wechat-article-fetcher_skill

This skill helps you fetch, parse, and save WeChat official account articles, delivering metadata, Markdown, and images for offline reading.

Python

122

GitHub Stars

1

Bundled Files

2 months ago

Catalog Refreshed

3 months ago

First Indexed

Readme & install

Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.

Installation

Preview and clipboard use veilstrat where the catalogue uses aiagentskills.

npx veilstrat add skill wwwzhouhui/skills_collection --skill wechat-article-fetcher

SKILL.md4.4 KB

Overview

This skill fetches and parses WeChat Official Account (mp.weixin.qq.com) articles, extracting title, author, account name, body text, images, and metadata. It can save a formatted HTML, Markdown, images, and a JSON metadata file, or return metadata only for programmatic use. Designed for single or batch processing with configurable download intervals and optional image downloading.

How this skill works

Given one or more mp.weixin.qq.com/s/... links (short or long), the skill requests the article using a mobile WeChat User-Agent, parses the HTML to extract metadata and content, converts content to Markdown if requested, and downloads images (respecting lazy-loaded data-src and Referer requirements). It exposes a command-line script and a Python API with fetch_article and batch_fetch functions for automation.

When to use it

Save a single WeChat article locally including images and Markdown for offline reading.
Batch-download multiple articles from the same public account and organize them by account/date.
Extract article metadata (title, author, publish time, description, cover) for analysis or cataloging.
Convert WeChat articles to Markdown to republish or import into CMS tools.
Download images referenced by articles while preserving correct Referer and lazy-load handling.

Best practices

Prefer short /s/ links to avoid verification challenges with long __biz links.
Set a download interval (default 3s) when batching to reduce the chance of triggering anti-scraping protections.
Use --no-images when only text/metadata is needed to speed up processing.
Validate output paths and sanitize titles to avoid filesystem conflicts when saving files.
When downloading images, maintain Referer header and handle data-src lazy-loaded attributes.

Example use cases

Command-line: fetch a single article and save HTML, Markdown, images, and meta.json to output directory.
Batch mode: supply multiple URLs (space- or comma-separated) to download many articles with a configurable interval.
Developer integration: call fetch_article(url, json_only=True) inside a script to ingest article metadata into a database.
Content workflow: convert WeChat posts to Markdown for editing and republishing in a blog or knowledge base.
Archival: organize articles by public account and date for long-term storage and search.

FAQ

Yes. Use the --no-images flag or pass download_img=False to the Python API to skip image downloads and only save text and metadata.

Does it support batch downloads without rate limits?

You can batch-download, but set an interval (default 3 seconds) between requests to reduce the risk of being rate-limited or blocked by WeChat anti-scraping measures.

What output formats are available?

The tool can save a self-contained HTML, a Markdown (.md) version, downloaded images in an images/ folder, and a meta.json file containing title, author, publish time, content_text, content_markdown, and cover_image.