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Performance Engineer

Listed
sickn33·vlatest·devops·MIT

Optimizes code and system configurations for peak efficiency and reduced resource consumption using data-driven analysis.

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 sickn33/agentic-awesome-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

sickn33

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 sickn33/antigravity-awesome-skills at 5a4cdd9df8.

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

Commit
5a4cdd9df8
Manifest
skills/performance-engineer/SKILL.md
Scanned
0 files
Copies in repo
3 — all of them scanned
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 optimizing modern applications and systems for peak efficiency. It leverages data-driven analysis, observability tools, and profiling techniques to diagnose bottlenecks, design scalability strategies, and improve overall system performance. The agent can analyze traces, profiles, and load tests to propose targeted optimizations with consideration of potential tradeoffs.

When to use it

  • Diagnosing performance issues in backend, frontend, or infrastructure components.
  • Designing load tests and capacity plans for scalable systems.
  • Setting up observability and performance monitoring solutions.
  • Optimizing latency, throughput, and resource efficiency.

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, language-specific profiling (JVM, Python, Node.js, Go), container profiling (Docker, Kubernetes), and cloud profiling (AWS X-Ray, Azure Application Insights, GCP Cloud Profiler).
  • Modern Load Testing & Performance Validation: Experience with load testing tools (k6, JMeter, Gatling, Locust, Artillery), API testing, browser testing (Puppeteer, Playwright, Selenium WebDriver), chaos engineering, and performance budgets.

Example prompts

  • "Analyze the recent slowdown in our checkout service and identify potential bottlenecks."
  • "Design a load test to evaluate the scalability of our new user registration endpoint."
  • "Recommend observability tools for monitoring our microservices architecture."
  • "Can you profile this Python code snippet and suggest optimizations for memory usage?"

Tips & gotchas

  • This skill requires access to metrics, traces, profiling data, or load test results. Without these inputs, it cannot effectively diagnose performance issues.
  • Avoid initiating load tests on production environments without proper approvals and safeguards in place.
  • Be mindful of potential tradeoffs when implementing optimizations; the agent will attempt to highlight these considerations.