I Can SEE EVERYTHING: Claude Code Hooks for Multi Agent Observability

Quick Overview

A multi-agent observability system for Claude Code agents provides real-time monitoring and visualization of agent behavior, enabling users to track events, filter by source, session, and type, and understand agent actions across multiple instances and codebases. This system facilitates scaling up agentic workflows by offering comprehensive insight into parallel operations, tool usage, and user interactions, ensuring engineers can effectively manage and debug complex AI systems.

Key Points: The system provides real-time monitoring and visualization of Claude Code agent events through a live dashboard. It uses Claude Code hooks to send event data to a Bun server, which stores it in an SQLite database and streams it to a Vue client via WebSockets. Users can filter events by source application, session ID, and event type for granular insights into agent activities. The system summarizes complex tool usage with a small, fast language model, offering quick, high-level understanding of agent actions. Full chat transcripts are available for stopped agent sessions, providing complete context for debugging and analysis. This multi-agent observability is crucial for scaling agentic engineering efforts, allowing for effective management and understanding of specialized, concurrent AI agents.

Context: This video demonstrates a multi-agent observability system built using Claude Code hooks, designed to provide real-time monitoring and insights into the behavior of multiple AI agents. The system addresses the challenge of tracking and understanding complex, concurrent operations performed by generative AI agents, which becomes crucial as agentic workflows scale up.

Detailed Analysis

The video introduces a multi-agent observability system designed to address the complexity of managing numerous Claude Code agents. When scaling up agentic workflows, tracking individual agent actions becomes challenging. This system provides real-time monitoring and visualization of Claude Code agent behavior by capturing, storing, and displaying hook events. The architecture involves multiple Claude Code agents firing their respective hooks, which send events via HTTP POST to a Bun server. This server then stores the data in an SQLite database for persistence and simultaneously streams these events to a Vue client dashboard using WebSockets. The live dashboard displays an 'Agent Event Stream' where users can see every action, including sub-tasks, planning, building, web scraping, and API calls. The system allows filtering events by source application, session ID, and event type, providing granular control over the displayed information. A 'Live Activity Pulse' visually represents event frequency over time. Crucially, the system uses a small, fast language model (like Haiku) to generate concise summaries of complex tool uses, allowing for quick understanding without deep diving into raw payloads. It also provides access to full chat transcripts for stopped agent sessions, offering complete context. This one-way data flow architecture simplifies monitoring, enabling engineers to understand agent performance, identify issues, and scale their agentic engineering efforts effectively across different codebases and devices.