metrik
Centralized quota and token consumption monitoring across multiple AI service providers reduces unexpected API failures, optimizes costs, and prevents overag…
Metrik 可以集中查看本机多个 Agent 的配额余量和 Token 消耗,目前支持 ChatGPT、Claude、GLM、Kimi 等主流 AI 服务。
- Monitor Claude token usage across multiple local AI agents simultaneously
- Track quota remaining for ChatGPT, Claude, GLM, and Kimi in one dashboard
- Alert when any AI service approaches spending limits or quota exhaustion
Centralized quota and token consumption monitoring across multiple AI service providers reduces unexpected API failures, optimizes costs, and prevents overages that disrupt development workflows.
Engineering teams managing multiple AI API integrations needing unified visibility into usage and quota limits.
https://github.com/keros68/metrik
By keros68
How to Get It
claude plugins install keros68/metrik
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me monitor Claude token usage across multiple local AI agents simultaneously
Trust Signals Auto-scanned
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): 95 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
- 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
Scored from trust signals (evidence-eval-v1): 95 GitHub stars; contributors unknown; last commit 0d ago; license AGPL-3.0.