Performance Engineer
Optimizes system performance through automated analysis, bottleneck identification, and tailored configuration recommendations.
Install on your platform
We auto-selected Claude Code based on this skill’s supported platforms.
Run in terminal (recommended)
claude mcp add rmyndharis-performance-engineer npx -- -y @trustedskills/rmyndharis-performance-engineer
Or manually add to ~/.claude/settings.json
{
"mcpServers": {
"rmyndharis-performance-engineer": {
"command": "npx",
"args": [
"-y",
"@trustedskills/rmyndharis-performance-engineer"
]
}
}
}Requires Claude Code (claude CLI). Run claude --version to verify your install.
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.
Tags
TrustedSkills Verification
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Security Audits
| Gen Agent Trust Hub | Pass |
| Socket | Pass |
| Snyk | Pass |
🌐 Community
Passed automated security scans.