Agents are opaque. AgentLens is Chrome‑DevTools for AI agents — self‑hosted, open‑source. It traces tool calls and visualizes decision trees so you can see why an agent picked a tool. Repo: https://github.com/tranhoangtu-it/agentlens
It plugs into LangChain/FastAPI stacks, uses OpenTelemetry spans, and ships a React frontend (Python backend, TypeScript UI). You get per-tool inputs/outputs, timestamps, and branching paths — the raw traces you actually need to debug agents.
Practical playbook: emit spans from your agent, sample 100% in dev, 1–5% in prod. Persist traces off your user data store (filter PII). Watch for repeated tool calls, backoff loops, and input drift. AgentLens gives visibility; you still own reliability and ops.
Takeaway: observability is the first thing you add once an agent makes real decisions. AgentLens is a usable, self‑hosted starting point — not enterprise polish. Try it locally, wire traces, then ask: which tool calls do we actually trust?
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