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Performance Engineer

Checked
rmyndharis·vlatest·testing·MIT

Optimizes system performance through automated analysis, bottleneck identification, and tailored configuration recommendations.

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-engineer -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-engineer/SKILL.md
Scanned
1 file, 181 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 an AI agent to act as a performance engineer specializing in modern application optimization and scalable system performance. It can diagnose bottlenecks, design load tests and capacity plans, set up observability, and optimize latency, throughput, and resource efficiency. The agent leverages expertise in observability, profiling, and testing methodologies to improve overall system performance.

When to use it

  • Diagnosing performance issues within backend systems, frontend applications, or infrastructure components.
  • Designing load tests, capacity plans, or strategies for scaling your application.
  • Setting up observability and performance monitoring solutions.
  • Optimizing latency, throughput, or resource utilization of a system.

Key capabilities

  • Modern Observability & Monitoring: Expertise with OpenTelemetry, APM platforms (DataDog, New Relic, Dynatrace, AppDynamics, Honeycomb, Jaeger), Prometheus, Grafana, InfluxDB, Real User Monitoring (RUM), Synthetic monitoring and log correlation.
  • Advanced Application Profiling: Proficiency in CPU profiling (flame graphs), memory profiling (heap analysis), I/O profiling, and language-specific profiling (JVM, Python, Node.js, Go). Includes container and cloud profiling capabilities (Docker, Kubernetes, AWS X-Ray, Azure Application Insights, GCP Cloud Profiler).
  • Modern Load Testing & Performance Validation: Experience with load testing tools like k6, JMeter, Gatling, Locust, Artillery, API testing, browser testing (Puppeteer, Playwright), chaos engineering and performance budgets.

Example prompts

  • "Analyze the CPU usage of our backend service and identify potential bottlenecks."
  • "Design a load test to evaluate the scalability of our new API endpoint."
  • "Recommend observability tools for monitoring our frontend application's Core Web Vitals."
  • “How can we optimize database query performance in our Python application?”

Tips & gotchas

  • Requires access to metrics, traces, and profiling data. Without this information, the skill cannot effectively diagnose issues.
  • Avoid load testing production environments without proper approvals and safeguards. Staged rollouts with rollback plans are recommended for high-risk changes.
  • The agent is not intended for feature development tasks that do not have performance goals.