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Performance Testing Review Multi Agent Review

Checked
rmyndharis·vlatest·agents·MIT

Helps with performance optimization, testing, code review as part of orchestrating AI agents and multi-step workflows 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 rmyndharis/antigravity-skills --skill performance-testing-review-multi-agent-review -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

rmyndharis

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 rmyndharis/antigravity-skills at 3eff4af253.

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

Commit
3eff4af253
Manifest
skills/performance-testing-review-multi-agent-review/SKILL.md
Scanned
1 file, 196 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 facilitates multi-agent review of performance testing results. It allows for the automated analysis and critique of performance test data, identifying areas of concern and suggesting improvements. The skill leverages multiple AI agents to provide a more comprehensive and nuanced assessment than a single agent could achieve.

When to use it

  • Performance Test Report Review: Automatically analyze and summarize reports from load testing tools like JMeter or Gatling.
  • Identifying Bottlenecks: Pinpoint potential performance bottlenecks in applications based on test data analysis.
  • Code Optimization Suggestions: Receive recommendations for code changes to improve application performance.
  • Regression Testing Analysis: Evaluate the impact of new code deployments on existing performance metrics.

Key capabilities

  • Multi-agent review process
  • Performance test report parsing and summarization
  • Bottleneck identification
  • Code optimization suggestions

Example prompts

  • "Review this JMeter results file and identify any areas of concern."
  • "Analyze the attached Gatling performance test data and suggest code improvements for faster response times."
  • "Compare these two sets of performance test results and highlight any regressions."

Tips & gotchas

The skill's effectiveness depends on the quality and format of the input performance testing reports. Ensure your reports are well-structured and contain relevant metrics for optimal analysis.