Skip to content
TrustedSkillsbeta
Back to all skills

V3 Performance Optimization

Checked
proffesor-for-testing·vlatest·testing·MIT

Helps with testing, performance optimization, optimization 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.

Installs under a different name. Its SKILL.md names it V3 Performance Optimization, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add proffesor-for-testing/agentic-qe --skill "V3 Performance Optimization" -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

proffesor-for-testing

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 proffesor-for-testing/agentic-qe at 124d8c735e.

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

Commit
124d8c735e
Manifest
.claude/skills/v3-performance-optimization/SKILL.md
Scanned
1 file, 362 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 analyze application performance metrics and identify bottlenecks within codebases. It assists in generating optimized solutions to improve execution speed and resource efficiency during the testing phase.

When to use it

  • Evaluating slow-running test suites to pinpoint specific failing or timing-out cases.
  • Analyzing server-side response times to suggest architectural improvements for backend services.
  • Reviewing database query logs to identify inefficient SQL statements causing latency.
  • Generating refactored code snippets aimed at reducing memory usage or CPU load.

Key capabilities

  • Performance metric analysis and bottleneck identification.
  • Code optimization suggestions for speed and efficiency.
  • Generation of optimized test cases based on performance constraints.
  • Identification of resource leaks in application logic.

Example prompts

  • "Analyze this test suite execution log and identify the three slowest functions causing delays."
  • "Suggest code refactoring strategies to reduce the memory footprint of this high-load API endpoint."
  • "Generate a set of performance regression tests to verify that recent changes did not degrade response times."

Tips & gotchas

Ensure you provide relevant context such as execution logs, error traces, or specific performance thresholds for accurate analysis. This skill focuses on optimization logic rather than executing live performance benchmarks directly.