Agent skill · software engineering · jeremylongshore
castai-core-workflow-b
Enable CAST AI optimization through a measured canary with explicit node and workload policy boundaries. Use when observation-first onboarding is complete and Node Autoscaling, Workload Autoscaling, or managed HPA behavior can be activated. Trigger with: "enable CAST AI automation", "canary CAST AI autoscaling", "apply CAST AI optimization policies".
Why this skill is useful
Provides specific commands and configurations for optimizing Kubernetes workloads with CAST AI that the AI wouldn't reliably generate on its own.
What it needs
Requires helm, jq installed locally. Requires castai account access. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
CAST AI Controlled Optimization Rollout Overview Turn recommendations into automation one bounded control at a time. Separate node capacity, vertical workload rightsizing, and horizontal replica control so each has an observable success condition and rollback. Prerequisites A healthy connected cluster and representative cost/workload baseline Current scaling policies, node templates, PDBs, HPAs, quotas, and protected namespaces A low-risk canary workload with an accountable owner Instructions Step 1: Define the control matrix Use Read and Grep to map Node Autoscaling, Workload Autoscaler vertical mode, horizontal autoscaling, existing HPAs, and external provisioners. Record one owner for each control. Do not transfer HPA ownership implicitly. Step 2: Set guardrails Use Write or Edit to define approved node templates, availability zones, instance lifecycle constraints, maximum CPU, workload minimums/maximums, policy assignment, PDB expectations, and rollback thresholds. Do not add the deprecated cluster minimum CPU setting. Step 3: Preview the change Use Bash(terraform:) to produce a saved reviewed plan when Terraform owns the configuration. Use Bash(castctl:) only for supported inspection or documented feature operations. Confirm the diff affects the intended cluster and canary only. Step 4: Enable a workload canary Choose Immediate mode only when controlled pod replacement is acceptable; the Eviction API will enforce PDBs. Choose Deferred mode when recommendations should apply on natural recreation. If horizontal autoscaling is enabled, review the native autoscaling/v2 HPA configuration and any take-ownership decision. Step 5: Observe capacity and workload outcomes Use Bash(kubectl:\) to inspect pending pods, scheduling events, HPA state, pod replacements, PDBs, requests, and node changes. Compare availability, latency, saturation, and spend to the pre-change baseline; do not optimize on cost alone. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/castai-core-workflow-b