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wechat-article-search-api-skillwechat article 搜索 API 技能

Agent Skill

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

总安装

24,837

周安装

1,056

GitHub Stars

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下载量

8,701
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:wechat-article-search-api-skill(wechat article 搜索 API 技能)
来源仓库:https://github.com/ccmagia2-gif/wechat-article-search-api-skill
安装命令:
openclaw skills install wechat-article-search-api-skill
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install wechat-article-search-api-skill

简介

wechat-article-search-api-skill 使用 BrowserAct API 从微信提取完整文章内容。

  • 适用于不同意直接访问时强制启用内容抓取的开发场景。
  • 通过 clawhub 安装并使用 openclaw skills install wechat-article-search-api-skill 命令集成。
  • 使用前需确认权限范围,注意可能涉及 API 调用限制与内容合规性。
  • 建议查阅原始文档以了解触发条件与返回数据结构。

SKILL.md

name
wechat-article-search-api-skill
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.
metadata
{"clawdbot":{"emoji":"🌐","requires":{"bins":["python"],"env":["BROWSERACT_API_KEY"]}}}

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

  1. 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.

  1. 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.

  1. 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.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.93%
按下载量换算6,694

安全审计

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通过

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通过

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权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

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来源信息

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