Competition K8s Control Plane
SkillCloud & infraInternal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Kubernetes API analysis, service-account trust, RBAC edges, admission and controller behavior, cluster secrets, workload mutation, and namespace-scoped drift. Use when the user asks to inspect kube API permissions, service-account tokens, RoleBinding or ClusterRoleBinding edges, admission webhooks, controller-created pods, secret exposure, or why live workloads differ from manifests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
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Details
Instructions available. Your AI can read the instructions. Execution depends on the setup they require.
Account requirements not reviewed. Check the skill instructions before use; Ahel provides instructions and does not run this skill.
No other account needed.
Add Ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
What this skill tells your AI
The instructions your AI receives, as published by alicewe1/alice_skill in _modules/competition-k8s-control-plane/SKILL.md and read by Ahel’s review.
Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.
Use this skill when the decisive path runs through Kubernetes control-plane state, API permissions, or controller behavior rather than a single container's runtime alone.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Separate manifest intent from live cluster state: API objects, mutations, controllers, secrets, and resulting workloads.
- Identify the active principal first: service account, kubeconfig identity, node credential, webhook, or controller.
- Map the smallest control-plane edge to its workload effect.
- Keep RBAC, service accounts, owner references, namespace boundaries, and secret consumers in compact evidence blocks.
- Reproduce the smallest cluster action that yields the decisive workload or secret effect.
Workflow
1. Map The API Trust Path
- Record namespaces, service accounts, Roles, ClusterRoles, bindings, admission hooks, controllers, and the resources they can mutate.
- Distinguish read access, create access, patch access, exec access, and secret access.
- Keep principal, verb, resource, namespace, and resulting object in one chain.
2. Trace Mutation To Workload State
- Show how an API action becomes a pod, volume mount, secret exposure, env injection, job run, or controller-created artifact.
- Compare checked-in YAML against live objects after defaulting, admission mutation, or controller reconciliation.
- Distinguish pod-runtime behavior from cluster-level mutation logic.
3. Reduce To The Decisive Cluster Path
- Compress the result to the smallest chain: principal -> API permission -> mutated object -> resulting workload, secret, or route effect.
- Keep kube objects, live describes, and consumed secret or config paths tied to the same namespace and controller.
- If the problem narrows down to one container's mount or runtime deviation, switch back to the tighter container-runtime skill.
Read This Reference
- Load
references/k8s-control-plane.mdfor the RBAC checklist, controller checklist, and evidence packaging. - If the hard part is metadata-service reachability, workload identity, instance credentials, or metadata-derived privilege, prefer
$competition-cloud-metadata-path.
What To Preserve
- Namespace, service account, verb, resource kind, RoleBinding or ClusterRoleBinding, and owner reference chains
- Admission mutations, generated workloads, mounted secrets, and controller-produced drift
- The exact API action or object diff that creates the decisive effect
Signals
- GitHub stars
- 36
- Forks
- 6
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
competition-k8s-control-plane- Source
- github.com/alicewe1/alice_skill
github.com/alicewe1/alice_skill
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