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Cloud native readiness

Skill labring/sealos-skills/skills/cloud-native-readiness

AI agent skills for Sealos — deploy any project, provision databases, object storage & more with one command. Works with Claude Code, Gemini CLI, Codex.

Install
npx -y skills add labring/sealos-skills --skill cloud-native-readiness

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Determine whether a repository contains a supported cloud workload, then assess eligible targets for cloud-native readiness with a 0-12 score. Use for containerization readiness, Docker/Kubernetes compatibility, deployment feasibility, workload eligibility, or pre-deployment assessment. Also triggers on "/cloud-native-readiness".

SKILL.md

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Cloud Native Readiness Assessment Skill

Overview

This skill evaluates a repository's readiness for cloud-native microservice deployment through a 3-phase workflow:

  1. Assess - Reject unsupported workload types, then score eligible targets
  2. Detect - Check if Docker artifacts already exist (Dockerfile, docker-compose, container images)
  3. Route - If artifacts exist, return the result directly; if not, invoke dockerfile-skill to containerize

Workflow

cloud-native-readiness
  │
  ├─ Phase 1: Cloud-Native Assessment
  │    ├─ Eligibility fails or needs review → Report evidence, END
  │    └─ Eligible → Calculate readiness score
  │
  ├─ Phase 2: Existing Artifacts Detection
  │    ├─ Found Dockerfile/docker-compose/image → Report existing setup, END
  │    └─ Not found → Continue
  │
  └─ Phase 3: Route to dockerfile-skill
       └─ Invoke /dockerfile to generate Docker configuration

Usage

/cloud-native-readiness              # Assess current directory
/cloud-native-readiness <path>       # Assess specific path
/cloud-native-readiness <github-url> # Clone and assess

Quick Start

When invoked, ALWAYS follow this sequence:

  1. Read and execute modules/assess.md — Cloud-native readiness evaluation
  2. Read and execute modules/detect.md — Existing Docker artifacts detection
  3. Read and execute modules/route.md — Decision routing

Phase 1: Cloud-Native Readiness Assessment

Load and execute: modules/assess.md

Apply knowledge/deployment-eligibility.md before assigning a readiness score. Continue only when the requested root is classified eligible.

Evaluates 6 dimensions (each scored 0-2):

DimensionWhat to check
StatelessnessDoes the app store state locally (sessions in memory, local file writes)?
Config ExternalizationAre configs hardcoded or driven by env vars / config files?
Horizontal ScalabilityCan multiple instances run without conflicts?
Startup/ShutdownDoes the app start fast and handle SIGTERM gracefully?
ObservabilityDoes it have health checks, structured logging, metrics?
Service BoundariesIs it a focused service or a tightly-coupled monolith?

Scoring:

  • 10-12: Excellent — fully cloud-native ready
  • 7-9: Good — ready with minor adjustments
  • 4-6: Fair — needs some refactoring before containerization
  • 0-3: Poor — significant rework needed, not recommended for containerization now

Output: Structured readiness report with score, findings, and recommendations.

Phase 2: Existing Artifacts Detection

Load and execute: modules/detect.md

Checks for:

  • Dockerfile / Dockerfile.* (multi-stage, multi-service)
  • docker-compose.yml / docker-compose.yaml / compose.yml
  • .dockerignore
  • DOCKER.md or docker-related documentation
  • Container registry references (ghcr.io, docker.io, ECR, GCR, ACR)
  • Kubernetes manifests (k8s/, kubernetes/, deploy/, helm/, charts/)
  • CI/CD pipeline with Docker build steps (.github/workflows/, .gitlab-ci.yml)

Output: Inventory of existing Docker/K8s artifacts with quality assessment.

Phase 3: Routing Decision

Load and execute: modules/route.md

Decision Matrix:

An ineligible or unresolved needs_review result always stops before artifact detection or Dockerfile generation. Apply the score matrix only to eligible targets.

Readiness ScoreArtifacts ExistAction
≥ 7Yes, completeReport existing setup. Done.
≥ 7Yes, partialReport gaps, suggest improvements. Done.
≥ 7NoInvoke dockerfile-skill to generate.
4-6AnyReport issues + remediation steps. Optionally proceed with dockerfile-skill.
0-3AnyReport blockers. Do NOT invoke dockerfile-skill.

Readiness Report Format

The final output MUST use this format:

For a stopped eligibility result, report its workload type, reason codes, evidence, and next action without inventing a readiness score.

# Cloud-Native Readiness Report

## Summary
- **Project**: {name}
- **Eligibility**: {eligible | ineligible | needs_review} — {workload type}
- **Score**: {score}/12 ({rating})
- **Verdict**: {Ready | Ready with caveats | Needs work | Not recommended}

## Assessment Details

### ✅ Strengths
- {what's already cloud-native friendly}

### ⚠️ Concerns
- {issues that need attention}

### ❌ Blockers (if any)
- {critical issues preventing containerization}

## Dimension Scores

| Dimension | Score | Notes |
|-----------|-------|-------|
| Statelessness | {0-2} | {detail} |
| Config Externalization | {0-2} | {detail} |
| Horizontal Scalability | {0-2} | {detail} |
| Startup/Shutdown | {0-2} | {detail} |
| Observability | {0-2} | {detail} |
| Service Boundaries | {0-2} | {detail} |

## Existing Docker Artifacts
- {inventory or "None found"}

## Recommendation
- {next steps}

Supporting Resources

Integration with dockerfile-skill

When routing to dockerfile-skill, pass the assessment context:

  1. The readiness report findings inform Dockerfile generation decisions
  2. Detected external services map directly to docker-compose.yml services
  3. Identified concerns become Dockerfile comments / DOCKER.md caveats
  4. The assessment's config externalization findings drive ENV/ARG setup

Handoff: When invoking dockerfile-skill, include a summary of:

  • Detected language/framework/package manager
  • External service dependencies
  • Config externalization status
  • Any special concerns (stateful components, long startup, etc.)

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