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observability

Log agent actions and execution lifecycles to Kafka and PostgreSQL.

3|1|Updated Oct 9, 2025
Search Tags:#postgresql#logging#observability#tracing#kafka#agent tracking
One-click install
npx skills add https://github.com/OmniNode-ai/omniclaude --skill observability-omninode-ai
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: observability
Source: https://github.com/OmniNode-ai/omniclaude/tree/main/plugins/onex/skills/observability
Command: npx skills add https://github.com/OmniNode-ai/omniclaude --skill observability-omninode-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides a centralized system for monitoring and understanding agent behavior, including actions, routing decisions, execution status, and end-to-end tracing.

Core Features & Use Cases

  • Action Logging: Records all agent actions (tool calls, decisions, errors, successes) to Kafka for real-time analysis.
  • Execution Tracking: Logs the lifecycle of agent tasks, from start to completion, in PostgreSQL for performance monitoring.
  • Trace Correlation: Enables end-to-end debugging by linking events across different systems using correlation IDs.
  • Use Case: Debug a complex agent workflow by tracing a specific request through its entire journey, identifying bottlenecks or errors at each step.

Quick Start

Use the observability skill to start tracking an agent execution for researching Claude Code skills.

Frequently Asked Questions about observability

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I trace agent actions and execution across Kafka and PostgreSQL?▼

You trace agent actions and execution by logging tool calls and decisions to Kafka topics like agent-actions, while storing execution lifecycles and routing data in PostgreSQL tables for persistent observability and debugging.

What is unified observability for AI agent workflows?▼

Unified observability for AI agents is the centralized monitoring of routing, execution, and tracing, recording tool calls, decisions, and performance metrics to provide end-to-end debugging across distributed systems.

Can I debug agent bottlenecks using correlation IDs across distributed systems?▼

Yes, you can debug agent bottlenecks by using correlation IDs to link events across different systems, enabling end-to-end tracing of a specific request through its entire journey to identify errors or delays.

How do I log agent tool calls and decisions for performance monitoring?▼

You log agent tool calls and decisions by recording actions, successes, and errors to Kafka for real-time analysis, and logging the task lifecycle from start to completion in PostgreSQL for performance monitoring.

Does this agent tracking approach require both Kafka and PostgreSQL?▼

Yes, this agent tracking approach uses Kafka for real-time action logging and analysis, while using PostgreSQL for persistent storage of execution and routing data to support comprehensive observability.

What is the best way to monitor an agent execution lifecycle from start to finish?▼

The best way to monitor an agent execution lifecycle is tracking the task from start to completion in PostgreSQL, combining it with Kafka action logs to capture routing decisions, tool calls, and performance metrics.

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