wechat-article-extractor

freestylefly/wechat-article-extractor-skill · updated May 17, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/freestylefly/wechat-article-extractor-skill --skill wechat-article-extractor
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summary

Parse WeChat Official Account articles to extract metadata, content, and account information.

  • Extracts article metadata (title, author, publish time, cover image) and account info (name, avatar, alias) from WeChat URLs and HTML
  • Supports multiple article types: posts, videos, images, voice messages, text, and reposts
  • Configurable extraction options for content, raw metadata, repost info, embedded links, and tags
  • Handles error cases including deleted content, expired links, rate lim
skill.md

WeChat Article Extractor

Extract metadata and content from WeChat Official Account (微信公众号) articles.

Capabilities

  • Parse WeChat article URLs (mp.weixin.qq.com)
  • Extract article metadata: title, author, description, publish time
  • Extract account info: name, avatar, alias, description
  • Get article content (HTML)
  • Get cover image URL
  • Support multiple article types: post, video, image, voice, text, repost
  • Handle various error cases: deleted content, expired links, access limits

Usage

Basic Extraction from URL

const { extract } = require('./scripts/extract.js');

const result = await extract('https://mp.weixin.qq.com/s?__biz=...');
// Returns: { done: true, code: 0, data: {...} }

Extraction from HTML

const html = await fetch(url).then(r => r.text());
const result = await extract(html, { url: sourceUrl });

Options

const result = await extract(url, {
  shouldReturnContent: true,      // Return HTML content (default: true)
  shouldReturnRawMeta: false,     // Return raw metadata (default: false)
  shouldFollowTransferLink: true, // Follow migrated account links (default: true)
  shouldExtractMpLinks: false,    // Extract embedded mp.weixin links (default: false)
  shouldExtractTags: false,       // Extract article tags (default: false)
  shouldExtractRepostMeta: false  // Extract repost source info (default: false)
});

Response Format

Success Response

{
  done: true,
  code: 0,
  data: {
    // Account info
    account_name: "公众号名称",
    account_alias: "微信号",
    account_avatar: "头像URL",
    account_description: "功能介绍",
    account_id: "原始ID",
    account_biz: "biz参数",
    account_biz_number: 1234567890,
    account_qr_code: "二维码URL",

    // Article info
    msg_title: "文章标题",
    msg_desc: "文章摘要",
    msg_content: "HTML内容",
    msg_cover: "封面图URL",
    msg_author: "作者",
    msg_type: "post", // post|video|image|voice|text|repost
    msg_has_copyright: true,
    msg_publish_time: Date,
    msg_publish_time_str: "2024/01/15 10:30:00",

    // Link params
    msg_link: "文章链接",
    msg_source_url: "阅读原文链接",
    msg_sn: "sn参数",
    msg_mid: 1234567890,
    msg_idx: 1
  }
}

Error Response

{
  done: false,
  code: 1001,
  msg: "无法获取文章信息"
}

Error Codes

Code Message Description
1000 文章获取失败 General failure
1001 无法获取文章信息 Missing title or publish time
1002 请求失败 HTTP request failed
1003 响应为空 Empty response
1004 访问过于频繁 Rate limited
1005 脚本解析失败 Script parsing error
1006 公众号已迁移 Account migrated
2001 请提供文章内容或链接 Missing input
2002 链接已过期 Link expired
2003 内容涉嫌侵权 Content removed (copyright)
2004 无法获取迁移后的链接 Migration link failed
2005 内容已被发布者删除 Content deleted by author
2006 内容因违规无法查看 Content blocked
2007 内容发送失败 Failed to send
2008 系统出错 System error
2009 不支持的链接 Unsupported URL
2010 内容获取失败 Content fetch failed
2011 涉嫌过度营销 Marketing/spam content
2012 账号已被屏蔽 Account blocked
2013 账号已自主注销 Account deleted
2014 内容被投诉 Content reported
2015 账号处于迁移流程中 Account migrating
2016 冒名侵权 Impersonation

Dependencies

Required npm packages:

  • cheerio - HTML parsing
  • dayjs - Date formatting
  • request-promise - HTTP requests
  • qs - Query string parsing
  • lodash.unescape - HTML entities

Notes

  • Handles various WeChat page structures and anti-scraping measures
  • Automatically detects article type from page content
  • Supports extracting from Sogou WeChat search results (weixin.sogou.com)
  • Some fields may be null depending on article type and page structure
how to use wechat-article-extractor

How to use wechat-article-extractor on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add wechat-article-extractor
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/freestylefly/wechat-article-extractor-skill --skill wechat-article-extractor

The skills CLI fetches wechat-article-extractor from GitHub repository freestylefly/wechat-article-extractor-skill and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/wechat-article-extractor

Reload or restart Cursor to activate wechat-article-extractor. Access the skill through slash commands (e.g., /wechat-article-extractor) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

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Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
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general reviews

Ratings

4.650 reviews
  • Luis Mensah· Dec 28, 2024

    We added wechat-article-extractor from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Soo Diallo· Dec 28, 2024

    Solid pick for teams standardizing on skills: wechat-article-extractor is focused, and the summary matches what you get after install.

  • Nia Mehta· Dec 24, 2024

    wechat-article-extractor reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Luis Martinez· Dec 16, 2024

    wechat-article-extractor has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Dhruvi Jain· Dec 8, 2024

    wechat-article-extractor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Kofi Johnson· Dec 8, 2024

    wechat-article-extractor fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Hiroshi Sethi· Dec 4, 2024

    wechat-article-extractor is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Oshnikdeep· Nov 27, 2024

    Registry listing for wechat-article-extractor matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Mia Sanchez· Nov 27, 2024

    Registry listing for wechat-article-extractor matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Min Rao· Nov 23, 2024

    Solid pick for teams standardizing on skills: wechat-article-extractor is focused, and the summary matches what you get after install.

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