Cloud Storage Optimization

Community

aj-geddes

cloud-storage-optimization

Optimize cloud storage across AWS S3, Azure Blob, and GCP Cloud Storage with compression, partitioning, lifecycle policies, and cost management.

Overview

Publisher	aj-geddes
Repository	`useful-ai-prompts`
Skill name	`cloud-storage-optimization`
Stars	340
Forks	55
Bundled files	6
License	MIT
Links	Skill source Repository

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 Storage Optimization AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/cloud-storage-optimization

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-storage-optimization .claude/skills/cloud-storage-optimization

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Storage Optimization 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 Storage Optimization 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 Storage Optimization 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.

Overview

Optimize cloud storage costs and performance across multiple cloud providers using compression, intelligent tiering, data partitioning, and lifecycle management. Reduce storage costs while maintaining accessibility and compliance requirements.

When to Use

Reducing storage costs
Optimizing data access patterns
Implementing tiered storage strategies
Archiving historical data
Improving data retrieval performance
Managing compliance requirements
Organizing large datasets
Optimizing data lakes and data warehouses

Quick Start

Minimal working example:

bash
# Enable Intelligent-Tiering
aws s3api put-bucket-intelligent-tiering-configuration \
  --bucket my-bucket \
  --id OptimizedStorage \
  --intelligent-tiering-configuration '{
    "Id": "OptimizedStorage",
    "Filter": {"Prefix": "data/"},
    "Status": "Enabled",
    "Tierings": [
      {
        "Days": 90,
        "AccessTier": "ARCHIVE_ACCESS"
      },
      {
        "Days": 180,
        "AccessTier": "DEEP_ARCHIVE_ACCESS"
      }
    ]
  }'

# Analyze storage usage
aws s3api list-bucket-metrics-configurations --bucket my-bucket

# Enable S3 Select for cost optimization
aws s3api put-bucket-metrics-configuration \
// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

Guide	Contents
AWS S3 Storage Optimization	AWS S3 Storage Optimization
Data Compression and Partitioning Strategy	Data Compression and Partitioning Strategy
Terraform Multi-Cloud Storage Configuration	Terraform Multi-Cloud Storage Configuration
Data Lake Partitioning Strategy	Data Lake Partitioning Strategy

Best Practices

✅ DO

Use Parquet or ORC formats for analytics
Implement tiered storage strategy
Partition data by time and queryable dimensions
Enable versioning for critical data
Use compression (gzip, snappy, brotli)
Monitor storage costs regularly
Implement data lifecycle policies
Archive infrequently accessed data

❌ DON'T

Store uncompressed data
Keep raw logs long-term
Ignore storage optimization
Use only hot storage tier
Store duplicate data
Forget to delete old test data

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 Storage Optimization AI skill do?

Optimize cloud storage across AWS S3, Azure Blob, and GCP Cloud Storage with compression, partitioning, lifecycle policies, and cost management.

Why use Cloud Storage Optimization on TypingMind?

Because you install it once and use it with any model. Cloud Storage Optimization 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 Storage Optimization in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/cloud-storage-optimization. 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 Storage Optimization?

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 Storage Optimization?

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

Is the Cloud Storage Optimization 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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Cloud Storage Optimization

Overview