Agent Skillsbrowser-act/skills › wechat-article-search-api-skill

wechat-article-search-api-skill

GitHub

通过BrowserAct API自动提取微信公众号文章全文。支持关键词搜索、日期过滤及数量限制,提供结构化数据。具备无验证码、无IP限制、高成本效益等优势,适用于竞品监控、舆情分析及媒体研究等场景。

solutions/social-listening/wechat-article-search-api-skill/SKILL.md browser-act/skills

Trigger Scenarios

获取微信公众号文章全文内容 基于关键词搜索微信文章 监控特定公众号或品牌的最新动态 进行社交媒体情感分析数据采集 自动化提取微信文章内容

Install

npx skills add browser-act/skills --skill wechat-article-search-api-skill -g -y
More Options

Non-standard path

npx skills add https://github.com/browser-act/skills/tree/main/solutions/social-listening/wechat-article-search-api-skill -g -y

Use without installing

npx skills use browser-act/skills@wechat-article-search-api-skill

指定 Agent (Claude Code)

npx skills add browser-act/skills --skill wechat-article-search-api-skill -a claude-code -g -y

安装 repo 全部 skill

npx skills add browser-act/skills --all -g -y

预览 repo 内 skill

npx skills add browser-act/skills --list

SKILL.md

Frontmatter
{
    "name": "wechat-article-search-api-skill",
    "metadata": {
        "openclaw": {
            "emoji": "🌐",
            "requires": {
                "env": [
                    "BROWSERACT_API_KEY"
                ],
                "bins": [
                    "python"
                ]
            }
        }
    },
    "description": "This skill helps users extract full article contents from WeChat using the BrowserAct API. The Agent should proactively apply this skill when users express needs like finding full WeChat articles for specific keywords, tracking WeChat public accounts for industry trends, extracting WeChat article contents for media research, monitoring public relations on WeChat platforms, collecting competitor updates from WeChat, getting full article body from WeChat links, monitoring brand exposure on WeChat articles, retrieving structured WeChat data for sentiment analysis, summarizing daily news from WeChat, getting author and publication date for WeChat articles, or automating WeChat content extraction without scraping."
}

WeChat Article Search API

📖 Introduction

This skill provides users with automated WeChat article extraction through the BrowserAct WeChat Article Search API template. It allows for the direct extraction of full-content, structured WeChat articles based on keyword searches. Simply provide search keywords and optional date filters, and you can obtain comprehensive article data including the full body text.

✨ Features

  1. No hallucinations, ensuring stable and precise data extraction: Pre-configured workflows avoid AI-generated hallucinations.
  2. No CAPTCHA issues: No need to handle reCAPTCHA or other verification challenges.
  3. No IP restrictions or geo-blocking: No need to handle regional IP limitations.
  4. Faster execution: Task execution is faster compared to pure AI-driven browser automation solutions.
  5. Extremely high cost-effectiveness: Significantly reduces data acquisition costs compared to AI solutions that consume a large number of tokens.

🔑 API Key Guidance Flow

Before running, check the BROWSERACT_API_KEY environment variable. If not set, do not take other actions; request and wait for the user to provide it. The Agent must inform the user:

"Since you have not configured the BrowserAct API Key, please go to the BrowserAct Console to get your Key."

🛠️ Input Parameters

When invoking the script, the Agent should flexibly configure the following parameters based on user needs:

  1. keywords (Search Keywords)

    • Type: string
    • Description: Search keywords used to find WeChat articles. Can be an industry term, topic, or specific phrase.
    • Example: openclaw, AI agent, browser automation
  2. Date_limit (Extraction Limit)

    • Type: number
    • Description: Maximum number of articles to extract. For the first run, a smaller default value is recommended.
    • Default Value: 10
    • Suggestions: Use 5 to 10 for quick testing, larger numbers for batch research.
  3. publication_date (Publication Date Filter)

    • Type: string
    • Description: Filter articles by their publication date.
    • Example: 3月11日, March 10, 2026-03-11

🚀 Invocation Method

The Agent should execute the following independent script to achieve "one command, direct results":

# Example invocation
python -u ./scripts/wechat_article_search_api.py "keywords" limit "publication_date"

⏳ Run Status Monitoring

Because this task involves automated browser operations, it may take a long time (several minutes). While running, the script will continuously output timestamped status logs (e.g., [14:30:05] Task Status: running). Agent Instructions:

  • Keep monitoring the terminal output while waiting for the script to return results.
  • As long as the terminal continues to output new status logs, it means the task is running normally; do not misjudge it as deadlocked or unresponsive.
  • Only consider triggering the retry mechanism if the status remains unchanged for a long time, or the script stops outputting without returning results.

📊 Output Data Explanation

Upon successful execution, the script will parse and print the results directly from the API response. The results include:

  • url_link: Original article URL
  • publication_date: Article publication date
  • author: Article author or publishing account name
  • image_url: Main image URL or article cover image URL
  • body_content: Full body content of the article
  • title: Full article title

⚠️ Error Handling & Retry

During script execution, if an error occurs (such as network fluctuation or task failure), the Agent should follow this logic:

  1. Check the output content:

    • If the output contains "Invalid authorization", it means the API Key is invalid or expired. In this case, do not retry; guide the user to re-check and provide the correct API Key.
    • If the output does not contain "Invalid authorization" but the task fails (e.g., output starts with Error: or returns an empty result), the Agent should automatically try to execute the script one more time.
  2. Retry limit:

    • Automatic retry is limited to once. If the second attempt still fails, stop retrying and report the specific error message to the user.

🌟 Typical Use Cases

  1. Content Monitoring: Track mentions of specific brands or topics across WeChat articles.
  2. Media Research: Analyze full text of articles published by top WeChat accounts.
  3. Trend Tracking: Collect articles about rising industry trends (e.g., AI agents) for comprehensive reading.
  4. Knowledge Base Building: Extract deep-dive articles into an internal repository.
  5. Competitor Analysis: Review full-length posts released by competitor accounts.

Version History

  • 22aad3f Current 2026-07-11 17:14

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