vercel-load-scale
Load test and scale Vercel deployments with concurrency tuning and capacity planning. Use when running performance tests, planning for traffic spikes, or optimizing serverless function scaling on Vercel. Trigger with phrases like "vercel load test", "vercel scale", "vercel performance test", "vercel capacity", "vercel benchmark". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vercel-load-scale --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Vercel Load & Scale ## Overview Load test Vercel deployments to identify scaling limits, cold start impact, and concurrency thresholds. Covers k6/autocannon test scripts, Vercel's auto-scaling model, Fluid Compute concurrency, and capacity planning. ## Prerequisites - Load testing tool: k6, autocannon, or artillery - Test environment deployment (never load test production without approval) - Acc
What does the vercel-load-scale skill do?
Load test and scale Vercel deployments with concurrency tuning and capacity planning. Use when running performance tests, planning for traffic spikes, or optimizing serverless function scaling on Vercel. Trigger with phrases like "vercel load test", "vercel scale", "vercel performance test", "vercel capacity", "vercel benchmark". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill vercel-load-scale --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From jeremylongshore/claude-code-plugins-plus-skills, a repository with 2,596 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.
