deploying-on-aws

deploying-on-aws is a skill for Claude Code from ancoleman/ai-design-components. It costs 45 tokens per session (4,881 once invoked), scanned A, original, MIT.

A guide to choosing and using Amazon Web Services, a cloud platform with services for computing, storage, databases, networking, and security.

In plain words
What is it for?
Use it to select compute, database, networking, serverless, or container services and to apply AWS Well-Architected design principles.
Why use it?
It helps match an application's needs to AWS services and design choices while considering cost, performance, reliability, and security.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the cloud-provider-skills plugin — 3 skills shipped together

Good fit Use it to select compute, database, networking, serverless, or container services and to apply AWS Well-Architected design principles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/ancoleman/ai-design-components/deploying-on-aws
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add ancoleman/ai-design-components --skill deploying-on-aws
Clone the repo
git clone --depth 1 https://github.com/ancoleman/ai-design-components

Made for: Claude Code.

Or install cloud-provider-skills, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for deploying-on-aws

README.md
[![agentmods](https://agentmods.dev/badge/skills/ancoleman/ai-design-components/deploying-on-aws.svg)](https://agentmods.dev/skills/ancoleman/ai-design-components/deploying-on-aws)
Your own site
<a href="https://agentmods.dev/skills/ancoleman/ai-design-components/deploying-on-aws"><img src="https://agentmods.dev/badge/skills/ancoleman/ai-design-components/deploying-on-aws.svg" alt="Measured on agentmods" height="20"></a>
Per session 45 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,881 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00045 $0.04881
Opus 5 $0.00023 $0.02440
Sonnet 5 $0.00009 $0.00976
Haiku 4.5 $0.00005 $0.00488

Measured 8d ago against content hash 8a478f330ce7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

deploying-on-aws scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/deploying-on-aws/SKILL.md · 592 lines

How it starts

The opening of the file, as written. The whole thing — 592 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AWS Patterns

Purpose

This skill provides decision frameworks and implementation patterns for Amazon Web Services. Navigate AWS's 200+ services through proven selection criteria, architectural patterns, and Well-Architected Framework principles. Focus on practical service selection, cost-aware design, and modern 2025 patterns including Lambda SnapStart, EventBridge Pipes, and S3 Express One Zone.

Use this skill when designing AWS solutions, selecting services for specific workloads, implementing serverless or container architectures, or optimizing existing AWS infrastructure for cost, performance, and reliability.

When to Use This Skill

Invoke this skill when:

  • Choosing between Lambda, Fargate, ECS, EKS, or EC2 for compute workloads
  • Selecting database services (RDS, Aurora, DynamoDB) based on access patterns
  • Designing VPC architecture for multi-tier applications
  • Implementing serverless patterns with API Gateway and Lambda
  • Building container-based microservices on ECS or EKS
  • Applying AWS Well-Architected Framework to designs
  • Optimizing AWS costs while maintaining performance
  • Implementing security best practices (IAM, KMS, encryption)

Core Service Selection Frameworks

Compute Service Selection

Decision Flow:

Execution Duration:
  <15 minutes → Evaluate Lambda
  >15 minutes → Evaluate containers or VMs

Event-Driven/Scheduled:
  YES → Lambda (serverless)
  NO → Consider traffic patterns

Containerized:
  YES → Need Kubernetes?
    YES → EKS
    NO → ECS (Fargate or EC2)
  NO → Evaluate EC2 or containerize first

Special Requirements:
  GPU/Windows/BYOL licensing → EC2
  Predictable high traffic → EC2 or ECS on EC2 (cost optimization)
  Variable traffic → Lambda or Fargate

Quick Reference:

Workload Primary Choice Cost Model Key Benefit
API Backend Lambda + API Gateway Pay per request Auto-scale, no servers
Microservices ECS on Fargate Pay for runtime Simple operations
Kubernetes Apps EKS $73/mo + compute Portability, ecosystem
Batch Jobs Lambda or Fargate Spot Request/spot pricing Cost efficiency
Long-Running EC2 Reserved Instances 30-60% savings Predictable cost

Read the full file on GitHub · 592 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 592 lines · 45 tokens per session scan A 8a478f330ce7

Subscribe to this mod's changes

deploying-on-aws is a skill published in the GitHub repository ancoleman/ai-design-components (519 stars, last pushed 9mo ago), licensed MIT. It adds 45 tokens to every session and 4,881 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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