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Cloud Cost Management

Community
aj-geddes
cloud-cost-management

Optimize and manage cloud costs across AWS, Azure, and GCP using reserved instances, spot pricing, and cost monitoring tools.

Overview

Publisheraj-geddes
Repositoryuseful-ai-prompts
Skill namecloud-cost-management
Stars
340
Forks
55
Bundled files
7
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.

  • 7 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 Cost Management 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-cost-management .claude/skills/cloud-cost-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cloud Cost Management 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 Cost Management 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 Cost Management 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 Cost Management

Table of Contents

Overview

Cloud cost management involves monitoring, analyzing, and optimizing cloud spending. Implement strategies using reserved instances, spot pricing, proper sizing, and cost allocation to maximize ROI and prevent budget overruns.

When to Use

  • Reducing cloud infrastructure costs
  • Optimizing compute spending
  • Managing database costs
  • Storage optimization
  • Data transfer cost reduction
  • Reserved capacity planning
  • Chargeback and cost allocation
  • Budget forecasting and alerts

Quick Start

Minimal working example:

bash
# Enable Cost Explorer
aws ce get-cost-and-usage \
  --time-period Start=2024-01-01,End=2024-01-31 \
  --granularity MONTHLY \
  --metrics "UnblendedCost" \
  --group-by Type=DIMENSION,Key=SERVICE

# List EC2 instances for right-sizing
aws ec2 describe-instances \
  --query 'Reservations[*].Instances[*].[InstanceId,InstanceType,State.Name,LaunchTime,Tag]' \
  --output table

# Find unattached EBS volumes
aws ec2 describe-volumes \
  --filters Name=status,Values=available \
  --query 'Volumes[*].[VolumeId,Size,State,CreateTime]'

# Identify unattached Elastic IPs
aws ec2 describe-addresses \
  --query 'Addresses[?AssociationId==null]'

# Get RDS instance costs
aws rds describe-db-instances \
  --query 'DBInstances[*].[DBInstanceIdentifier,DBInstanceClass,StorageType,AllocatedStorage]'

// ... (see reference guides for full implementation)

Reference Guides

Detailed implementations in the references/ directory:

GuideContents
AWS Cost Optimization with AWS CLIAWS Cost Optimization with AWS CLI
Terraform Cost Management ConfigurationTerraform Cost Management Configuration
Azure Cost ManagementAzure Cost Management
GCP Cost OptimizationGCP Cost Optimization
Cost Monitoring DashboardCost Monitoring Dashboard

Best Practices

✅ DO

  • Use Reserved Instances for stable workloads
  • Implement Savings Plans for flexibility
  • Right-size instances based on metrics
  • Use Spot Instances for fault-tolerant workloads
  • Delete unused resources regularly
  • Enable detailed billing and cost allocation
  • Monitor costs with CloudWatch/Cost Explorer
  • Set budget alerts
  • Review monthly cost reports

❌ DON'T

  • Leave unused resources running
  • Ignore cost optimization recommendations
  • Use on-demand for predictable workloads
  • Skip tagging resources
  • Ignore data transfer costs
  • Forget about storage lifecycle policies

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 Cost Management AI skill do?

Optimize and manage cloud costs across AWS, Azure, and GCP using reserved instances, spot pricing, and cost monitoring tools.

Why use Cloud Cost Management on TypingMind?

Because you install it once and use it with any model. Cloud Cost Management 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 Cost Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aj-geddes/useful-ai-prompts/tree/main/skills/cloud-cost-management. 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 Cost Management?

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 Cost Management?

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

Is the Cloud Cost Management 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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