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Performance Testing

Checked
aj-geddes·vlatest·testing·MIT

Helps with performance optimization, testing as part of testing, debugging, and quality assurance 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 aj-geddes/useful-ai-prompts --skill performance-testing -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

aj-geddes

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 aj-geddes/useful-ai-prompts at 3f5182cfd7.

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

Commit
3f5182cfd7
Manifest
skills/performance-testing/SKILL.md
Scanned
9 files, 601 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

This skill enables AI agents to perform performance testing, which involves measuring how systems behave under various load conditions. It helps identify bottlenecks, validate performance requirements (like response times and throughput), and ensure systems can handle expected user loads. The skill supports multiple tools including k6, Apache JMeter, pytest-benchmark, and JMH for Java benchmarking.

When to use it

  • Validating response time requirements
  • Measuring API throughput and latency
  • Testing database query performance
  • Identifying performance bottlenecks
  • Benchmarking before/after optimizations

Key capabilities

  • Performance testing of APIs using tools like k6.
  • Database query performance testing.
  • Algorithm efficiency comparison.
  • Caching effectiveness validation.
  • Concurrent user capacity testing.
  • Support for various benchmarking tools (k6, JMeter, pytest-benchmark, JMH).

Example prompts

  • "Run a load test on the /api/orders endpoint using k6."
  • "Benchmark this Python function and identify any performance bottlenecks."
  • "Test the database query SELECT * FROM users to measure its execution time."

Tips & gotchas

  • Define clear performance requirements (SLAs) before testing.
  • Use realistic data volumes during testing for accurate results.
  • Warm up systems before measuring performance metrics.