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Python Observability Patterns

Checked
neversight·vlatest·backend

Helps with Python, patterns as part of developing backend services and APIs workflows.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add neversight/learn-skills.dev --skill python-observability-patterns -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

neversight

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Install target

Live repository

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No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

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  • Pinned to a commit: passed

    Scanned neversight/skills_feed at 58220bbac4.

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Commit
58220bbac4
Manifest
data/skills-md/0xdarkmatter/claude-mods/python-observability-patterns/SKILL.md
Scanned
13 files, 184 lines
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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.