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 jingyanjiang/k8s-mcp --skill k8s-opsgit clone --depth 1 https://github.com/jingyanjiang/k8s-mcpWrote 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/jingyanjiang/k8s-mcp/k8s-ops)<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.
<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>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 | $0.00077 | $0.03043 |
| Opus 5 | $0.00039 | $0.01522 |
| Sonnet 5 | $0.00015 | $0.00609 |
| Haiku 4.5 | $0.00008 | $0.00304 |
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 | 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_contextto 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)
- Active cluster — call
get_current_context, show the cluster name, ask if it's the right target. - Target namespace — if unsure,
list_namespacesand ask. Do not default todefault. - 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.
- ImagePullSecret — ask only if the registry is private.
Sequence
- Analyze repo — read
Dockerfile,pyproject.toml/package.json, any existingk8s/ormanifests/directory. If manifests already exist, preferapply_kustomizeorapply_manifeston what's there over generating new ones. - Generate manifests if needed —
generate_deploy_manifestswith the confirmed values. Write to ak8s/directory in the repo, not a temp dir. - Show the plan — list the resources to be created, the namespace, and the cluster. Wait for user approval.
- Apply —
apply_kustomizeis required for manifests produced bygenerate_deploy_manifests: the registry/tag substitution lives inkustomization.yaml'simages:field. Applying the individualdeployment.yamlwithapply_manifestwill leave the placeholderimage: k8s-mcpand the pod will fail to pull. Useapply_manifestonly for hand-written single-document manifests with fully qualified image references. - Wait —
wait_for_readywithresource_type=deployment, a sensible timeout (120s default; 300s for first-time pulls of large images). - Verify — on success,
get_deployment+list_pods(label-selector scoped). Report endpoint(s) fromget_serviceif a Service was created. - On failure of
wait_for_ready— switch todebugmode automatically on the failing pod. Do not retry the apply blindly.
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.
- 12d ago First seen · 169 lines · 0 tokens per session scan A dc99737f161c
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.
Other skills, from other repositories
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pod-pending-debug
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kubernetes
Kubernetes operations playbook for deploying services: core objects, probes, resource sizing, safe rollouts, and fast kubectl debugging.
container-manager-kubernetes-operations
Full operational Kubernetes surface via the container-manager-mcp MCP server — workloads (pods/rollouts/StatefulSets/DaemonSets/ReplicaSets/Jobs/CronJobs), config (ConfigMaps/Secrets/Namespaces/CRDs/patch), networking (Ingress/native Services/NetworkPolicy/DNS), storage (PV/PVC/StorageClass/snapshots/CSI), RBAC…
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Use when pods are in CrashLoopBackOff, ImagePullBackOff, ErrImagePull, or OOMKilled — collects describe/logs/events and identifies the failure class before recommending a fix.
kubernetes-mesh-provisioner
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