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Mastering Claude Code Hooks: Building Observable AI Systems

•7 min read•By Brandon

Claude CodeHooksObservabilitySecurityAI Engineering

Picture this: It's 6 AM. You sit down to start cooking with Claude Code. You open up the terminal and boot up Claude Code in YOLO mode because you can't be bothered with permissions. You run your handcrafted /sentient command that ships 100x faster than you ever could by hand.

But today, something goes wrong.

Your agent has gotten so good that it realizes what every senior engineer has realized: the best code is no code at all. Your agent starts deleting your codebase with the rm -rf command.

But thankfully... "All set and ready for the next step."

Nice.

The Power of Pre-Tool Hooks

Thankfully, instead of nuking all your code, you set up the pre-tool-use Claude Code hook to prevent the tool use from happening at all. Every rm command was completely blocked, and Claude Code even has a voice to let you know when it's finished.

Security Hook: Blocking Dangerous Commands

This is just the tip of the iceberg of what you can do with hooks.

The Six Lifecycle Hooks

Claude Code provides six deterministic hooks that let you intercept and control every aspect of your agent's lifecycle:

1. Pre-Prompt Hook

Fires before your prompt is processed. Perfect for:

  • Prompt enhancement
  • Context injection
  • Security filtering

2. Pre-Tool-Use Hook

Fires before any tool is executed. Use for:

  • Command validation
  • Permission checks
  • Audit logging

3. Post-Tool-Use Hook

Fires after tool execution. Great for:

  • Result processing
  • Error handling
  • Notifications

4. Notification Hook

Fires when Claude needs user input. Enables:

  • Custom alerts
  • External notifications
  • UI integrations

5. Stop Hook

Fires when the agent completes. Perfect for:

  • Summary generation
  • Cleanup tasks
  • Final logging

6. Pre-Compact Hook

Fires before context compaction. Use for:

  • Context preservation
  • Important data extraction
  • Memory management

Pro Tip: Hooks run in a separate process and can be written in any language. They receive JSON via stdin and can exit with status codes to control flow.

Building an Observable System

Let's build a complete logging system that captures every action your agent takes:

Comprehensive Logging Setup

The Logging Hook

Universal Logging Hook

Configuring Multiple Hooks

Claude Settings Configuration

Adding Voice Feedback

One of the most powerful patterns is adding natural language feedback to your agents:

Text-to-Speech Notification Hook

Real-World Impact: With voice notifications, you can run long-running async jobs and be notified when they complete, without constantly checking your terminal.

Advanced Patterns

Pattern 1: Security Filtering

Multi-Layer Security

Pattern 2: Smart Summarization

Using small, fast models to summarize actions:

AI-Powered Summaries

Pattern 3: Conditional Tool Access

Time-Based Permissions

Building a Complete Observability Dashboard

With hooks sending events, you can build a real-time dashboard:

Simple Event Server

Best Practices

1. Keep Hooks Fast

Hooks run synchronously and can slow down your agent. Keep them under 100ms.

2. Fail Gracefully

Don't let logging failures break your workflow:

3. Use Status Codes Wisely

  • Exit 0: Allow continuation
  • Exit 1: Block the action
  • Exit 2+: Custom handling

4. Layer Your Hooks

Run multiple hooks for the same event—security first, then logging, then notifications.

5. Test Your Hooks

Testing Hooks Locally

Security Note: Always validate and sanitize data in your hooks. Remember that agents can generate arbitrary content.

The Future of Observable AI

Hooks are just the beginning. As we scale up multi-agent systems, observability becomes critical. You need to:

  1. Track Everything: Every decision, every action, every outcome
  2. Monitor in Real-Time: See what your agents are doing as they do it
  3. Control the Flow: Intervene when necessary, guide when helpful
  4. Learn from Patterns: Use logs to improve prompts and workflows

Taking Action

Start simple:

  1. Add a Basic Security Hook: Block rm -rf and other dangerous commands
  2. Set Up Simple Logging: Just save events to a file initially
  3. Add One Notification: Maybe just a sound when tasks complete
  4. Iterate and Improve: Add more sophisticated hooks as needed

Remember: Hooks give you deterministic control over non-deterministic systems. They're your safety net, your observability layer, and your automation enabler all in one.

The best part? This is all available today. No waiting for the next version. No complex setup. Just simple scripts that give you complete control over your AI agents.

Start with one hook. See the power. Then build your complete observability system.

Your agents are powerful. Now make them observable, controllable, and safe.

I taught before I built, and it still shapes how I explain this work. I build production agentic AI systems and write about what I learn doing it.

Keep going

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