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welink

Skill Infrastructure Poor

🔍微信聊天数据分析的本地化AI-agent(Docker/Windows/MacOS) · AI分身 / 大模型分析 / 好友排行 / 词云 / 情感趋势 / 群聊画像

167 starsAGPL-3.0 (check with legal)FreeQuick setup
Below standard — Significant caveats apply. Not recommended without careful review of the security and evaluation sections.

Extracts actionable insights from WeChat chat histories locally without cloud dependencies. Enables sentiment analysis, relationship mapping, and communication pattern discovery for teams operating in Chinese enterprises.

Teams in China-based organizations who need to analyze internal WeChat collaboration patterns and social dynamics without data leaving premises.

Claude Code Claude Cowork Claude Chat

https://github.com/runzhliu/welink

By runzhliu

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install runzhliu/welink

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars167Last updated2026-06-03LicenseAGPL-3.0 (check with legal)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-06-04 · scanner v1

Community Pulse New

No community discussions found yet. This doesn't mean the tool isn't good — it may be new or serve a niche use case.

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 167 GitHub stars; contributors unknown; last commit 1d ago; license AGPL-3.0.

Things to check

  • License (AGPL-3.0) may restrict commercial use. Check with your legal team.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
1/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score2.30 / 5.00 PoorEvaluatedJun 2026
Scored from trust signals (evidence-eval-v1): 167 GitHub stars; contributors unknown; last commit 1d ago; license AGPL-3.0.

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