chojs23

chojs23 / lazyagent

Public

Observe your coding agents and sessions in terminal

ai ai-agents claude claude-code cli
12
2
100% credibility
Found Apr 13, 2026 at 12 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 terminal UI for monitoring AI agent sessions across projects, displaying agents, subagents, tools, prompts, and outputs in an organized view.

How It Works

1
🔍 Discover lazyagent

You hear about a handy terminal viewer that lets you watch your AI helpers in action, seeing projects, chats, and steps all in one spot.

2
📥 Get it set up

Pick an easy way like a quick script or your usual tool to add it to your computer.

3
🔗 Link your AI buddy

Tell it which AI tool you use, like your coding assistant, so it can follow along.

4
🚀 Open the viewer

Run it in your terminal and watch your ongoing projects and chats appear automatically.

5
👀 See everything unfold

Glance at active sessions, spot busy helpers and their tools, and check if they're on track.

6
🔍 Zoom into details

Jump between lists of chats, helpers, steps, and outputs to understand what happened.

✅ Master your AI work

Now you easily catch when things go off course and keep your projects humming smoothly.

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AI-Generated Review

What is lazyagent?

Lazyagent is a Go-built terminal TUI for observing AI coding agents and sessions from Claude, Codex, and OpenCode. It ingests runtime events via hooks and plugins, grouping them by project directories into a live view of sessions, agents, tools, prompts, and outputs. Run `lazyagent init claude` to set up, then `lazyagent` launches the interface—perfect for tracking what your agents are doing without leaving the terminal.

Why is it gaining traction?

It stands out by unifying observation across multiple AI runtimes in one lightweight TUI, with panes for projects/sessions/agents/events/details, plus search, filtering by type/agent, and auto-follow. Developers dig the keybindings (tab/jk/gG/enter) for quick navigation and JSON/raw toggles, solving the pain of scattered transcripts during machine coding rounds. No bloat—just real-time insight into agent behavior.

Who should use this?

AI-assisted coders running Claude or OpenCode sessions for debugging/refactoring, especially those juggling subagents and tools in terminal workflows. Ideal for backend devs observing agent chains in coding interviews or open observe github experiments, or anyone tired of hunting JSONL files post-session.

Verdict

Grab it if you're deep into AI agents—solid TUI and multi-runtime hooks make observation painless, despite 12 stars and 1.0% credibility signaling early days. Docs are clear, tests thorough, but expect tweaks as it matures; brew install now for the lazy agent edge.

(187 words)

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