WeChat Chat Analyzer
Paste the following prompt into your AI chat to install this skill:
Please follow https://skillhub.cn/install/skillhub.md and install @user_4e735797/wechat-analyzer.
About this skill
Problem
WeChat private and group messages are hard to review manually. It is difficult to answer concrete questions: who initiates more, whether the relationship is unbalanced, how much late-night chat occurs, how present someone is in a group, and which topics deserve follow-up. wechat-analyzer turns these questions into a searchable, comparable analysis flow.
How It Works
- It uses
wx-clito read WeChat local database data on macOS, including private and group chats, with stable fields for group identity. - A Flask interface provides contact search and analysis entry points for selected chat scopes.
- LLM outputs are structured into cards: private chat includes
signal reading,reply advice,relationship insight,topic mining,todo extraction, andemotion tracking. - Group chat includes topic leaderboard, member profiles, group vibe, signal radar, personal trace, and role map, rendered as graphical components.
- Relationship diagnostics focus on message ratio, daily volume, monthly trend, late-night share, response speed, and who speaks first.
Boundaries
The skill targets logged-in macOS WeChat and requires readable local database access. config.json must include the database path, LLM API key, and your own nickname. Results depend on LLM inference from sampled messages, making them useful for personal review and relationship observation, but not legal evidence or medical advice. Group outputs are optimized for casual WeChat groups, not formal organizational decision analysis.
Use Cases
- Review private chats to see who initiates, late-night share, and response-speed imbalance.
- Analyze work group messages to extract frequent topics, active members, group vibe, and key signals.
- When writing a retro, identify todos, emotion shifts, and follow-up reply lines from the last 7 days.
- Before a conversation, inspect message density, first-speech ratio, and topic heat.
Best For
- Communicators reviewing close relationships or friend chats who care about who initiates, late-night share, and emotion signals.
- Product or ops managers handling multiple WeChat work groups who need topic, member activity, and group vibe extraction.
- Knowledge workers organizing personal tasks who want todos, topics, and actionable replies from chats.
- Data analysts studying social interaction patterns who need message ratio, response speed, and first-speech ratio.
Related Skills
Query Douyin creator videos, image/text posts, and short-drama series by sec_user_id or profile URL with paginated list retrieval.
Uses CDP-controlled browser screenshots of Douyin video pages and multimodal AI to extract teaching points into a Markdown report.
Query Douyin hot searches and works with SocialDataX API or MCP tools, supporting keyword, sorting, time range, duration, content type, and pagination.
Fetch the GitHub Trending leaderboard and generate fact-grounded project analysis, trend hypotheses, and directional insights.