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Wechat Search

ASecurity

Search WeChat Official Account articles using OpenClaw's web search, Tavily API, and web fetch capabilities with compliance-focused design.

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  • Added November 11, 2026
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A100/100

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Scanned November 11, 2026

npx -y skills add johnalbertini14-glitch/openclaw-skills --skill wechat-search --agent claude-code

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SKILL.md
---
name: wechat-search
description: Search WeChat Official Account articles using OpenClaw's web search, Tavily API, and web fetch capabilities with compliance-focused design.
---

# WeChat Search Skill

Search for WeChat Official Account (微信公众号) articles using a compliant, three-layer approach that prioritizes legal search APIs and falls back to respectful web scraping when needed.

## Features
- **Compliant Design**: Prioritizes legal search APIs, respects robots.txt and rate limits
- **Three-Layer Strategy**: 
  - Primary: OpenClaw web_search (Brave Search API)
  - Secondary: Tavily Search API (if Brave unavailable)
  - Fallback: Direct page fetching from WeChat search
- **Recent Results**: Returns the 5 most recent articles by default (configurable)
- **Time Filtering**: Support for date range and recency filters
- **Multiple Output Formats**: Text, JSON, and markdown formats available

## Prerequisites
- **OpenClaw Web Tools**: Requires `web_search`, `web_fetch` tools to be available
- **API Keys** (optional but recommended):
  - Brave Search API Key (for primary search)
  - Tavily API Key (for secondary search, already configured in your environment)

## Usage

### Basic Search
```bash
wechat-search "人工智能"
```

### Advanced Options
```bash
# Return 10 results instead of default 5
wechat-search "机器学习" --max-results 10

# Search within past week
wechat-search "大模型" --past-week

# Custom date range
wechat-search "AI应用" --from 2026-01-01 --to 2026-02-01

# JSON output format
wechat-search "开源AI" --output json

# Force specific strategy
wechat-search "最新技术" --strategy tavily_only
```

## Configuration
Create `~/.openclaw/wechat-search-config.json` to customize behavior:

```json
{
  "defaultMaxResults": 5,
  "maxResultsLimit": 20,
  "requestDelayMs": 5000,
  "cacheDurationHours": 1,
  "userAgent": "OpenClaw-WeChat-Search-Bot/1.0 (+https://github.com/your-username/wechat-search-skill)"
}
```

## Search Strategy Details

### Layer 1: OpenClaw Web Search (Brave Search)
- Uses Brave Search API with `site:mp.weixin.qq.com` filter
- Fastest and most reliable when API key is configured
- Respects search engine's indexing and ranking

### Layer 2: Tavily Search API
- Activated when Brave Search is unavailable or fails
- Uses Tavily's AI-powered search with WeChat site restriction
- Provides high-quality, relevant results with good coverage

### Layer 3: Direct Web Fetch
- Final fallback when both APIs are unavailable
- Scrapes WeChat search results directly from搜狗微信搜索
- Implements proper delays and respects robots.txt
- Parses HTML to extract article metadata

## Compliance & Ethics
- **Respects robots.txt**: Checks and follows robots.txt directives
- **Rate limiting**: Minimum 5-second delay between requests
- **Transparent identification**: Clear User-Agent string identifying the bot
- **Public content only**: Only accesses publicly available articles
- **No data retention**: Does not store full article content, only metadata

## Error Handling
- Automatic retry on network failures (up to 3 attempts)
- Graceful fallback between all three search strategies
- Clear error messages for debugging
- Handles API key missing scenarios gracefully

## Future Enhancements
- RSS feed integration support
- Article content summarization
- Author/subscription management
- Enhanced filtering options

This skill is designed to be both useful and responsible, providing access to valuable WeChat Official Account content while respecting platform rules and legal requirements.

Files in this skill

  • README.md3.2 KB
  • SKILL.md3.5 KB
  • _meta.json460 B
  • debug_test.py448 B
  • example-config.json324 B
  • requirements.txt39 B
  • wechat_search.py6.9 KB
  • wechat_search_fixed.py11.7 KB
  • wechat_search_simple.py5 KB

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