performance-engineering

v0.2.3

Performance- and capacity-engineering team — agents (performance-architect, load-testing-engineer, profiling-and-capacity-engineer) for system performance and scalability: performance strategy and budgets, workload modeling, and SLO-linked NFR targets (performance-architect); load/stress/soak/spike testing with k6/Gatling/Locust/JMeter, open- vs closed-model workloads, ramping, think time, and test data (load-testing-engineer); profiling, flame graphs, USE/RED bottleneck triage, capacity and headroom via Little's law, and regression detection (profiling-and-capacity-engineer). Knowledge bank with decision trees, a Little's-law/percentiles capacity calculator, best-practices, skills, commands, templates, an advisory hook, scenarios. Distinct from frontend Core Web Vitals and observability-sre SLOs. Seams: web vitals -> frontend-engineering; SLO -> observability-sre; query tuning -> database-engineering; resilience -> backend-engineering. Requires ravenclaude-core@>=0.7.0.

Claude Code3 Skills

By Matt CorbettLicense: MIT7 GitHub starsUpdated last week

Directory evidence

Runtimes: Claude Code
Parsed components: 3 skill or MCP entries
Source updated: Sep 15, 2026
Manifest status: Canonical path parsed

The directory validates manifest shape and source location. It does not execute the plugin or provide a security endorsement. Review the indexing methodology →

Install performance-engineering for Claude Code

Installs for the current user

claude plugin marketplace add IchenDEV/agent-plugin-mkt
claude plugin marketplace update agent-plugin-marketplace
claude plugin install performance-engineering-2@agent-plugin-marketplace

Paste and run these commands in a terminal with Claude Code. They add and refresh the PluginsMP catalog, then install this plugin.

The installer fetches third-party code from the source repository shown on this page. This directory validates manifest structure and source location, but does not perform a security audit; review the manifest, components, and source before installing.

Get the source manually

$ git clone https://github.com/mcorbett51090/RavenClaude

Clone the source repository, then follow its setup instructions to add the plugin to a compatible client. The plugin root is plugins/performance-engineering/.

Plugin files

plugins/performance-engineering/

├── .claude-plugin/plugin.json
├── skills/load-test-design/SKILL.md
├── skills/performance-test-strategy/SKILL.md
└── skills/profiling-and-bottleneck-triage/SKILL.md

Included Skills3

load-test-designskills/load-test-design/SKILL.md

Design the load/stress/soak/spike test from a modeled workload: pick the open- vs closed-model executor deliberately, design ramping and think time, generate realistic owned test data, avoid coordinated omission, and assert thresholds in-script — tool-neutral across k6/Gatling/Locust/JMeter.

performance-test-strategyskills/performance-test-strategy/SKILL.md

Set the performance strategy before testing: turn vague goals into falsifiable NFRs (percentile + threshold + load), model the real workload, link targets to the customer SLO, and choose the test type (load/stress/soak/spike) that answers the open question.

profiling-and-bottleneck-triageskills/profiling-and-bottleneck-triage/SKILL.md

Localize the bottleneck and size the system: CPU/memory/IO profiling and flame graphs, USE/RED triage to name the constraining resource, capacity planning with headroom via Little's law and the measured saturation point, and regression detection against a committed baseline.

Plugin manifests1

plugins/performance-engineering/.claude-plugin/plugin.json

{
  "name": "performance-engineering",
  "version": "0.2.3",
  "description": "Performance- and capacity-engineering team — agents (performance-architect, load-testing-engineer, profiling-and-capacity-engineer) for system performance and scalability: performance strategy and budgets, workload modeling, and SLO-linked NFR targets (performance-architect); load/stress/soak/spike testing with k6/Gatling/Locust/JMeter, open- vs closed-model workloads, ramping, think time, and test data (load-testing-engineer); profiling, flame graphs, USE/RED bottleneck triage, capacity and headroom via Little's law, and regression detection (profiling-and-capacity-engineer). Knowledge bank with decision trees, a Little's-law/percentiles capacity calculator, best-practices, skills, commands, templates, an advisory hook, scenarios. Distinct from frontend Core Web Vitals and observability-sre SLOs. Seams: web vitals -> frontend-engineering; SLO -> observability-sre; query tuning -> database-engineering; resilience -> backend-engineering. Requires ravenclaude-core@>=0.7.0.",
  "author": {
    "name": "Matt Corbett"
  },
  "homepage": "https://github.com/mcorbett51090/RavenClaude",
  "license": "MIT",
  "keywords": [
    "performance-engineering",
    "load-testing",
    "k6",
    "gatling",
    "profiling",
    "flame-graph",
    "capacity-planning",
    "bottleneck",
    "soak-test",
    "throughput",
    "latency",
    "scalability"
  ],
  "requires": {
    "plugins": [
      "ravenclaude-core@>=0.7.0"
    ]
  }
}

For maintainers

If you maintain this plugin, link to this source-backed listing from your README so users can review its manifest and indexed components.

[performance-engineering on Agent Plugins Marketplace](https://pluginsmp.com/plugins/performance-engineering-2)