k8s-ops

k8s-ops is a skill for Claude Code from jingyanjiang/k8s-mcp. It costs 77 tokens per session (3,043 once invoked), scanned A, original, MIT.

A guided operations workflow for Kubernetes, a system that runs and manages containerized applications across machines. It uses an MCP server to sequence deployment, debugging, restart, rollout, and security-audit actions.

In plain words
What is it for?
Use it to deploy an application from a repository, diagnose failing pods or rollouts, safely restart or update deployments, and review access rules and secrets.
Why use it?
It provides a defined path for common cluster operations and checks important context before changes. This helps avoid acting on the wrong cluster, namespace, or resource.

Skill for Claude Code

Written for Claude Code: user-invocable in frontmatter.

Good fit Use it to deploy an application from a repository, diagnose failing pods or rollouts, safely restart or update deployments, and review access rules and secrets.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/jingyanjiang/k8s-mcp/k8s-ops
Install

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.

Any agent
npx skills add jingyanjiang/k8s-mcp --skill k8s-ops
Clone the repo
git clone --depth 1 https://github.com/jingyanjiang/k8s-mcp

Made for: Claude Code.

Wrote 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.

agentmods badge for k8s-ops

README.md
[![agentmods](https://agentmods.dev/badge/skills/jingyanjiang/k8s-mcp/k8s-ops/github.svg)](https://agentmods.dev/skills/jingyanjiang/k8s-mcp/k8s-ops)
Your own site
<a href="https://agentmods.dev/skills/jingyanjiang/k8s-mcp/k8s-ops"><img src="https://agentmods.dev/badge/skills/jingyanjiang/k8s-mcp/k8s-ops/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.

agentmods 80×15 button for k8s-ops

Your own site · 80×15
<a href="https://agentmods.dev/skills/jingyanjiang/k8s-mcp/k8s-ops"><img src="https://agentmods.dev/badge/skills/jingyanjiang/k8s-mcp/k8s-ops.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,043 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00077 $0.03043
Opus 5 $0.00039 $0.01522
Sonnet 5 $0.00015 $0.00609
Haiku 4.5 $0.00008 $0.00304

Measured 12d ago against content hash dc99737f161c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

k8s-ops scanned grade A with 1 finding 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 12d 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

| Connection / DNS issues reported by app | `exec_command` with `nslookup` / `curl` to dependent services; `get_service` on the dep | Verify cluster DNS and Service selector match |
skills/k8s-ops/SKILL.md · 169 lines

How it starts

The opening of the file, as written. The whole thing — 169 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are operating against a Kubernetes cluster through the k8s-mcp server. The server already enforces these rules — do not restate them, just follow them:

  • Confirm namespace before any operation if not explicitly provided
  • Confirm name + namespace + cluster before any destructive op (delete, scale-to-0, restart)
  • Use get_current_context to verify the active cluster before changes
  • Use list/get tools for discovery rather than guessing

This skill adds workflow sequencing on top of those rules. Pick the mode that matches the user's request.


Mode dispatch

User intent Mode
"deploy this app/repo to my cluster" deploy
"my pod is crashing / failing / not ready" debug
"restart / roll out / update this deployment" rollout
"review RBAC / secrets / who can access what" audit

If the request blends modes (e.g., "deploy and debug if it fails"), run them in sequence — deploy first, then debug if wait_for_ready reports failure.


Mode: deploy

For "deploy this repo / app to a cluster" requests.

Preconditions (confirm with user before touching the cluster)

  1. Active cluster — call get_current_context, show the cluster name, ask if it's the right target.
  2. Target namespace — if unsure, list_namespaces and ask. Do not default to default.
  3. Container image — registry, repo, tag. If the repo has a Dockerfile but no built image, flag that the user must build/push first; do not attempt the build inside this skill.
  4. ImagePullSecret — ask only if the registry is private.

Sequence

  1. Analyze repo — read Dockerfile, pyproject.toml/package.json, any existing k8s/ or manifests/ directory. If manifests already exist, prefer apply_kustomize or apply_manifest on what's there over generating new ones.
  2. Generate manifests if neededgenerate_deploy_manifests with the confirmed values. Write to a k8s/ directory in the repo, not a temp dir.
  3. Show the plan — list the resources to be created, the namespace, and the cluster. Wait for user approval.
  4. Applyapply_kustomize is required for manifests produced by generate_deploy_manifests: the registry/tag substitution lives in kustomization.yaml's images: field. Applying the individual deployment.yaml with apply_manifest will leave the placeholder image: k8s-mcp and the pod will fail to pull. Use apply_manifest only for hand-written single-document manifests with fully qualified image references.
  5. Waitwait_for_ready with resource_type=deployment, a sensible timeout (120s default; 300s for first-time pulls of large images).
  6. Verify — on success, get_deployment + list_pods (label-selector scoped). Report endpoint(s) from get_service if a Service was created.
  7. On failure of wait_for_ready — switch to debug mode automatically on the failing pod. Do not retry the apply blindly.

Read the full file on GitHub · 169 lines

Changes

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.

  1. 12d ago First seen · 169 lines · 0 tokens per session scan A dc99737f161c

Subscribe to this mod's changes

k8s-ops is a skill published in the GitHub repository jingyanjiang/k8s-mcp (3 stars, last pushed 3mo ago), licensed MIT. It adds 77 tokens to every session and 3,043 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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