb3b4. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 15 files in scripts/ (Python, from the files we listed), which the agent can run.

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • x.com
  • mp.weixin.qq.com
  • bbc.com
  • toutiao.com
  • 163.com
  • sohu.com
  • news.qq.com
  • edition.cnn.com
  • lennysnewsletter.com
  • blog.naver.com
  • news.detik.com
  • quora.com

  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

News Extractor loads about 1.3k tokens when it runs, and up to ~2.6k if it reads all its reference files. Until then it costs about 46 tokens; SKILL.md has 198 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~46

When it runs · the whole SKILL.md, loaded when a task matches

~1.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~2.6k

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

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); the scripts in this folder are not scanned.

SKILL.md

The full file from NanmiCoder/NewsCrawler at commit 25fb3b4, republished under its GPL-3.0 licence (© NanmiCoder). 198 words, ~1,310 tokens.

name

news-extractor

description

新闻站点内容提取。支持 12 个平台：微信公众号、今日头条、网易新闻、搜狐新闻、腾讯新闻、BBC News、CNN News、Twitter/X、Lenny's Newsletter、Naver Blog、Detik News、Quora。当用户需要提取新闻内容、抓取公众号文章、爬取新闻、或获取新闻JSON/Markdown时激活。

license

GPL-3.0

cd <Agent Skills 目录>/news-extractor
uv sync

# 以下命令均在 news-extractor Skill 目录内执行

# 提取新闻，自动检测平台，输出 JSON + Markdown
uv run scripts/extract_news.py "URL"

# 指定输出目录
uv run scripts/extract_news.py "URL" --output ./output

# 仅输出 JSON
uv run scripts/extract_news.py "URL" --format json

# 仅输出 Markdown
uv run scripts/extract_news.py "URL" --format markdown

# Twitter 受保护推文 (需要 Cookie)
uv run scripts/extract_news.py "URL" --cookie "auth_token=xxx; ct0=yyy"

# 列出支持的平台
uv run scripts/extract_news.py --list-platforms

{
  "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...

![图片](URL)

---

## 媒体资源
### 图片 (N)
1. URL1
2. URL2

uv run scripts/extract_news.py \
  "https://mp.weixin.qq.com/s/ebMzDPu2zMT_mRgYgtL6eQ"

uv run scripts/extract_news.py \
  "https://www.bbc.com/news/articles/c797qlx93j0o"

# 公开推文 (无需认证)
uv run scripts/extract_news.py \
  "https://x.com/BarackObama/status/896523232098078720"

# 受保护推文 (需要 Cookie)
uv run scripts/extract_news.py \
  "https://x.com/user/status/123456" --cookie "auth_token=xxx; ct0=yyy"

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

© NanmiCoder, GPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 24 other files (scripts, references) in .claude/skills/news-extractor of NanmiCoder/NewsCrawler.

• SKILL.md
• pyproject.toml
• references/platform-patterns.md
• scripts/crawlers/__init__.py
• scripts/crawlers/base.py
• scripts/crawlers/bbc.py
• scripts/crawlers/cnn.py
• scripts/crawlers/detik.py
• scripts/crawlers/fetchers.py
• scripts/crawlers/lenny.py
• scripts/crawlers/naver.py
• scripts/crawlers/netease.py
• scripts/crawlers/quora.py
• scripts/crawlers/sohu.py
• scripts/crawlers/tencent.py
• scripts/crawlers/toutiao.py
• scripts/crawlers/twitter.py
• scripts/crawlers/twitter_client.py
• … and 7 more

Open the folder on GitHubat commit 25fb3b4