Search WeChat public account articles by keyword with title, summary, publish time, and source information.
Works with
Searches WeChat articles across topics including technology, AI, social trends, finance, education, and workplace content
Returns article metadata: title, summary, publication date, source public account name, and access links
Supports optional parameters for result count (up to 50), JSON file output, and real URL resolution for article links
Requires Node.js with the cheeri
该脚本依赖NodeJS依赖包 cheerio，建议先执行全局安装或在项目中安装：
npm install -g cheerio
1、 确认关键词与数量
1、执行常规搜索命令
node scripts/search_wechat.js "关键词"
node scripts/search_wechat.js "关键词" -n 15
node scripts/search_wechat.js "关键词" -n 20 -o result.json
node scripts/search_wechat.js "关键词" -n 5 -r
query：搜索关键词（必填）-n, --num：返回数量（默认 10，最大 50）-o, --output：输出 JSON 文件路径（可选）-r, --resolve-url：尝试把中间链接解析成微信文章真实链接（会额外请求每条结果）文章标题、文章地址、文章概要、发布时间、来源公众号名称
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionwechat-article-searchExecute the skills CLI command in your project's root directory to begin installation:
Fetches wechat-article-search from wuchubuzai2018/expert-skills-hub 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 wechat-article-search. Access via /wechat-article-search 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
7
total installs
7
this week
11
GitHub stars
0
upvotes
Run in your terminal
7
installs
7
this week
11
stars
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.
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mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
wechat-article-search fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Solid pick for teams standardizing on skills: wechat-article-search is focused, and the summary matches what you get after install.
wechat-article-search is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in wechat-article-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
I recommend wechat-article-search for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
wechat-article-search has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: wechat-article-search is the kind of skill you can hand to a new teammate without a long onboarding doc.
Registry listing for wechat-article-search matched our evaluation — installs cleanly and behaves as described in the markdown.
We added wechat-article-search from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in wechat-article-search — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
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