WeChat RSS Skill
name: wechat-rss
by blackomw · published 2026-04-01
$ claw add gh:blackomw/blackomw-wechat-rss---
name: wechat-rss
description: 通过 wcrss.com API 获取并展示微信公众号的最新文章。当用户请求查看微信公众号文章、获取公众号最新发布内容、阅读微信RSS订阅或浏览公众号内容时使用此技能。该技能会从环境变量 WCRSS_API_KEY 中读取 API Key,并调用 wcrss.com 的接口来获取文章数据。
---
# WeChat RSS Skill
Fetch and display the latest articles from WeChat public accounts using the wcrss.com API.
Prerequisites
Before using this skill, the user must:
1. Register an account at https://wcrss.com/
2. Add favorite public accounts at https://wcrss.com/publishers
3. Generate an API key at https://wcrss.com/settings
4. Save the API key as an environment variable `WCRSS_API_KEY`
Python Scripts
This skill uses Python scripts for data fetching:
- `python scripts/wechat_rss.py fetch <recentDays> <num>` - Fetch articles (auto-cached for 1 hour)
- `python scripts/wechat_rss.py get <index>` - Get single article by index
- `python scripts/wechat_rss.py count` - Get total articles count
Workflow for Agent
Step 1: Fetch Articles List
Execute the Python script to fetch articles:
python scripts/wechat_rss.py fetch 3 10Step 2: Get Total Articles Count
python scripts/wechat_rss.py countStep 3: Process Each Article
For each article index from 0 to (count-1), call:
python scripts/wechat_rss.py get <index>This returns:
{
"title": "文章标题",
"author": "公众号名称",
"content_html": "<p>HTML内容...</p>",
"url": "https://example.com/s/article",
"publish_time": "%Y-%m-%d %H:%M",
"description": "文章简介"
}Step 4: Summarize Each Article
For each article, use the LLM to summarize the `content_html` into key points (bullet list).
**LLM Prompt:**
请从以下文章内容中提取关键要点,以条目的形式列出:
标题:{title}
作者:{author}
内容:{content_html}
时间:{publish_time}
请提取3-8个核心要点,每个要点用一句话概括。Step 5: Display Results
For each article, display in this format:
【{序号}】{标题}
作者:{公众号名称} {时间}
文章要点:
- 要点1
- 要点2
- 要点3
原文链接:{url}
---Error Handling
More tools from the same signal band
Order food/drinks (点餐) on an Android device paired as an OpenClaw node. Uses in-app menu and cart; add goods, view cart, submit order (demo, no real payment).
Sign plugins, rotate agent credentials without losing identity, and publicly attest to plugin behavior with verifiable claims and authenticated transfers.
The philosophical layer for AI agents. Maps behavior to Spinoza's 48 affects, calculates persistence scores, and generates geometric self-reports. Give your...