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Cloud Migration Planning

Community
aj-geddes
cloud-migration-planning

Plan and execute cloud migrations with assessment, database migration, application refactoring, and cutover strategies across AWS, Azure, and GCP.

Overview

Publisheraj-geddes
Repositoryuseful-ai-prompts
Skill namecloud-migration-planning
Stars
340
Forks
55
Bundled files
6
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 6 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by aj-geddes on GitHub. Read the source before you install it.

Installation

Install the Cloud Migration Planning AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/aj-geddes/useful-ai-prompts.git /tmp/useful-ai-prompts
mkdir -p .claude/skills
cp -r /tmp/useful-ai-prompts/skills/cloud-migration-planning .claude/skills/cloud-migration-planning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Migration Planning in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cloud Migration Planning on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cloud Migration Planning is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Cloud Migration Planning

Table of Contents

Overview

Cloud migration planning involves assessing current infrastructure, designing migration strategies, executing migrations with minimal downtime, and validating outcomes. Support lift-and-shift, replatforming, and refactoring approaches for smooth cloud adoption.

When to Use

  • Moving from on-premises to cloud
  • Cloud platform consolidation
  • Legacy system modernization
  • Reducing data center costs
  • Improving scalability and availability
  • Meeting compliance requirements
  • Disaster recovery enhancement
  • Technology refresh initiatives

Quick Start

Minimal working example:

python
# Cloud migration assessment tool
from enum import Enum
from typing import Dict, List, Tuple
from dataclasses import dataclass

class MigrationStrategy(Enum):
    LIFT_AND_SHIFT = "lift_and_shift"  # Rehost
    REPLATFORM = "replatform"          # Rehost with optimizations
    REFACTOR = "refactor"              # Rebuild for cloud
    REPURCHASE = "repurchase"          # Switch to SaaS
    RETIRE = "retire"                  # Decommission

class ApplicationComplexity(Enum):
    LOW = 1
    MEDIUM = 2
    HIGH = 3

@dataclass
class ApplicationAssessment:
    name: str
    complexity: ApplicationComplexity
    dependencies: List[str]
    estimated_effort: int  # days
    business_criticality: int  # 1-10
    current_costs: float  # annual
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
Migration Assessment and PlanningMigration Assessment and Planning
Database Migration StrategiesDatabase Migration Strategies
Terraform Migration InfrastructureTerraform Migration Infrastructure
Cutover Validation ChecklistCutover Validation Checklist

Best Practices

✅ DO

  • Perform thorough discovery and assessment
  • Run parallel systems during transition
  • Test thoroughly before cutover
  • Have rollback plan ready
  • Monitor closely post-migration
  • Document all changes
  • Train operations team
  • Maintain previous systems temporarily

❌ DON'T

  • Rush migration without planning
  • Migrate without testing
  • Forget rollback procedures
  • Ignore dependencies
  • Skip stakeholder communication
  • Migrate everything at once
  • Forget to update documentation

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cloud Migration Planning AI skill do?

Plan and execute cloud migrations with assessment, database migration, application refactoring, and cutover strategies across AWS, Azure, and GCP.

Why use Cloud Migration Planning on TypingMind?

Because you install it once and use it with any model. Cloud Migration Planning is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cloud Migration Planning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/cloud-migration-planning. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cloud Migration Planning?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cloud Migration Planning?

As many as you like. As long as a model supports skills, you can use Cloud Migration Planning with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cloud Migration Planning AI skill free?

Yes. It is published on GitHub by aj-geddes under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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