Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add sethdford/claude-skills --skill container-orchestrationgit clone --depth 1 https://github.com/sethdford/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/sethdford/claude-skills/container-orchestration)<a href="https://agentmods.dev/skills/sethdford/claude-skills/container-orchestration"><img src="https://agentmods.dev/badge/skills/sethdford/claude-skills/container-orchestration/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sethdford/claude-skills/container-orchestration"><img src="https://agentmods.dev/badge/skills/sethdford/claude-skills/container-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00034 | $0.00670 |
| Opus 5 | $0.00017 | $0.00335 |
| Sonnet 5 | $0.00007 | $0.00134 |
| Haiku 4.5 | $0.00003 | $0.00067 |
Grade A, and why
container-orchestration scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Container Orchestration
Design and operate Kubernetes clusters for scalable, resilient container deployments.
Context
You are designing Kubernetes infrastructure. Plan cluster architecture, scaling policies, storage, networking, and operations. Read workload characteristics, scale requirements, and team Kubernetes maturity.
Domain Context
Based on Kubernetes best practices (CNCF, Google, AWS EKS):
- Clusters: Logical Kubernetes environment; runs multiple services. Multi-cluster for HA across regions or failure domains.
- Nodes: Worker machines (EC2 instances). Auto-scaling groups scale nodes based on demand.
- Pods: Smallest deployable unit; usually one container per pod. Co-locate dependent containers sparingly.
- StatefulSets: For databases, caches with persistent state. PersistentVolumes for storage. StatelessSets for typical applications.
- Service Mesh: Advanced traffic management (Istio); not needed for simple deployments
Instructions
-
Design Cluster Topology: Single cluster (simpler) or multi-cluster (HA, isolation)? Multi-AZ for resilience. Master nodes (API server, etcd) managed by cloud provider (EKS, GKE).
-
Plan Node Sizing: How many nodes for peak load? Large nodes (fewer, simpler) vs small nodes (more flexible). Use auto-scaling to handle traffic spikes.
-
Configure Storage: Stateless apps: no storage needed. Stateful: PersistentVolumes for databases, caches. Use managed databases (RDS) for data, K8s for cache (Redis).
-
Set Up Networking: Calico or Weave for container networking. Service mesh (Istio) for traffic management. Ingress controller for external traffic. Network policies for security.
-
Plan Operations: Helm for templating deployments. Flux or ArgoCD for GitOps-driven deployments. Monitoring (Prometheus), logging (ELK), tracing (Jaeger). Regular upgrades.
Anti-Patterns
- Over-Complexity from Start: Add service mesh, istio, monitoring before you need them. Result: hard to operate, debug. Guard: Start simple; add features when you hit concrete problems.
- Ignoring Resource Limits: Pods unbounded CPU/memory. Result: noisy neighbors, thrashing. Guard: Set requests (guaranteed) and limits (max). Monitor utilization.
- No Pod Disruption Budgets: Kill pods ungracefully during node drains. Result: request loss. Guard: PodDisruptionBudgets ensure minimum replicas during maintenance.
- Persistent State in Pods: Use local storage for databases. Result: lost data on pod restart. Guard: Use PersistentVolumes or managed databases for state.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 48 lines · 34 tokens per session scan A 9bb8d1cf43c2
container-orchestration is a skill published in the GitHub repository sethdford/claude-skills (40 stars, last pushed 6mo ago), licensed MIT. It adds 34 tokens to every session and 670 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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