TypingMindTypingMindThe best frontend for AI
Wechat Article Search logo

Wechat Article Search

Community
zjp1997720
wechat-article-search

搜索微信公众号文章技能。通过微信搜索获取文章列表，覆盖科技/AI、社会热点、财经、教育、职场等各类中文资讯；可按关键词检索并返回标题、概要、发布时间、来源公众号与链接。当用户需要查找微信公众号文章、整理参考资料或快速获取文章信息时使用此技能。

Overview

Publisherzjp1997720
Repositoryzhijian-skills
Skill namewechat-article-search
Stars
780
Forks
99
Bundled files
6
LicenseMIT
Links
Skill sourceRepository
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by zjp1997720 on GitHub. Read the source before you install it.

Installation

Install the Wechat Article Search AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zjp1997720/zhijian-skills/tree/main/skills/wechat-article-search
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zjp1997720/zhijian-skills.git /tmp/zhijian-skills
mkdir -p .claude/skills
cp -r /tmp/zhijian-skills/skills/wechat-article-search .claude/skills/wechat-article-search
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Wechat Article Search in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Wechat Article Search on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Wechat Article Search is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

微信公众号文章搜索说明

适用场景

  • 用户说“帮我搜某个关键词的公众号文章/最近文章”
  • 需要快速拿到：标题、摘要、发布时间、公众号名称、可访问链接

工作流程

步骤1: 定位脚本和依赖

先把 SKILL_DIR 设为本次读取的 SKILL.md 所在目录（软链接先解析真实目录）。依赖在该目录内管理；已安装时直接使用，仅缺少依赖时按下文的仓库约定安装，不全局安装，也不在用户项目根目录安装。

步骤2: 使用已有输入

从用户请求提取关键词；未指定数量时用默认 10 条。已有关键词和范围时直接执行；只有缺少搜索主题时才询问。输出文件仅在用户要求保存时创建。

步骤3: 执行搜索命令

1、执行常规搜索命令

bash
node "$SKILL_DIR/scripts/search_wechat.js" "关键词"

特殊流程（可选）

  1. 执行包含数量限制的搜索命令
bash
node "$SKILL_DIR/scripts/search_wechat.js" "关键词"  -n 15
  1. 如果用户需要保存结果到文件，执行命令
bash
node "$SKILL_DIR/scripts/search_wechat.js" "关键词" -n 20 -o result.json
  1. 若想要获取微信文章域名的真实链接”，执行如下命令
bash
node "$SKILL_DIR/scripts/search_wechat.js" "关键词" -n 5 -r

参数说明

  • query：搜索关键词（必填）
  • -n, --num：返回数量（默认 10，最大 50）
  • -o, --output：输出 JSON 文件路径（可选）
  • -r, --resolve-url：尝试把中间链接解析成微信文章真实链接（会额外请求每条结果）

输出字段（文章对象）

文章标题、文章地址、文章概要、发布时间、来源公众号名称

常见问题处理

  • 结果为空：尝试更换关键词、更少的特殊字符、或稍后重试
  • 解析真实 URL 失败：这是常态（反爬限制）；可提示用户用浏览器打开中间链接

注意事项

  • 本工具仅用于学习和研究目的，请勿用于商业用途或大规模爬取。
  • 使用本工具时请遵守相关网站的使用条款和规定。
  • 过度使用可能导致 IP 被封禁，请谨慎使用。

Vault 适配说明（deepsight_vault 专属，原版无此段）

以下内容由大鹏的 vault 自动追加，用于把本 skill 接入 Obsidian 仓库生态。原版说明见上方。

依赖安装（本仓库约定）

本 skill 在仓库内自包含依赖，不要全局安装。首次使用或克隆仓库后，在本 skill 目录执行一次：

bash
cd "$SKILL_DIR"
npm install

cheerio 会装到本目录的 node_modules/，已被 .gitignore 排除。脚本通过 Node 的向上查找机制能 require('cheerio')，无需配 NODE_PATH。

单一真源与同步

  • 真源：本 Portfolio 的 skills/wechat-article-search/。
  • 安装入口可以是宿主 Skill 目录内的软链接；以本次读取路径解析后的真实目录为准，不假设所有宿主共享同步脚本。
  • 修改本 Portfolio 的 skills/wechat-article-search/ 真实来源；先解析软链接，不把安装入口当另一份源码。

与 wxmp-article-harvester 的衔接

两个 skill 职责互补，可串联使用：

环节skill输入输出
关键词发现（本 skill）wechat-article-search关键词，如「AI Agent」文章列表 JSON（标题/链接/摘要/来源/时间）
按账号/URL 抓正文wxmp-article-harvester公众号名或 mp.weixin.qq.com/s/... 链接结构化索引 + Markdown 正文

典型链路：先用本 skill 按关键词发现一批文章 URL 和来源公众号 → 再用 harvester 对感兴趣的账号或具体 URL 抓取正文导出到 ~/.dapeng/wxmp-harvester/exports/。

输出落点建议

  • 临时检索：直接看 stdout JSON，不落盘。
  • 需要留档：用 -o 写到 00_收件箱/Clippings/ 或对应项目的来源目录，文件名带关键词和日期，如 wechat-search-AI培训-2026-07-06.json。
  • 不要把搜索结果散落到仓库根目录。

反爬与免责（重要）

  • 数据源是搜狗微信搜索（weixin.sogou.com），受反爬策略影响，偶发返回空结果或被 antispider 拦截属正常现象，换关键词或稍后重试即可。
  • -r 解析真实链接在反爬收紧时成功率低，失败会保留搜狗中间链接并标记 url_resolved: false。
  • 仅用于学习研究和个人资料整理，不要高频调用、不要做大规模商业爬取。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Wechat Article Search AI skill do?

搜索微信公众号文章技能。通过微信搜索获取文章列表，覆盖科技/AI、社会热点、财经、教育、职场等各类中文资讯；可按关键词检索并返回标题、概要、发布时间、来源公众号与链接。当用户需要查找微信公众号文章、整理参考资料或快速获取文章信息时使用此技能。

Why use Wechat Article Search on TypingMind?

Because you install it once and use it with any model. Wechat Article Search is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Wechat Article Search in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zjp1997720/zhijian-skills/tree/main/skills/wechat-article-search. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Wechat Article Search?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Wechat Article Search?

As many as you like. As long as a model supports skills, you can use Wechat Article Search with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Wechat Article Search AI skill free?

Yes. It is published on GitHub by zjp1997720 under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Related AI Skills

View all
obra logo

Diagnosing Superpowers

obra
CommunityPopular

Use when a superpowers session went wrong and your human partner wants to know why — repeated work, ignored plans, stumbles, poor results, a skill that didn't fire, "it took too long", "why is it so…

26.3K
293.5K
19 files
View
obra logo

Brainstorming

obra
CommunityPopular

You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.

25.8K
288.1K
7 files
View
obra logo

Executing Plans

obra
CommunityPopular

Use when you have a written implementation plan to execute in a separate session with review checkpoints

25.8K
288.1K
Instructions
View
obra logo

Using Superpowers

obra
CommunityPopular

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

25.8K
288.1K
5 files
View

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇