Python Observability Patterns
Helps with Python, patterns as part of developing backend services and APIs workflows.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add neversight-python-observability-patterns npx -- -y @trustedskills/neversight-python-observability-patterns
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"neversight-python-observability-patterns": {
"command": "npx",
"args": [
"-y",
"@trustedskills/neversight-python-observability-patterns"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
About This Skill
What it does
This skill provides Python code snippets and best practices for implementing observability patterns in backend systems. It helps developers instrument their applications to collect metrics, logs, and traces, enabling better monitoring and troubleshooting. The skill focuses on practical examples of common observability techniques.
When to use it
- You need help adding logging to a Python application.
- You want to implement Prometheus-compatible metrics collection in your backend service.
- You're struggling to understand how to structure traces for distributed systems.
- You are looking for examples of using OpenTelemetry with Python.
Key capabilities
- Prometheus metrics generation
- Structured logging
- OpenTelemetry integration
- Distributed tracing implementation
Example prompts
- "Show me an example of how to log a request in Python."
- "Generate Prometheus metrics for my Flask API endpoint."
- "How can I implement distributed tracing using OpenTelemetry in Python?"
- “Give me an example of structured logging with severity levels.”
Tips & gotchas
This skill assumes basic familiarity with Python and backend development concepts. While it provides code snippets, understanding the underlying observability principles is crucial for effective application.
Tags
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
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