adobe-load-scale
Implement load testing, auto-scaling, and capacity planning for Adobe API integrations with k6 scripts targeting Firefly, PDF Services, and Photoshop APIs, plus Kubernetes HPA configuration. Trigger with phrases like "adobe load test", "adobe scale", "adobe performance test", "adobe capacity", "adobe benchmark". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill adobe-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.
# Adobe Load & Scale ## Overview Load testing and scaling strategies for Adobe API integrations. Adobe APIs are async and relatively slow (5-30s per operation), requiring different load testing approaches than typical REST APIs. ## Prerequisites - k6 load testing tool installed (`npm install -g k6` or `brew install k6`) - Adobe Developer Console credentials for testing (separate from production) -
What does the adobe-load-scale skill do?
Implement load testing, auto-scaling, and capacity planning for Adobe API integrations with k6 scripts targeting Firefly, PDF Services, and Photoshop APIs, plus Kubernetes HPA configuration. Trigger with phrases like "adobe load test", "adobe scale", "adobe performance test", "adobe capacity", "adobe benchmark". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill adobe-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.
