performance-engineering

performance-engineering is a skill for Claude Code from ancoleman/ai-design-components. It costs 72 tokens per session (2,846 once invoked), scanned B, original, MIT.

A guide to testing and improving how quickly and reliably software works under expected or heavy use. It covers load tests, performance profiling, and improvements to backends, databases, and web pages.

In plain words
What is it for?
Use it to test traffic limits, investigate slow responses, plan capacity, compare performance after code changes, improve Core Web Vitals, and reduce infrastructure costs.
Why use it?
It helps find slow parts, capacity limits, memory leaks, and performance regressions before they affect users.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the data-engineering-skills plugin — 6 skills shipped together

Good fit Use it to test traffic limits, investigate slow responses, plan capacity, compare performance after code changes, improve Core Web Vitals, and reduce infrastructure costs.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ancoleman/ai-design-components/performance-engineering
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ancoleman/ai-design-components --skill performance-engineering
Clone the repo
git clone --depth 1 https://github.com/ancoleman/ai-design-components

Made for: Claude Code.

Or install data-engineering-skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for performance-engineering

README.md
[![agentmods](https://agentmods.dev/badge/skills/ancoleman/ai-design-components/performance-engineering/github.svg)](https://agentmods.dev/skills/ancoleman/ai-design-components/performance-engineering)
Your own site
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/performance-engineering"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/performance-engineering/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for performance-engineering

Your own site · 80×15
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/performance-engineering"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/performance-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 72 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,846 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 2 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00072 $0.02846
Opus 5.5 $0.00029 $0.01138
Sonnet 5.5 $0.00014 $0.00569
Haiku 4.5 $0.00007 $0.00285

Measured 1mo ago against content hash a396452603cb, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade B, and why

performance-engineering scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

The scan reads SKILL.md. This mod also ships 6 executable files (examples/k6/load-test.js, examples/k6/soak-test.js, examples/k6/stress-test.js, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Asks for rootmediumPrivilege escalation

A mod that escalates privileges can change anything on the machine, not only the project.

sudo apt-get install k6 # Linux

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

curl https://github.com/grafana/k6/releases/download/v0.48.0/k6-v0.48.0-linux-amd64.tar.gz -L | tar xvz
skills/performance-engineering/SKILL.md · 430 lines

How it starts

The opening of the file, as written. The whole thing — 430 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Performance Engineering

Purpose

Performance engineering encompasses load testing, profiling, and optimization to deliver reliable, scalable systems. This skill provides frameworks for choosing the right performance testing approach (load, stress, soak, spike), profiling techniques to identify bottlenecks (CPU, memory, I/O), and optimization strategies for backend APIs, databases, and frontend applications.

Use this skill to validate system capacity before launch, detect performance regressions in CI/CD pipelines, identify and resolve bottlenecks through profiling, and optimize application responsiveness across the stack.

When to Use This Skill

Common Triggers:

  • "Validate API can handle expected traffic"
  • "Find maximum capacity and breaking points"
  • "Identify why the application is slow"
  • "Detect memory leaks or resource exhaustion"
  • "Optimize Core Web Vitals for SEO"
  • "Set up performance testing in CI/CD"
  • "Reduce cloud infrastructure costs"

Use Cases:

  • Pre-launch capacity planning and load validation
  • Post-refactor performance regression testing
  • Investigating slow response times or high latency
  • Detecting memory leaks in long-running services
  • Optimizing database query performance
  • Validating auto-scaling configuration
  • Establishing performance SLOs and budgets

Performance Testing Types

Load Testing

Validate system behavior under expected traffic levels.

When to use: Pre-launch capacity planning, regression testing after refactors, validating auto-scaling.

Stress Testing

Find system capacity limits and failure modes.

When to use: Capacity planning, understanding failure behavior, infrastructure sizing decisions.

Soak Testing

Identify memory leaks, resource exhaustion, and degradation over time.

When to use: Detecting memory leaks, validating connection pool cleanup, testing long-running batch jobs.

Spike Testing

Validate system response to sudden traffic spikes.

When to use: Validating auto-scaling, testing event-driven systems (product launches), ensuring rate limiting works.

Read the full file on GitHub · 430 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 430 lines · 72 tokens per session scan B a396452603cb

Subscribe to this mod's changes

performance-engineering is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 72 tokens to every session and 2,846 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it B with 2 findings (asks for root, makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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