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Python Test Micrometer Testing Metrics

Checked
dawiddutoit·vlatest·backend

Helps with Python, testing 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 dawiddutoit/custom-claude --skill python-test-micrometer-testing-metrics -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

dawiddutoit

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

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

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

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    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned dawiddutoit/custom-claude at 17b45a90a6.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
17b45a90a6
Manifest
skills/python-test-micrometer-testing-metrics/SKILL.md
Scanned
1 file, 647 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
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About this skill

What it does

This skill enables AI agents to write and execute tests for Python applications using Micrometer, a metrics collection library. It allows the agent to verify that application metrics are being recorded correctly and consistently. The skill facilitates automated testing of metric reporting logic and ensures data integrity within monitoring systems.

When to use it

  • Automated Metric Validation: When you need to automatically ensure your Python application is properly emitting metrics to a Micrometer registry.
  • Continuous Integration/Continuous Delivery (CI/CD): Integrate this skill into CI/CD pipelines to validate metric reporting changes before deployment.
  • Regression Testing: When refactoring code that impacts metric generation, use this skill to confirm existing metrics remain accurate.
  • New Feature Development: When introducing new features that generate custom metrics, automatically test their correctness and consistency.

Key capabilities

  • Writes Micrometer tests for Python applications.
  • Executes generated tests.
  • Validates metric recording logic.
  • Ensures data integrity within monitoring systems.

Example prompts

  • "Write a unit test to verify the request_latency metric is recorded correctly."
  • "Generate a test suite for all custom Micrometer metrics in my application."
  • "Run the existing tests and report any failures related to metric reporting."

Tips & gotchas

  • Requires familiarity with Micrometer and Python testing frameworks.
  • The agent's effectiveness depends on clear and concise descriptions of expected metric behavior.