| name | goodqunbot |
| displayName | 微信消息助手 |
| description | AI-powered WeChat message assistant. Retrieve recent messages from contacts/groups and send messages directly through AI chat. Windows 10/11 only. Requires WeChat PC client logged in. |
微信消息助手 (WeChat Message Assistant)
This skill enables AI to interact with WeChat directly through AI chat, providing two core capabilities: retrieving recent messages and sending messages to contacts or groups.
Platform Requirements
- OS: Windows 10/11 only
- WeChat: WeChat PC client must be installed, running, and logged in
- Python: Python 3.11+ (automatically handled by Goodable)
Core Capabilities
1. Retrieve Recent Messages
Fetch the last 10-15 messages from any WeChat contact or group chat.
What you can ask:
Get the last 15 messages from "张三"
Show me recent messages from "Product Team" group
Retrieve messages from "李四", last 10 only
What AI will do:
- Opens the specified chat in WeChat
- Retrieves the requested number of messages (default: 15, max: 100)
- Returns messages with timestamp, sender, and content
- Formats as structured JSON for easy parsing
2. Send Messages
Send a text message to any WeChat contact or group chat.
What you can ask:
Send "Meeting at 3pm" to "张三"
Message "Product Team" group: "Release notes updated"
Tell "李四": "Please review the document"
What AI will do:
- Opens the specified chat in WeChat
- Sends the message content
- Confirms successful delivery
How to Use
Prerequisites
Before using this skill, ensure:
- WeChat PC client is running
- You are logged into your WeChat account
- The contact/group name you specify exists in your WeChat
Example Usage
Scenario 1: Check messages from a colleague
User: "帮我看一下张三最近给我发了什么消息"
AI: [Runs get_messages.py script]
AI: "张三最近的5条消息：
1. [2024-01-28 10:30] 张三: 会议资料已发送
2. [2024-01-28 11:00] 张三: 请查收
..."
Scenario 2: Send a message
User: "给产品群发个消息：今天下午3点开会"
AI: [Runs send_message.py script]
AI: "消息已成功发送到产品群"
Instructions for AI
When the user requests WeChat message operations:
1. Retrieve Messages
Run the get_messages.py script:
python scripts/get_messages.py "<Contact/Group Name>" [count]
Parameters:
Contact/Group Name: Exact name as shown in WeChat (required)count: Number of recent messages to retrieve (optional, default: 15, max: 100)
Output Format:
The script returns JSON with message details:
[
{
"time": "2024-01-28 10:30:45",
"sender": "张三",
"content": "会议资料已发送",
"type": "text"
}
]
IMPORTANT - Output Formatting for User:
After successfully retrieving messages, you MUST format them in a clean, readable way. DO NOT show raw JSON to the user.
For 5 or fewer messages - Use a numbered list:
📨 **张三** 的最近消息：
1. [2024-01-28 10:30] 张三: 会议资料已发送
2. [2024-01-28 11:00] 张三: 请查收
3. [2024-01-28 14:30] 你: 好的，已收到
Tips:
- Always include contact/group name in the header
- Keep timestamps concise (remove date if same day)
- Group consecutive messages from same sender when appropriate
- Highlight important information if user asks for summary
Error Handling:
- If WeChat is not running: "WeChat PC client is not running or not logged in"
- If contact not found: "Contact or group 'xxx' not found"
- Parse the error and provide user-friendly explanation in Chinese
2. Send Messages
Run the send_message.py script:
python scripts/send_message.py "<Contact/Group Name>" "<Message Content>"
Parameters:
Contact/Group Name: Exact name as shown in WeChat (required)Message Content: Text message to send (required, cannot be empty)
Output:
- Success: "Message sent successfully to 'xxx'"
- Failure: Error message with details
Important Notes:
- Always enclose contact names and message content in quotes
- Contact names must match exactly as shown in WeChat
- For group chats, use the full group name
- Only text messages are supported (no images/files/emojis)
3. Best Practices
Name Matching:
- Ask user to confirm the exact contact/group name if unsure
- Suggest checking WeChat contact list for correct spelling
- Chinese names are case-sensitive and must match exactly
Error Recovery:
- If "WeChat not found" error: Ask user to start WeChat and log in
- If "Contact not found" error: Ask user to verify the name
- If script fails: Check if Python environment is properly set up
User Experience:
- Summarize retrieved messages in a readable format
- Confirm before sending messages if content seems important
- Provide context about what happened after each operation
Technical Details
Script Locations
skills/goodqunbot/
├── SKILL.md # This file
├── scripts/
│ ├── get_messages.py # Retrieve messages
│ └── send_message.py # Send messages
└── wxauto_lib/ # WeChat automation library (pyc bytecode)
Implementation
Both scripts use the wxauto library (RPA-based WeChat automation):
get_messages.py:
- Initializes WeChat instance
- Opens specified chat with
wx.ChatWith(who)
- Retrieves all messages with
wx.GetAllMessage(savepic=False, savefile=False)
- Returns recent N messages as JSON
send_message.py:
- Initializes WeChat instance
- Sends message with
wx.SendMsg(msg=message, who=who, clear=True)
- Returns success/failure status
Limitations
- Platform: Windows only (wxauto uses Windows API)
- Message Types: Text only (no images, files, or rich media)
- Rate Limits: May be subject to WeChat's anti-spam mechanisms
- Accuracy: Contact name must match exactly (case-sensitive)
- State Dependency: Requires WeChat PC client to be running and logged in
Troubleshooting
| Issue | Solution |
|---|
| "WeChat window not found" | Start WeChat PC client and log in |
| "Contact not found" | Verify exact contact/group name in WeChat |
| Script timeout | Check if WeChat is responding, restart if frozen |
| Import error | Ensure wxauto_lib directory exists in goodqunbot |
| Permission error | Run with appropriate user permissions on Windows |
Privacy & Security
- Local Only: All operations are local, no data sent to external servers
- Read-Only Access: get_messages.py only reads, doesn't modify chat history
- User Control: send_message.py only sends when explicitly requested
- No Logging: Messages are not stored or logged by the scripts
- Compliance: Use responsibly and comply with WeChat Terms of Service
Related Features
This skill complements the GoodQunBot App (template.json), which provides:
- Web UI for browsing all groups
- AI-powered chat summaries
- Data visualization (activity charts, word clouds)
- Member management and business opportunity discovery
Skill vs App:
- Skill Mode: Quick AI-driven message operations in chat
- App Mode: Full-featured web interface for comprehensive chat management
- Both modes share the same wxauto library and work independently
