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 rohitg00/kubectl-mcp-server --skill k8s-deploygit clone --depth 1 https://github.com/rohitg00/kubectl-mcp-serverWrote 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/rohitg00/kubectl-mcp-server/k8s-deploy)<a href="https://agentmods.dev/skills/rohitg00/kubectl-mcp-server/k8s-deploy"><img src="https://agentmods.dev/badge/skills/rohitg00/kubectl-mcp-server/k8s-deploy/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/rohitg00/kubectl-mcp-server/k8s-deploy"><img src="https://agentmods.dev/badge/skills/rohitg00/kubectl-mcp-server/k8s-deploy.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00035 | $0.01380 |
| Opus 5 | $0.00017 | $0.00690 |
| Sonnet 5 | $0.00007 | $0.00276 |
| Haiku 4.5 | $0.00003 | $0.00138 |
Grade A, and why
k8s-deploy 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 9d 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 — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kubernetes Deployment Workflows
Comprehensive deployment strategies using kubectl-mcp-server tools, including Argo Rollouts and Flagger for progressive delivery.
When to Apply
Use this skill when:
- User mentions: "deploy", "release", "rollout", "scale", "update", "upgrade"
- Operations: creating deployments, updating images, scaling replicas
- Strategies: canary, blue-green, rolling update, recreate
- Keywords: "new version", "push to production", "traffic shifting"
Priority Rules
| Priority | Rule | Impact | Tools |
|---|---|---|---|
| 1 | Preview with template before apply | CRITICAL | template_helm_chart |
| 2 | Check existing state first | CRITICAL | get_pods, list_helm_releases |
| 3 | Use progressive delivery for prod | HIGH | rollout_* tools |
| 4 | Verify health after deployment | HIGH | get_pod_metrics, get_endpoints |
| 5 | Keep rollback revision noted | MEDIUM | get_helm_history |
| 6 | Scale incrementally | LOW | scale_deployment |
Quick Reference
| Task | Tool | Example |
|---|---|---|
| Deploy from manifest | kubectl_apply |
apply_manifest(yaml, namespace) |
| Deploy with Helm | install_helm_chart |
install_helm_chart(name, chart, namespace) |
| Update image | set_deployment_image |
set_deployment_image(name, ns, container, image) |
| Scale replicas | scale_deployment |
scale_deployment(name, ns, replicas=5) |
| Rollback | rollback_deployment |
rollback_deployment(name, ns, revision=0) |
| Canary promote | rollout_promote_tool |
rollout_promote_tool(name, ns) |
Standard Deployments
Deploy from Manifest
kubectl_apply(manifest_yaml, namespace)
Deploy with Helm
install_helm_chart(
name="my-app",
chart="bitnami/nginx",
namespace="production",
values={"replicaCount": 3}
)
Scale Deployment
scale_deployment(name, namespace, replicas=5)
Rolling Update
set_deployment_image(name, namespace, container="app", image="myapp:v2")
rollout_status(name, namespace, resource_type="deployment")
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 208 lines · 35 tokens per session scan A 1375674eb8eb
k8s-deploy is a skill published in the GitHub repository rohitg00/kubectl-mcp-server (956 stars, last pushed 5mo ago), licensed MIT. It adds 35 tokens to every session and 1,380 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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