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Agent Skill · 运维和基础设施

k8s-manifest-generator(Kubernetes manifest 生成器)

k8s-manifest-generator 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

k8s-manifest-generator 是运维和基础设施类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有未通过项,按安装量在运维和基础设施类的 2,449 个 Skill 里排第 915。

总安装 1,224周安装 50GitHub Stars 25下载 392核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:k8s-manifest-generator(Kubernetes manifest 生成器)
来源仓库:https://github.com/oimiragieo/agent-studio
仓库路径:skills/k8s-manifest-generator
安装命令:
npx skills add https://github.com/oimiragieo/agent-studio --skill k8s-manifest-generator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/oimiragieo/agent-studio --skill k8s-manifest-generator

这个 Skill 是做什么的

运维和基础设施类 Skill 处理部署、监控、日志和云资源,多数需要较高的执行权限。

k8s-manifest-generator 处理 GitHub 仓库、Issue、PR 和代码协作信息,适合整理仓库状态和变更事项。适用于在 Codex、Claude、Cursor、Gemini CLI 中围绕协作流程进行信息梳理的场景。

通过 npx skills add 命令从 GitHub 安装,结合原始 README 核验具体用法。安装前需确认权限范围和维护状态,注意是否触发联网、命令执行或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/k8s-manifest-generator

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/oimiragieo/agent-studio --skill k8s-manifest-g…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

k8s-manifest-generator 怎么安装?

在终端执行 npx skills add https://github.com/oimiragieo/agent-studio --skill k8s-manifest-generator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

k8s-manifest-generator 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

k8s-manifest-generator 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

k8s-manifest-generator 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

k8s-manifest-generator 用的人多吗?

公开数据是累计安装 1,224 次,近一周安装 50 次,下载 392 次,GitHub 25 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

k8s-manifest-generator 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理运维和基础设施类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

运维和基础设施类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
brainstorming

头脑风暴 · Codex、Claude

3,148,776173,131操作浏览器MIT通过
copywriting

文案写作 · Codex、Claude

1,996,72425,583需要联网MIT通过
openclaw-secure-linux-cloud

OpenClaw secure linux cloud 命令行 · Codex、Claude

1,853,08840接触敏感数据未明确未通过
xget

xget 命令行 · Codex、Claude

1,799,28040执行命令未明确未通过
requesting-code-review

代码审查请求 · Codex、Claude

1,590,144173,103权限未标注MIT通过
k8s-manifest-generator

Kubernetes manifest 生成器 · 本页

1,22425接触敏感数据未明确未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Kubernetes Manifest Generator

Step-by-step guidance for creating production-ready Kubernetes manifests including Deployments, Services, ConfigMaps, Secrets, and PersistentVolumeClaims.

Purpose

This skill provides comprehensive guidance for generating well-structured, secure, and production-ready Kubernetes manifests following cloud-native best practices and Kubernetes conventions.

When to Use This Skill

Use this skill when you need to:

  • Create new Kubernetes Deployment manifests
  • Define Service resources for network connectivity
  • Generate ConfigMap and Secret resources for configuration management
  • Create PersistentVolumeClaim manifests for stateful workloads
  • Follow Kubernetes best practices and naming conventions
  • Implement resource limits, health checks, and security contexts
  • Design manifests for multi-environment deployments

Step-by-Step Workflow

1. Gather Requirements

Understand the workload:

  • Application type (stateless/stateful)
  • Container image and version
  • Environment variables and configuration needs
  • Storage requirements
  • Network exposure requirements (internal/external)
  • Resource requirements (CPU, memory)
  • Scaling requirements
  • Health check endpoints

Questions to ask:

  • What is the application name and purpose?
  • What container image and tag will be used?
  • Does the application need persistent storage?
  • What ports does the application expose?
  • Are there any secrets or configuration files needed?
  • What are the CPU and memory requirements?
  • Does the application need to be exposed externally?

2. Create Deployment Manifest

Follow this structure:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: <app-name>
  namespace: <namespace>
  labels:
    app: <app-name>
    version: <version>
spec:
  replicas: 3
  selector:
    matchLabels:
      app: <app-name>
  template:
    metadata:
      labels:
        app: <app-name>
        version: <version>
    spec:
      containers:
        - name: <container-name>
          image: <image>:<tag>
          ports:
            - containerPort: <port>
              name: http
          resources:
            requests:
              memory: '256Mi'
              cpu: '250m'
            limits:
              memory: '512Mi'
              cpu: '500m'
          livenessProbe:
            httpGet:
              path: /health
              port: http
            initialDelaySeconds: 30
            periodSeconds: 10
          readinessProbe:
            httpGet:
              path: /ready
              port: http
            initialDelaySeconds: 5
            periodSeconds: 5
          env:
            - name: ENV_VAR
              value: 'value'
          envFrom:
            - configMapRef:
                name: <app-name>-config
            - secretRef:
                name: <app-name>-secret

Best practices to apply:

  • Always set resource requests and limits
  • Implement both liveness and readiness probes
  • Use specific image tags (never :latest)
  • Apply security context for non-root users
  • Use labels for organization and selection
  • Set appropriate replica count based on availability needs

Reference: See references/deployment-spec.md for detailed deployment options

3. Create Service Manifest

Choose the appropriate Service type:

ClusterIP (internal only):

apiVersion: v1
kind: Service
metadata:
  name: <app-name>
  namespace: <namespace>
  labels:
    app: <app-name>
spec:
  type: ClusterIP
  selector:
    app: <app-name>
  ports:
    - name: http
      port: 80
      targetPort: 8080
      protocol: TCP

LoadBalancer (external access):

apiVersion: v1
kind: Service
metadata:
  name: <app-name>
  namespace: <namespace>
  labels:
    app: <app-name>
  annotations:
    service.beta.kubernetes.io/aws-load-balancer-type: nlb
spec:
  type: LoadBalancer
  selector:
    app: <app-name>
  ports:
    - name: http
      port: 80
      targetPort: 8080
      protocol: TCP

Reference: See references/service-spec.md for service types and networking

4. Create ConfigMap

For application configuration:

apiVersion: v1
kind: ConfigMap
metadata:
  name: <app-name>-config
  namespace: <namespace>
data:
  APP_MODE: production
  LOG_LEVEL: info
  DATABASE_HOST: db.example.com
  # For config files
  app.properties: |
    server.port=8080
    server.host=0.0.0.0
    logging.level=INFO

Best practices:

  • Use ConfigMaps for non-sensitive data only
  • Organize related configuration together
  • Use meaningful names for keys
  • Consider using one ConfigMap per component
  • Version ConfigMaps when making changes

Reference: See assets/configmap-template.yaml for examples

5. Create Secret

For sensitive data:

apiVersion: v1
kind: Secret
metadata:
  name: <app-name>-secret
  namespace: <namespace>
type: Opaque
stringData:
  DATABASE_PASSWORD: 'changeme'
  API_KEY: 'secret-api-key'
  # For certificate files
  tls.crt: |
    -----BEGIN CERTIFICATE-----
    ...
    -----END CERTIFICATE-----
  tls.key: |
    -----BEGIN PRIVATE KEY-----
    ...
    -----END PRIVATE KEY-----

Security considerations:

  • Never commit secrets to Git in plain text
  • Use Sealed Secrets, External Secrets Operator, or Vault
  • Rotate secrets regularly
  • Use RBAC to limit secret access
  • Consider using Secret type: kubernetes.io/tls for TLS secrets

6. Create PersistentVolumeClaim (if needed)

For stateful applications:

apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: <app-name>-data
  namespace: <namespace>
spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: gp3
  resources:
    requests:
      storage: 10Gi

Mount in Deployment:

spec:
  template:
    spec:
      containers:
        - name: app
          volumeMounts:
            - name: data
              mountPath: /var/lib/app
      volumes:
        - name: data
          persistentVolumeClaim:
            claimName: <app-name>-data

Storage considerations:

  • Choose appropriate StorageClass for performance needs
  • Use ReadWriteOnce for single-pod access
  • Use ReadWriteMany for multi-pod shared storage
  • Consider backup strategies
  • Set appropriate retention policies

7. Apply Security Best Practices

Add security context to Deployment:

spec:
  template:
    spec:
      securityContext:
        runAsNonRoot: true
        runAsUser: 1000
        fsGroup: 1000
        seccompProfile:
          type: RuntimeDefault
      containers:
        - name: app
          securityContext:
            allowPrivilegeEscalation: false
            readOnlyRootFilesystem: true
            capabilities:
              drop:
                - ALL

Security checklist:

  • Run as non-root user
  • Drop all capabilities
  • Use read-only root filesystem
  • Disable privilege escalation
  • Set seccomp profile
  • Use Pod Security Standards

8. Add Labels and Annotations

Standard labels (recommended):

metadata:
  labels:
    app.kubernetes.io/name: <app-name>
    app.kubernetes.io/instance: <instance-name>
    app.kubernetes.io/version: '1.0.0'
    app.kubernetes.io/component: backend
    app.kubernetes.io/part-of: <system-name>
    app.kubernetes.io/managed-by: kubectl

Useful annotations:

metadata:
  annotations:
    description: 'Application description'
    contact: 'team@example.com'
    prometheus.io/scrape: 'true'
    prometheus.io/port: '9090'
    prometheus.io/path: '/metrics'

9. Organize Multi-Resource Manifests

File organization options:

Option 1: Single file with --- separator

# app-name.yaml
---
apiVersion: v1
kind: ConfigMap
...
---
apiVersion: v1
kind: Secret
...
---
apiVersion: apps/v1
kind: Deployment
...
---
apiVersion: v1
kind: Service
...

Option 2: Separate files

manifests/
├── configmap.yaml
├── secret.yaml
├── deployment.yaml
├── service.yaml
└── pvc.yaml

Option 3: Kustomize structure

base/
├── kustomization.yaml
├── deployment.yaml
├── service.yaml
└── configmap.yaml
overlays/
├── dev/
│   └── kustomization.yaml
└── prod/
    └── kustomization.yaml

10. Validate and Test

Validation steps:

# Dry-run validation
kubectl apply -f manifest.yaml --dry-run=client

# Server-side validation
kubectl apply -f manifest.yaml --dry-run=server

# Validate with kubeval
kubeval manifest.yaml

# Validate with kube-score
kube-score score manifest.yaml

# Check with kube-linter
kube-linter lint manifest.yaml

Testing checklist:

  • Manifest passes dry-run validation
  • All required fields are present
  • Resource limits are reasonable
  • Health checks are configured
  • Security context is set
  • Labels follow conventions
  • Namespace exists or is created

Common Patterns

Pattern 1: Simple Stateless Web Application

Use case: Standard web API or microservice

Components needed:

  • Deployment (3 replicas for HA)
  • ClusterIP Service
  • ConfigMap for configuration
  • Secret for API keys
  • HorizontalPodAutoscaler (optional)

Reference: See assets/deployment-template.yaml

Pattern 2: Stateful Database Application

Use case: Database or persistent storage application

Components needed:

  • StatefulSet (not Deployment)
  • Headless Service
  • PersistentVolumeClaim template
  • ConfigMap for DB configuration
  • Secret for credentials

Pattern 3: Background Job or Cron

Use case: Scheduled tasks or batch processing

Components needed:

  • CronJob or Job
  • ConfigMap for job parameters
  • Secret for credentials
  • ServiceAccount with RBAC

Pattern 4: Multi-Container Pod

Use case: Application with sidecar containers

Components needed:

  • Deployment with multiple containers
  • Shared volumes between containers
  • Init containers for setup
  • Service (if needed)

Templates

The following templates are available in the assets/ directory:

  • deployment-template.yaml - Standard deployment with best practices
  • service-template.yaml - Service configurations (ClusterIP, LoadBalancer, NodePort)
  • configmap-template.yaml - ConfigMap examples with different data types
  • secret-template.yaml - Secret examples (to be generated, not committed)
  • pvc-template.yaml - PersistentVolumeClaim templates

Reference Documentation

  • references/deployment-spec.md - Detailed Deployment specification
  • references/service-spec.md - Service types and networking details

Best Practices Summary

  1. Always set resource requests and limits - Prevents resource starvation
  2. Implement health checks - Ensures Kubernetes can manage your application
  3. Use specific image tags - Avoid unpredictable deployments
  4. Apply security contexts - Run as non-root, drop capabilities
  5. Use ConfigMaps and Secrets - Separate config from code
  6. Label everything - Enables filtering and organization
  7. Follow naming conventions - Use standard Kubernetes labels
  8. Validate before applying - Use dry-run and validation tools
  9. Version your manifests - Keep in Git with version control
  10. Document with annotations - Add context for other developers

Troubleshooting

Pods not starting:

  • Check image pull errors: kubectl describe pod <pod-name>
  • Verify resource availability: kubectl get nodes
  • Check events: kubectl get events --sort-by='.lastTimestamp'

Service not accessible:

  • Verify selector matches pod labels: kubectl get endpoints <service-name>
  • Check service type and port configuration
  • Test from within cluster: kubectl run debug --rm -it --image=busybox -- sh

ConfigMap/Secret not loading:

  • Verify names match in Deployment
  • Check namespace
  • Ensure resources exist: kubectl get configmap,secret

Next Steps

After creating manifests:

  1. Store in Git repository
  2. Set up CI/CD pipeline for deployment
  3. Consider using Helm or Kustomize for templating
  4. Implement GitOps with ArgoCD or Flux
  5. Add monitoring and observability

Iron Laws

  1. ALWAYS set CPU and memory resource requests and limits on every container — pods without resource limits consume unbounded node resources, cause node pressure evictions, and starve neighboring workloads.
  2. NEVER run containers as root (runAsNonRoot: false or omitted) in production — root containers can escape containment via kernel exploits; always set securityContext.runAsNonRoot: true with a specific runAsUser.
  3. ALWAYS define liveness and readiness probes on every workload — without probes, Kubernetes cannot distinguish a deadlocked container from a healthy one; failing probes block deployments and traffic incorrectly.
  4. NEVER store secrets in ConfigMaps — ConfigMaps are stored in plaintext in etcd; use Kubernetes Secrets (with etcd encryption at rest) or an external secrets manager (Vault, AWS Secrets Manager).
  5. ALWAYS set a PodDisruptionBudget for production workloads — without PDBs, node drains during upgrades can terminate all replicas simultaneously, causing complete service outages.

Anti-Patterns

Anti-PatternWhy It FailsCorrect Approach
No resource limitsPod consumes all node memory; node OOM kills other pods; cluster destabilizedSet requests (scheduling) and limits (enforcement) for CPU and memory on every container
Running as rootKernel exploits allow container escape; file system writes as root corrupt hostSet runAsNonRoot: true, runAsUser: 1000, readOnlyRootFilesystem: true
Missing liveness/readiness probesDeadlocked pods serve traffic; new pods receive traffic before readyAdd /health liveness and /ready readiness probes with appropriate initialDelaySeconds
Secrets in ConfigMapsPlaintext in etcd; visible in kubectl get configmap; audit log exposes valuesUse kind: Secret with base64 encoding; enable etcd encryption; prefer external secrets
Single replica for productionPod restart = service outage; zero tolerance for node failureMinimum 2 replicas + PodAntiAffinity rules to spread across nodes; PodDisruptionBudget

Related Skills

  • helm-chart-scaffolding - For templating and packaging
  • gitops-workflow - For automated deployments
  • k8s-security-policies - For advanced security configurations

Memory Protocol (MANDATORY)

Before starting:

cat C:\dev\projects\agent-studio\.claude\context\memory\learnings.md

After completing:

  • New pattern -> C:\dev\projects\agent-studio\.claude\context\memory\learnings.md
  • Issue found -> C:\dev\projects\agent-studio\.claude\context\memory\issues.md
  • Decision made -> C:\dev\projects\agent-studio\.claude\context\memory\decisions.md
ASSUME INTERRUPTION: If it's not in memory, it didn't happen.

平台分布

Codex

32.55%
按下载量换算128

Claude

28.74%
按下载量换算113

Cursor

19.61%
按下载量换算77

Gemini CLI

9.33%
按下载量换算37

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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