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Agent skill

Tsh Implementing Kubernetes

by TheSoftwareHouse in TheSoftwareHouse/copilot-collections

Kubernetes deployment patterns, Helm charts, and cluster management.

MITAuto-check passedDevOps & Cloud

Install Tsh Implementing Kubernetes

skills CLI
$ npx skills add TheSoftwareHouse/copilot-collections --skill tsh-implementing-kubernetes -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install TheSoftwareHouse/copilot-collections tsh-implementing-kubernetes --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/TheSoftwareHouse/copilot-collections.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/tsh-implementing-kubernetes .claude/skills/tsh-implementing-kubernetes && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tsh-implementing-kubernetes
GitHub stars
284
Token cost
~2.2k tokens
SKILL.md length
578 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

Kubernetes deployment patterns, Helm charts, and cluster management.

  • Works in 8 steps: Discover context → Check existing K8s… → Choose workload type → Deployment,… → Configure resources → Set… → …
  • Deploying applications to K8s
  • SKILL.md covers When to Use, Project Detection, Workload Type Decision and Deployment Configuration, plus 8 more sections
  • Calls kubectl

What it does

Tsh Implementing Kubernetes is an agent skill from TheSoftwareHouse/copilot-collections. Kubernetes deployment patterns, Helm charts, and cluster management. Use when deploying applications to K8s, designing workload configurations, implementing scaling strategies, or managing cluster resources.

Its SKILL.md is about 2.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in DevOps & Cloud, covering Container orchestration. It works with Kubernetes and Helm. The repository describes itself as: Opinionated AI-enabled workflows for product engineering. The licence is MIT.

When your agent uses it

  • Deploying applications to K8s
  • Designing workload configurations
  • Implementing scaling strategies
  • Managing cluster resources

Example prompts

  • “Use the tsh-implementing-kubernetes skill to kubernete deployment patterns, Helm charts, and cluster management”
  • “/tsh-implementing-kubernetes”

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Discover context → Check existing K8s manifests, Helm charts, Kustomize
  2. Choose workload type → Deployment, StatefulSet, Job based on requirements
  3. Configure resources → Set requests/limits based on profiling or estimates
  4. Add probes → Configure readiness, liveness, and startup probes
  5. Enable scaling → Add HPA/KEDA based on scaling requirements
  6. Add resilience → PDB, pod anti-affinity, topology spread
  7. Configure security → Security context, network policies
  8. Validate → kubectl apply --dry-run=server, helm template

What it can do on your machine

Read from SKILL.md and the folder at commit 2fbe51e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • kubectl

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use kubectl, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tsh Implementing Kubernetes loads about 2.2k tokens when it runs. Until then it costs about 59 tokens; SKILL.md has 578 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~59
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from TheSoftwareHouse/copilot-collections at commit 2fbe51e, republished under its MIT licence (© TheSoftwareHouse). 578 words, ~2,165 tokens.

Download SKILL.mdSave it as .claude/skills/tsh-implementing-kubernetes/SKILL.md (or your agent's skills folder).
name
tsh-implementing-kubernetes
description
Kubernetes deployment patterns, Helm charts, and cluster management. Use when deploying applications to K8s, designing workload configurations, implementing scaling strategies, or managing cluster resources.
user-invocable
false

Kubernetes Patterns

When to Use

  • Deploying applications to Kubernetes
  • Designing Deployment, StatefulSet, or Job configurations
  • Implementing auto-scaling (HPA, VPA, KEDA)
  • Creating or modifying Helm charts
  • Setting up ingress, networking, and service mesh
  • Configuring resource requests, limits, and QoS

Project Detection

Check which Kubernetes tooling the project uses:

  • helm/ or Chart.yaml → Helm charts
  • kustomize/ or kustomization.yaml → Kustomize
  • k8s/ or kubernetes/ with *.yaml → Raw manifests
  • skaffold.yaml → Skaffold for local dev
  • argocd/ or Application resources → ArgoCD GitOps
  • flux-system/ or Kustomization CRD → Flux GitOps

Use context7 to look up Kubernetes API versions and syntax.

Workload Type Decision

Workload TypeUse When
DeploymentStateless apps, web servers, APIs
StatefulSetDatabases, stateful apps needing stable identity
DaemonSetNode-level agents (logging, monitoring)
JobOne-time tasks, batch processing
CronJobScheduled recurring tasks

Deployment Configuration

Resource Management
yaml
resources:
  requests:    # Scheduler uses for placement
    memory: "256Mi"
    cpu: "100m"
  limits:      # Kubelet enforces these
    memory: "512Mi"
    cpu: "500m"

Rules:

  • Always set requests (required for scheduling)
  • Set memory limits to prevent OOM impact on node
  • CPU limits optional (can cause throttling)
  • Request:Limit ratio of 1:2 is good starting point
QoS Classes
ClassConditionEviction Priority
Guaranteedrequests == limits (all containers)Last to evict
Burstablerequests < limitsMedium
BestEffortNo requests or limitsFirst to evict

Rule: Production workloads should be Guaranteed or Burstable, never BestEffort.

Probes Configuration
yaml
livenessProbe:      # Restarts container if fails
  httpGet:
    path: /healthz
    port: 8080
  initialDelaySeconds: 15
  periodSeconds: 10
  failureThreshold: 3

readinessProbe:     # Removes from Service if fails
  httpGet:
    path: /ready
    port: 8080
  initialDelaySeconds: 5
  periodSeconds: 5
  failureThreshold: 3

startupProbe:       # Delays liveness until startup complete
  httpGet:
    path: /healthz
    port: 8080
  failureThreshold: 30
  periodSeconds: 10

Rules:

  • Always configure readinessProbe (graceful traffic handling)
  • Use startupProbe for slow-starting apps (instead of long initialDelaySeconds)
  • livenessProbe should check app health, not dependencies
Pod Disruption Budget
yaml
apiVersion: policy/v1
kind: PodDisruptionBudget
metadata:
  name: api-pdb
spec:
  minAvailable: 2        # OR maxUnavailable: 1
  selector:
    matchLabels:
      app: api

Rule: Always create PDB for production workloads to ensure availability during node drains.

Pod Anti-Affinity
yaml
affinity:
  podAntiAffinity:
    preferredDuringSchedulingIgnoredDuringExecution:
      - weight: 100
        podAffinityTerm:
          labelSelector:
            matchLabels:
              app: api
          topologyKey: kubernetes.io/hostname

Rule: Spread replicas across nodes/zones for high availability.

Scaling Strategies

Horizontal Pod Autoscaler (HPA)
yaml
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: api-hpa
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: api
  minReplicas: 2
  maxReplicas: 10
  metrics:
    - type: Resource
      resource:
        name: cpu
        target:
          type: Utilization
          averageUtilization: 70
  behavior:
    scaleDown:
      stabilizationWindowSeconds: 300  # Prevent flapping
Scaling Decision Matrix
Scaling TypeUse WhenTool
CPU-basedGeneral compute workloadsHPA
Memory-basedMemory-intensive appsHPA
Custom metricsQueue depth, request rateHPA + Prometheus Adapter
Event-drivenMessage queues, scheduled jobsKEDA
VerticalRight-sizing requests/limitsVPA

Helm Chart Structure

mychart/
├── Chart.yaml          # Chart metadata
├── values.yaml         # Default values
├── values-dev.yaml     # Environment overrides
├── values-prod.yaml
├── templates/
│   ├── _helpers.tpl    # Template helpers
│   ├── deployment.yaml
│   ├── service.yaml
│   ├── ingress.yaml
│   ├── hpa.yaml
│   ├── pdb.yaml
│   └── configmap.yaml
└── charts/             # Dependencies
Helm Best Practices
yaml
# values.yaml - use structured defaults
replicaCount: 2

image:
  repository: myapp
  tag: ""  # Override in CI, not here
  pullPolicy: IfNotPresent

resources:
  requests:
    memory: "256Mi"
    cpu: "100m"
  limits:
    memory: "512Mi"

# Enable/disable optional components
autoscaling:
  enabled: true
  minReplicas: 2
  maxReplicas: 10

Rules:

  • Don't hardcode image tags in values.yaml (set in CI)
  • Use {{ include "mychart.fullname" . }} for resource names
  • Provide sensible defaults, override per environment

Ingress Configuration

Ingress Class Decision
Ingress ControllerUse When
nginx-ingressGeneral purpose, widely supported
AWS ALBAWS-native, integrated with WAF/ACM
TraefikSimple setup, automatic HTTPS
Istio GatewayService mesh already in use
Show full SKILL.md (231 more words)Show less
Ingress Example (nginx)
yaml
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
  name: api-ingress
  annotations:
    nginx.ingress.kubernetes.io/ssl-redirect: "true"
    cert-manager.io/cluster-issuer: "letsencrypt-prod"
spec:
  ingressClassName: nginx
  tls:
    - hosts:
        - api.example.com
      secretName: api-tls
  rules:
    - host: api.example.com
      http:
        paths:
          - path: /
            pathType: Prefix
            backend:
              service:
                name: api
                port:
                  number: 80

Security Context

yaml
securityContext:
  runAsNonRoot: true
  runAsUser: 1000
  runAsGroup: 1000
  fsGroup: 1000
  seccompProfile:
    type: RuntimeDefault

containers:
  - name: app
    securityContext:
      allowPrivilegeEscalation: false
      readOnlyRootFilesystem: true
      capabilities:
        drop:
          - ALL

Rule: Always run as non-root with minimal capabilities in production.

Process

  1. Discover context → Check existing K8s manifests, Helm charts, Kustomize
  2. Choose workload type → Deployment, StatefulSet, Job based on requirements
  3. Configure resources → Set requests/limits based on profiling or estimates
  4. Add probes → Configure readiness, liveness, and startup probes
  5. Enable scaling → Add HPA/KEDA based on scaling requirements
  6. Add resilience → PDB, pod anti-affinity, topology spread
  7. Configure security → Security context, network policies
  8. Validate → kubectl apply --dry-run=server, helm template

Checklist

  • Resource requests and limits defined
  • Readiness and liveness probes configured
  • PodDisruptionBudget created for production
  • Pod anti-affinity or topology spread configured
  • HPA configured for variable workloads
  • Security context with non-root user
  • Image pull policy appropriate (Never use latest in prod)
  • Labels consistent (app, version, environment)
  • Namespace isolation per environment

Anti-Patterns

Don'tDo
Use latest image tagPin specific versions or SHA
Skip resource requestsAlways set requests for scheduling
Single replica in productionMinimum 2 replicas with PDB
Run as rootUse non-root user with minimal caps
Missing readiness probeConfigure probes for graceful traffic
kubectl apply in productionGitOps with ArgoCD/Flux
Hardcode values in manifestsUse Helm values or Kustomize overlays
Ignore pod evictionSet PDB to maintain availability
  • tsh-implementing-observability - For K8s monitoring and logging setup
  • tsh-implementing-ci-cd - For K8s deployment pipelines
  • tsh-managing-secrets - For K8s secret management patterns
  • tsh-implementing-terraform-modules - For provisioning K8s clusters

© TheSoftwareHouse, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .github/skills/tsh-implementing-kubernetes of TheSoftwareHouse/copilot-collections.

Open the folder on GitHubat commit 2fbe51e

Compare with similar skills

Tsh Implementing Kubernetes next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tsh Implementing Kubernetes compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tsh Implementing Kubernetes this skillTheSoftwareHouse/copilot-collections284—~2.2kAutomated safety check: PassMIT
Sim Helmsimstudioai/sim30k—~2.2kAutomated safety check: PassApache-2.0
Helm Chart ScaffoldingCybereason-Public/owLSM28013 repos~381Automated safety check: PassGPL-2.0
NGINX Ingress Controller Feature Checklistsnginx/kubernetes-ingress5.1k—~1.4kAutomated safety check: PassApache-2.0
Kubernetes SpecialistJeffallan/claude-skills12k1 repos~2.1kAutomated safety check: PassMIT
KubeShark for KubernetesLukasNiessen/kubernetes-skill444—~1.2kAutomated safety check: PassMIT

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Works with

Categories

Questions about Tsh Implementing Kubernetes

What does Tsh Implementing Kubernetes do?

Kubernetes deployment patterns, Helm charts, and cluster management. Tsh Implementing Kubernetes is an agent skill from TheSoftwareHouse/copilot-collections. Kubernetes deployment patterns, Helm charts, and cluster management.

When should I use Tsh Implementing Kubernetes?

Tsh Implementing Kubernetes fits situations like: deploying applications to K8s; designing workload configurations; implementing scaling strategies; managing cluster resources.

How do I install Tsh Implementing Kubernetes in Claude Code?

Run `npx skills add TheSoftwareHouse/copilot-collections --skill tsh-implementing-kubernetes -a claude-code`. Or copy the skill folder (.github/skills/tsh-implementing-kubernetes in TheSoftwareHouse/copilot-collections) into .claude/skills/tsh-implementing-kubernetes in your project. Claude Code loads it when a task matches its description.

How do I install Tsh Implementing Kubernetes in Codex?

Run `npx skills add TheSoftwareHouse/copilot-collections --skill tsh-implementing-kubernetes -a codex`. Or copy the skill folder (.github/skills/tsh-implementing-kubernetes in TheSoftwareHouse/copilot-collections) into .agents/skills/tsh-implementing-kubernetes in your project. Codex loads it when a task matches its description.

Can I use Tsh Implementing Kubernetes in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add TheSoftwareHouse/copilot-collections --skill tsh-implementing-kubernetes -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tsh-implementing-kubernetes, .gemini/skills/tsh-implementing-kubernetes, .github/skills/tsh-implementing-kubernetes and .opencode/skills/tsh-implementing-kubernetes in your project.

What does Tsh Implementing Kubernetes need to run?

Going by SKILL.md and its folder, Tsh Implementing Kubernetes needs the command-line tools its instructions call (kubectl).

Does Tsh Implementing Kubernetes access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tsh Implementing Kubernetes safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Tsh Implementing Kubernetes use?

Tsh Implementing Kubernetes is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tsh Implementing Kubernetes use?

About 2.2k tokens (SKILL.md is roughly 8.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Tsh Implementing Kubernetes?

Skills that share tags, products or a category with Tsh Implementing Kubernetes: Sim Helm (simstudioai/sim, 30k stars), Helm Chart Scaffolding (Cybereason-Public/owLSM, 280 stars), NGINX Ingress Controller Feature Checklists (nginx/kubernetes-ingress, 5.1k stars) and Kubernetes Specialist (Jeffallan/claude-skills, 12k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tsh Implementing Kubernetes?

TheSoftwareHouse (a GitHub organization) maintains it in TheSoftwareHouse/copilot-collections, which has 284 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 5, 2026.

Source: TheSoftwareHouse/copilot-collections on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.