castai-local-dev-loop
Set up a local Kubernetes development loop with CAST AI cost monitoring. Use when building cost-aware deployments, testing autoscaler policies, or iterating on Terraform CAST AI configurations locally. Trigger with phrases like "cast ai dev setup", "cast ai local testing", "develop with cast ai", "cast ai terraform dev". '
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill castai-local-dev-loop --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.
# CAST AI Local Dev Loop ## Overview Fast iteration workflow for CAST AI integrations: test autoscaler policies in a dev cluster, validate Terraform modules before applying to production, and use the CAST AI API to measure savings impact during development. ## Prerequisites - Completed `castai-install-auth` setup - A development Kubernetes cluster (kind, minikube, or cloud dev cluster) - `kubectl`
What does the castai-local-dev-loop skill do?
Set up a local Kubernetes development loop with CAST AI cost monitoring. Use when building cost-aware deployments, testing autoscaler policies, or iterating on Terraform CAST AI configurations locally. Trigger with phrases like "cast ai dev setup", "cast ai local testing", "develop with cast ai", "cast ai terraform dev". '
How do I install it?
Run `npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill castai-local-dev-loop --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.