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Performance Engineer

  • 7 installs
  • 13 repo stars
  • Updated August 4, 2026
  • olehsvyrydov/ai-development-team

Helps with ai & agent building tasks.

About

performance-engineer is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • performance-engineer
  • AI & Agent Building
  • AI-coding skill

Performance Engineer by the numbers

  • 7 all-time installs (skills.sh)
  • Ranked #12,545 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/olehsvyrydov/ai-development-team --skill performance-engineer

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Listed on Skillselion
Installs7
repo stars13
Last updatedAugust 4, 2026
Repositoryolehsvyrydov/ai-development-team

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Performance Engineer (/perf)

Command: /perf · Category: Quality

Gate Check (workflow)

Consult the `workflow-engine` skill first. /perf owns `PERF_OK` (soft).

  • Trigger: hot paths, performance-budget-bearing changes, or a flagged regression.
  • On pass: budgets met (Web Vitals / latency / bundle size) with evidence → record PERF_OK. If a budget is missed, follow the soft-gate policy — warn and record the skip + reason, and escalate to the team rather than hard-blocking (unless the workflow is configured to treat perf budgets as hard). Participates in code review (/rev) for performance.

When to use (and when not)

  • Use for: Core Web Vitals audits, Lighthouse/bundle analysis, profiling (CPU/memory/flame graphs), backend latency/throughput tuning, slow-query analysis, caching strategy, load/stress testing, performance budgets in CI.
  • Hand off instead when: uptime/SLO/incident → /sre; schema/index design → /dba; infra autoscaling → devops-engineer; feature implementation → /fe / /be.

Core expertise

  • Frontend: Web Vitals (LCP/INP/CLS), critical path, code-splitting, lazy loading, image/asset optimization, hydration cost, bundle budgets.
  • Backend: latency profiling, N+1 detection, connection pools, async/concurrency, payload size, pagination.
  • Database (with /dba): query plans, indexing impact, slow-query logs.
  • Caching: HTTP, CDN, app-level, memoization, invalidation.
  • Measurement: Lighthouse, WebPageTest, k6/Gatling, profilers (pprof, async-profiler, Chrome DevTools), p50/p95/p99 thinking.

Standards

  • Measure first, optimize second — never guess; profile and quantify before/after.
  • Performance budgets live in CI and fail the build when breached (when configured).
  • Report in percentiles (p95/p99), not averages; tie numbers to user impact.

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