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Get Started Free →Deploy CAST AI across multi-cloud Kubernetes clusters with Terraform modules. Use when onboarding EKS, GKE, or AKS clusters to CAST AI using infrastructure-as-code patterns. Trigger with phrases like "deploy cast ai", "cast ai eks", "cast ai gke", "cast ai aks", "cast ai terraform module".
.claude/skills/jeremylongshore-castai-deploy-integration/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-06 | ✗→✓ | ▲ Improved | -18% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 0% | 0% |
| case-16 | ✗→✓ | ▲ Improved | 1% | 0% |
| case-01 | ✗→✓ | ▲ Improved | -28% | 0% |
| case-02 | ✗→✓ | ▲ Improved | -18% | 0% |
Make the repository the declared source of truth for CAST AI installation and policy, then promote one cluster ring at a time. Keep registration, cloud permissions, chart configuration, and automation decisions independently reviewable.
Use Read and Grep to find CAST AI resources, individual component charts, the unified castai chart, Terraform state addresses, Flux or Argo CD objects, and console-only settings. Stop if two systems can reconcile the same resource.
Use Write or Edit to separate cluster registration, cloud IAM, Helm values, scaling policies, node templates, workload annotations, notification settings, and automation toggles. Parameterize organization, region, and cluster identity; never parameterize a secret with a committed literal.
Use Bash(helm:_) to lint and render the pinned chart. Use Bash(terraform:_) to format, validate, and save a plan. Use Bash(kubectl:\) for client-side manifest checks. Review RBAC, webhooks, CRDs, namespace, disruption behavior, deleted resources, and ownership transfers.
If the cluster uses individual CAST AI Helm releases, evaluate the documented castctl cluster migrate path to the unified umbrella chart. Use Bash(castctl:\) only after recording current releases, values, rollback, and the exact cluster context.
Apply through the declared delivery controller to one canary cluster. Verify agent health, telemetry, policy state, and automation boundaries before staging and production. Require an explicit approval between rings and preserve the reviewed artifact digest.
Document how to revert the Git commit or Terraform change, restore policy assignments, and detect console drift. A rollback must preserve cluster connectivity and workload availability; do not assume uninstalling is harmless.
Use Read and Grep for ownership discovery. Use Write and Edit for infrastructure definitions and runbooks. Use Bash(helm:_), Bash(terraform:_), and Bash(kubectl:_) for bounded render, plan, and verification. Use Bash(castctl:_) only for documented migration or connection actions inside an approved window.
A team migrates legacy per-component releases to the unified chart in one canary cluster, then lets Argo CD own the pinned result. Terraform continues to own cloud IAM but not Helm values.
| Failure | Response | | --------------------------------------------- | ------------------------------------------- | | Two reconcilers own one object | Stop promotion and choose one authority | | Plan deletes registration or IAM unexpectedly | Reject the plan and reconcile state | | Rendered output includes a key | Remove the secret from values and rotate it | | Canary loses telemetry | Roll back before promoting another cluster |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-21 | fail→fail | 9,457 | 8,716 | -8% | 1 | 1 | 0% | 1,624 | 2,715 | +67% | 0 | 0 | — |
case-22 | fail→fail | 10,321 | 8,151 | -21% | 1 | 1 | 0% | 1,846 | 2,469 | +34% | 0 | 0 | — |
case-06 | fail→pass | 11,876 | 4,422 | -63% | 1 | 1 | 0% | 2,271 | 1,851 | -18% | 0 | 0 | — |
case-15 | fail→pass | 14,908 | 8,459 | -43% | 1 | 1 | 0% | 2,442 | 2,445 | +0% | 0 | 0 | — |
case-16 | fail→pass | 9,428 | 2,335 | -75% | 1 | 1 | 0% | 1,342 | 1,360 | +1% | 0 | 0 | — |
case-01 | fail→pass | 26,890 | 11,297 | -58% | 1 | 1 | 0% | 4,972 | 3,595 | -28% | 0 | 0 | — |
case-02 | fail→pass | 14,088 | 5,749 | -59% | 1 | 1 | 0% | 2,820 | 2,315 | -18% | 0 | 0 | — |
case-03 | fail→pass | 18,411 | 10,580 | -43% | 1 | 1 | 0% | 3,632 | 3,495 | -4% | 0 | 0 | — |
case-04 | fail→pass | 5,046 | 3,098 | -39% | 1 | 1 | 0% | 865 | 1,586 | +83% | 0 | 0 | — |
case-05 | pass→pass | 6,549 | 3,414 | -48% | 1 | 1 | 0% | 1,162 | 1,640 | +41% | 0 | 0 | — |
case-07 | fail→pass | 7,934 | 3,264 | -59% | 1 | 1 | 0% | 1,473 | 1,634 | +11% | 0 | 0 | — |
case-08 | pass→pass | 17,095 | 5,514 | -68% | 1 | 1 | 0% | 3,172 | 2,253 | -29% | 0 | 0 | — |
case-09 | fail→pass | 7,496 | 3,032 | -60% | 1 | 1 | 0% | 1,340 | 1,585 | +18% | 0 | 0 | — |
case-10 | fail→pass | 10,029 | 2,307 | -77% | 1 | 1 | 0% | 1,694 | 1,383 | -18% | 0 | 0 | — |
case-11 | pass→pass | 13,154 | 14,256 | +8% | 1 | 1 | 0% | 2,572 | 4,373 | +70% | 0 | 0 | — |
case-12 | pass→pass | 7,390 | 3,103 | -58% | 1 | 1 | 0% | 1,201 | 1,540 | +28% | 0 | 0 | — |
case-13 | fail→pass | 12,721 | 4,450 | -65% | 1 | 1 | 0% | 2,165 | 1,938 | -10% | 0 | 0 | — |
case-14 | fail→pass | 9,816 | 2,592 | -74% | 1 | 1 | 0% | 1,717 | 1,511 | -12% | 0 | 0 | — |
case-17 | pass→pass | 7,292 | 2,019 | -72% | 1 | 1 | 0% | 1,204 | 1,380 | +15% | 0 | 0 | — |
case-18 | pass→pass | 7,607 | 3,282 | -57% | 1 | 1 | 0% | 1,456 | 1,697 | +17% | 0 | 0 | — |
case-19 | pass→pass | 10,115 | 4,239 | -58% | 1 | 1 | 0% | 1,752 | 1,856 | +6% | 0 | 0 | — |
case-20 | fail→fail | 15,890 | 13,556 | -15% | 1 | 1 | 0% | 2,670 | 3,685 | +38% | 0 | 0 | — |
case-23 | pass→pass | 13,210 | 3,036 | -77% | 1 | 1 | 0% | 2,054 | 1,603 | -22% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted. The headline lift of +52 percentage points is the difference between those two pass rates over the 23 comparable cases.
The publisher has shipped newer versions since this run, so these numbers describe v1, not the version currently listed.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.