baoyu-wechat-summary

Name: baoyu-wechat-summary
Availability: InStock
Author: guanyang

Aggregate WeChat group chats into structured multi-round digests.

947|163|Updated Jan 13, 2026

Search Tags:#automation #memory #wechat #profiles #digest #leaderboard #group-chat

Ready to run

npx skills add https://github.com/guanyang/open-agent-hub --skill baoyu-wechat-summary-guanyang

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: baoyu-wechat-summary
Source: https://github.com/guanyang/open-agent-hub/tree/main/skills/baoyu-wechat-summary
Command: npx skills add https://github.com/guanyang/open-agent-hub --skill baoyu-wechat-summary-guanyang

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill extracts and consolidates WeChat group conversations into structured, readable digests. It maintains per-group history, per-user portraits, and a shared memory to preserve context across runs, enabling incremental updates and a roast variant.

Core Features & Use Cases

Automated group-digest generation: converts chat histories into compact reports with a per-user leaderboard and a clear narrative.
Profiles & memory: loads and updates 群友画像 (profiles) and a central memory file to keep context across digests.
Roast version support: optionally generates a spicy roast version with adjusted tone and sections.
Workspace integration: stores data under a project directory and supports extensible references, scripts, and assets as needed.

Quick Start

Tell the assistant to generate a daily WeChat group digest from the latest messages.

Frequently Asked Questions about baoyu-wechat-summary

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I generate a structured digest from WeChat group chat history?▼

A WeChat group digest converts chat histories into compact reports with a per-user leaderboard and clear narrative by loading and updating per-group memories, profiles, and history to handle incremental updates.

Can I automatically summarize WeChat group chats with user profiles and memory?▼

Yes, automated group-digest generation maintains per-user portraits and a central memory file to preserve context across runs, enabling incremental updates without losing historical profile data.

How does incremental update handling work for large batches of WeChat messages?▼

Incremental updates process large batches by loading and updating per-group memories, profiles, and history, ensuring new messages integrate with existing context without reprocessing the entire chat history.

What do I need to set up before fetching WeChat messages for digest generation?▼

Before generating digests, you need local tooling (wx-cli) to fetch messages and a configured project directory workspace to store digests, per-user profiles, and the shared memory file.

Does this WeChat digest tool support generating a roast or spicy summary variant?▼

Yes, an optional roast variant generates a spicy version of the WeChat digest with adjusted tone and sections, operating alongside the normal digest composition within the project directory.

What are the limitations of using local tooling to fetch WeChat group chats?▼

Limitations include dependency on local tooling (wx-cli) for fetching messages and the need to configure a project directory to properly store per-group memories, profiles, and history for incremental updates.