GoKawiilAgentSight
AgentSight is a zero-instrumentation AI Agent observability tool based on eBPF. It captures LLM API calls, Token consumption, and process behavior at the kernel level without modifying Agent code.
Overview
AgentSight provides full-stack observability for AI Agents running on Linux:
Capability Description Token consumption analysis Multi-dimensional Token accounting by agent, task, and model Behavior audit Complete tracing of LLM calls and process execution Dashboard visualization Web UI for real-time Token trends, Agent health, and session traces Agent auto-discovery Automatic detection of running AI Agent processes Interruption detection Detection of LLM errors, SSE truncation, context overflow, and crashes External log export Supports exporting structured events to external log services
Prerequisites
Requirement Minimum OS Linux Kernel >= 5.8 (BTF support required) Privileges root or CAP_BPF (for eBPF probes) ANOLISA raw package Linux x86_64, system mode
macOS: On macOS, AgentSight provides two commands — trace (trajectory collector that scans local JSONL session files, no eBPF) and serve (Dashboard viewer). All other eBPF-dependent commands are Linux-only.
Installation
Install the published component with the ANOLISA CLI:
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