Python Observability
wshobson/agentsWhen your Python application runs in production, you need to see what is happening inside it. This skill teaches you how to add structured logging, metrics, and distributed tracing. You can then answer what broke, where it broke, and why without changing your code.
Structured logging means printing log entries as JSON with consistent fields. This makes log data easy to search and analyze. You will also learn to track the four golden signals such as latency, traffic, errors, and saturation. Correlation IDs thread through all logs and traces so you can follow a single request across services.
Use these patterns to build observability into your Python apps. You will debug production issues faster and keep your systems running smoothly.
Add Python Observability skill to your workflow
Global
mkdir -p ~/.claude/skills/python-observabilityProject
mkdir -p .claude/skills/python-observabilitySource Repository
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