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cloud-native-readiness

cloud-native-readiness

github.com/zjy365Cloud & DevOps68 installs
Repository

About cloud-native-readiness

A skill that assesses whether a repository is ready for cloud-native microservice deployment. It scores six readiness dimensions, inventories existing Docker and Kubernetes artifacts, and routes suitable projects to dockerfile-skill when artifacts are absent.

Key features

  1. 01Six-dimension readiness assessment
  2. 02Readiness score and report
  3. 03Docker and Kubernetes artifact detection
  4. 04Routing based on readiness and artifacts
  5. 05Context handoff to dockerfile-skill

Use cases

  1. 01Checking a repository before containerization
  2. 02Finding existing Docker or Kubernetes deployment files
  3. 03Identifying changes needed before deployment
  4. 04Passing assessment findings into Dockerfile generation

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/zjy365/sealos-skills --skill cloud-native-readiness

After installing, type/cloud-native-readinessin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

examples/
sample-report.md
knowledge/
anti-patterns.md
criteria.md
scoring-model.md
sealos-patterns.md
modules/
assess.md
detect.md
route.md

Details

From the project README

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 - Analyze the project against cloud-native criteria and produce a readiness report
  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
  │    ├─ NOT suitable → Report reasons, suggest remediation, END
  │    └─ Suitable → Continue
  │
  ├─ 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

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:

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:

# Cloud-Native Readiness Report

## Summary
- **Project**: {name}
- **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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