wechat-article-fetcher

Fetch and rank WeChat official account articles by research interests.

Updated Jan 12, 2026

Search Tags:#automation #mcp #obsidian #wechat #ranking #article-fetcher

Ready to run

npx skills add https://github.com/ppx123-web/claude-config --skill wechat-article-fetcher

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: wechat-article-fetcher
Source: https://github.com/ppx123-web/claude-config/tree/main/skills/wechat-article-fetcher
Command: npx skills add https://github.com/ppx123-web/claude-config --skill wechat-article-fetcher

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill consolidates the effort of collecting, ranking, and saving WeChat official account articles based on your research interests (AI Agent, System Design, GitHub Open Source), delivering ready-to-use insights.

Core Features & Use Cases

Intelligent ranking of articles against predefined research interests.
Multi-account support: fetch from specific accounts or all followed accounts.
Date filtering and Obsidian integration to save structured reports.
Output tailored to Obsidian markdown with frontmatter and actionable items.

Quick Start

Ask the AI to fetch yesterday's WeChat articles and save the report to Obsidian.

Frequently Asked Questions about wechat-article-fetcher

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automatically rank and save WeChat articles to Obsidian?▼

You can automatically rank and save WeChat articles to Obsidian by fetching posts from followed accounts, scoring them against research interests like AI Agent and System Design, and generating a Markdown report with frontmatter appended to your vault.

Can I fetch WeChat articles from specific official accounts with date filtering?▼

Yes, you can fetch WeChat articles from specific official accounts or all followed accounts. The tool applies date filtering to retrieve targeted posts and scores them based on keyword tiers matching your research interests.

How does keyword scoring work for ranking WeChat articles?▼

Keyword scoring for ranking WeChat articles works by evaluating fetched content against predefined tiers of research interests such as AI Agent, System Design, and GitHub Open Source to determine relevance and generate ranked insights.

Does this article fetcher require MCP integration for retrieving WeChat posts?▼

Yes, retrieving WeChat posts requires MCP integration. The tool implements MCP-based article retrieval to access official account content, apply keyword-based scoring, and output structured Obsidian Markdown reports.

What is the best way to consolidate WeChat articles based on research interests?▼

The best way to consolidate WeChat articles based on research interests is using an automated fetcher that scores posts across predefined keyword tiers, ranks them by relevance, and delivers ready-to-use Markdown insights.