vivekchand

vivekchand / clawmetry

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See your agent think. Real-time observability dashboard for OpenClaw AI agents.

clawmetry.com ai-agent dashboard monitoring observability openclaw
107
20
69% credibility
Found Feb 19, 2026 at 31 stars 3x -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

ClawMetry is an open-source dashboard providing real-time visualizations, metrics, and logs for monitoring AI agents from the OpenClaw framework.

How It Works

1
🔍 Discover ClawMetry

You hear about a simple tool that lets you watch your AI helpers think step by step in real time.

2
📦 Set it up quickly

You grab the tool with one easy instruction, and it finds your AI setup automatically.

3
🚀 Start the viewer

With a single go command, a window opens in your web browser showing your agents at work.

4
👁️ Watch the flow live

You see colorful animations of thoughts moving through channels, brains, and tools like magic.

5
📈 Check health and costs

Glance at activity heatmaps, token usage breakdowns, and ongoing sessions to stay in control.

6
📋 Explore logs and memory

Browse real-time colored logs, chat histories, and notes to understand every detail.

🎉 See your agents clearly

Now you have full visibility into how your AI agents think, spend, and perform every day.

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Star Growth

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AI-Generated Review

What is clawmetry?

Clawmetry delivers a real-time dashboard to see your agent think, built in Python with Flask for OpenClaw AI agents. Fire up `pip install clawmetry && clawmetry` for instant access at localhost:8900 to live flow diagrams tracking messages through channels, brains, and tools; token/cost breakdowns; active sessions; cron jobs; color logs; memory files; and chat transcripts. It auto-detects your workspace, solving opaque agent behavior without setup hassles—perfect for seeing agent meaning in action.

Why is it gaining traction?

Zero-config magic hooks devs: detects OpenClaw setups, launches animated flows to visualize agent flugzeug (thinking paths), and tracks costs over time like github stars over time. Beats generic tools by focusing on agent-specific views—usage heatmaps, session histories akin to github copilot chat history, cron status—making debugging feel effortless versus wiring Prometheus or custom logs.

Who should use this?

OpenClaw builders monitoring autonomous agents, indie AI devs tracking token burn on crons/sessions, or teams needing quick observability for boarding-pass-like agent flows (see agent at gate alaska airlines vibes). Ideal for those eyeing github commit history patterns in agent runs or github copilot usage spikes without extra tooling.

Verdict

Grab it if you're deep in OpenClaw—crisp docs, PyPI ease, and MIT license make it a no-brainer despite 13 stars and 0.7% credibility score signaling early days. Low maturity means watch for edge cases; otherwise, skip for broader agent frameworks.

(198 words)

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