Best AI Agent Skills for Monitoring & Observability

Open-source AI copilot that lets you chat with your observability data and code 🧙‍♂️

AI observability platform for production LLM and agent systems.

Local-first observability for AI agents. Tokens, cost, latency, and traces — stored locally, queryable with SQL.

DataOps Observability Integration Agents are part of DataKitchen's Open Source Data Observability. They connect to various ETL, ELT, BI, data science, data visualization, data governance, and data analytic tools. They provide logs, messages, metrics, overall run-time start/stop, subtask status, and scheduling information to DataOps Observability.

Python SDK for Agent AI Observability, Monitoring and Evaluation Framework. Includes features like agent, llm and tools tracing, debugging multi-agentic system, self-hosted dashboard and advanced analytics with timeline and execution graph view

🪁 A lightweight, modern Kubernetes dashboard that unifies multi-cluster and resource management, enterprise-grade user governance (OAuth, RBAC, and audit logs), and AI agents in one workspace. Not just a tool, but more like a platform.

Langtrace 🔍 is an open-source, Open Telemetry based end-to-end observability tool for LLM applications, providing real-time tracing, evaluations and metrics for popular LLMs, LLM frameworks, vectorDBs and more.. Integrate using Typescript, Python. 🚀💻📊

🔍 LangKit: An open-source toolkit for monitoring Large Language Models (LLMs). 📚 Extracts signals from prompts & responses, ensuring safety & security. 🛡️ Features include text quality, relevance metrics, & sentiment analysis. 📊 A comprehensive tool for LLM observability. 👀

Official plugin for OpenClaw that exports agent traces to Opik. See and monitor agent behaviour, cost, tokens, errors and more.

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