Mininglamp-OSS

Mininglamp-OSS / octo-matter

Public

Lightweight task & matter service for the OCTO platform — REST API, timeline tracking, and LLM-powered extraction. Part of the OCTO open workplace for humans × AI agents.

ai-agents apache2 gin go golang
10
0
100% credibility
Found May 12, 2026 at 10 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

A simple service for creating, assigning, and tracking tasks with AI-powered extraction from chats, built-in timelines, and team notifications.

How It Works

1
👋 Discover OCTO Matter

You hear about OCTO, a friendly workplace tool where AI helpers manage tasks so you can focus on what matters.

2
📥 Get it ready

Download the task manager and start it up quickly with your notes storage and AI thinking service.

3
🔗 Connect your chat

Link it to your team's chat app so updates and new tasks arrive right where you talk.

4
✨ Turn chats into tasks

Paste chat messages or notes, and the AI smartly pulls out tasks, to-dos, and who should handle them.

5
📝 Assign and track

Give tasks to teammates, set reminders, and watch the timeline grow with every update.

6
🔔 Get notified automatically

Team members get instant alerts in chat when tasks change, assignees added, or progress shared.

🎉 Tasks stay organized

Your work flows smoothly with AI spotting action items, full history at a glance, and everyone in sync.

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AI-Generated Review

What is octo-matter?

Octo-matter is a lightweight Go service for task management in the OCTO platform, offering a REST API to create, assign, update, and close action items with built-in timeline tracking for comments and status changes. It uses LLM-powered extraction to turn chat snippets or meeting notes into structured todos via POST /matters/extract, stores data in MySQL, and pushes notifications to IM or webhooks. Developers get a single-query audit trail per task, perfect for humans and AI agents collaborating.

Why is it gaining traction?

Unlike bloated task managers, it bundles timeline and AI extraction in one lightweight API—no microservice sprawl for history reconstruction. Agents call one endpoint for todo drafts from text, with rate-limited LLM paths preventing abuse. Docker Compose quickstart and env-config make it a drop-in lightweight task tracker for agent workflows.

Who should use this?

Backend engineers integrating tasks into AI agent platforms like OCTO. Dev teams needing a lightweight task management tool with REST API for Linux/Windows prototypes. Builders of agent-driven apps wanting LLM extraction without custom RAG pipelines.

Verdict

Solid pick for OCTO users or lightweight task schedulers with agent smarts—quick to spin up via Docker. Low 10 stars and 1.0% credibility score mean it's immature; strong tests and bilingual docs help, but validate in staging first.

(198 words)

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