Skip to content
TrustedSkillsbeta
Back to all skills

Pytest Optimizer

Checked
jorgealves·vlatest·testing·GPL-3.0

This Pytest Optimizer analyzes your tests & suggests improvements for faster execution and better code coverage – boosting efficiency!

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 jorgealves/agent_skills --skill pytest-optimizer -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

jorgealves

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

    No pipe-to-shell or download-and-run installers.

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

  • Pinned to a commit: passed

    Scanned jorgealves/agent_skills at 85014ad37d.

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

Commit
85014ad37d
Manifest
pytest-optimizer/SKILL.md
Scanned
2 files, 50 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.
What each check looks for →

About this skill

What it does

The Pytest Optimizer analyzes existing pytest test suites to identify opportunities for improvement. It aims to enhance speed, pinpoint flaky tests, and increase code coverage within Python projects. By providing actionable suggestions, this skill helps maintain high-quality and fast-running test pipelines.

When to use it

  • Project Setup: When starting a new Python project and establishing testing practices from the beginning.
  • Continuous Integration: As part of automated build and test pipelines to ensure consistent performance.
  • Legacy Refactoring: During updates to older Python codebases, helping modernize testing approaches.

Key capabilities

  • Analyzes pytest suites for optimization opportunities.
  • Identifies flaky tests.
  • Suggests improvements to increase code coverage.
  • Performs all analysis locally without transmitting source code externally.

Example prompts

  • "Analyze my pytest suite and suggest ways to improve its speed."
  • "Find any flaky tests in my project's test pipeline."
  • "How can I increase the code coverage of my pytest tests?"

Tips & gotchas

  • The skill is specifically designed for Python projects.
  • It requires a requirements.txt or pyproject.toml file to function correctly.
  • Ensure your project uses a supported version of Python, as incompatible versions may cause issues.