zarazhangrui

zarazhangrui / lark-minutes-tasks

Public

AI agent skill: read Lark meeting transcripts, extract action items, and actually get them done

17
5
89% credibility
Found Apr 01, 2026 at 17 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
AI Summary

An AI agent skill that analyzes Lark/Feishu meeting transcripts, identifies action items using wake words, lets users select tasks, and executes them like sending messages or scheduling meetings.

How It Works

1
📰 Discover the meeting helper

You hear about a handy AI skill that reads your meeting notes and turns talk into action.

2
📥 Add it to your AI assistant

You simply place the helper file into your AI friend's skill folder, like adding a new recipe to a cookbook.

3
🔗 Link your meeting app

You connect your Lark account to let the AI peek at your meeting records safely.

4
📝 Share meeting notes

You tell your AI the web link to your meeting transcript, and it starts reading everything.

5
📋 Review smart task list

The AI shows a clear numbered list of all action items, including hidden ones and your special voice commands from the meeting.

6
✅ Pick and go

You select which tasks to handle, and the AI jumps in to send messages, book meetings, or create docs for you.

🎉 Tasks all done

Sit back as your to-dos vanish – everything from the meeting is completed automatically.

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AI-Generated Review

What is lark-minutes-tasks?

This agent skills repo turns Lark/Feishu meeting transcripts into executed action items, not just a todo list. Paste a minutes URL or doc link via `/minutes` command, and it scans for wake word triggers, extracts explicit and implied tasks, lets you approve a list, then handles them—like drafting messages to clipboard, scheduling meetings via calendar checks, or creating Lark docs and tasks. Built as a simple Markdown skill for agent github claude or similar setups, it relies on Lark CLI for auth and access.

Why is it gaining traction?

It stands out in the agent skills marketplace by actually executing tasks across types like research, doc creation, or product trials, using agent github copilot-style integration but focused on post-meeting automation. The wake word hooks devs who verbally delegate during calls without manual follow-up, and drop-in install for agent skills github or vscode agents makes it a quick win over verbose agent github action alternatives. Early buzz on agent github reddit threads praises the hands-off execution.

Who should use this?

PMs and engineering leads in Lark-using teams who waste hours chasing meeting follow-ups. Devs building agent skills library extensions or experimenting with agent skills anthropic/Claude workflows. Remote teams needing agent github openai or microsoft copilot-like automation for scheduling and docs.

Verdict

Worth a test for Lark-heavy agent users—solid docs and MIT license, but 15 stars and 0.9% credibility score signal early-stage maturity with no tests visible. Fork and extend if it fits your agent skills io stack.

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