Does this skill require a specific SDK?

While the skill provides the architecture and patterns, full implementation of custom hook triggers typically requires the Claude Agent SDK.

Why use hook-based architecture for AI agents?

It provides transparency into the AI execution process, allowing developers to monitor, log, and visualize agent actions in real-time for better debugging and oversight.

What are Claude Code hooks?

Hooks are trigger points in the Claude Code execution cycle, such as PreToolUse or PostToolUse, that allow external scripts to intercept and process data during agent operations.

What is ADW observability?

AI Developer Workflow (ADW) observability is the practice of tracking the steps, tools, and logic used by AI agents to ensure they are performing tasks correctly and efficiently.

Can I stream these events to a web interface?

Yes, the architecture specifically includes patterns for WebSocket broadcasting to enable real-time swimlane visualizations and monitoring dashboards.

Hook Event Architecture

Name: Hook Event Architecture
Author: melodic-software

bymelodic-software

•

分析与监控

Architects robust, hook-based event systems to monitor and broadcast real-time AI agent activities within Claude Code workflows.

关于

This skill enables developers to design and implement sophisticated observability layers for AI Developer Workflows (ADW) by leveraging Claude Code's internal hook system. It provides standardized patterns for capturing tool usage, agent thinking, and system steps, then piping that data through asynchronous pipelines for database logging, WebSocket broadcasting, and AI-powered event summarization. It is essential for building dashboards, audit logs, and real-time monitoring tools that provide deep visibility into how an AI agent interacts with a codebase.

主要功能

Standardized ADW event schemas with Pydantic model support
Real-time event pipeline and WebSocket broadcasting patterns
Hook-based event capturing for tool usage and agent thinking
Structured logging and database schema design for activity tracking
AI-powered event summarization using Claude Haiku
12 GitHub stars

使用场景

Monitoring agent performance metrics and tool execution durations
Building real-time observability dashboards for AI developer agents
Creating comprehensive audit logs for AI-driven code modifications

关于

主要功能

Standardized ADW event schemas with Pydantic model support
Real-time event pipeline and WebSocket broadcasting patterns
Hook-based event capturing for tool usage and agent thinking
Structured logging and database schema design for activity tracking
AI-powered event summarization using Claude Haiku
12 GitHub stars

使用场景

Monitoring agent performance metrics and tool execution durations
Building real-time observability dashboards for AI developer agents
Creating comprehensive audit logs for AI-driven code modifications