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.
npx skills add ancoleman/ai-design-components --skill deploying-on-awsgit clone --depth 1 https://github.com/ancoleman/ai-design-componentsWrote 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.
[](https://agentmods.dev/skills/ancoleman/ai-design-components/deploying-on-aws)<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/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<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="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00045 | $0.04881 |
| Opus 5.5 | $0.00018 | $0.01952 |
| Sonnet 5.5 | $0.00009 | $0.00976 |
| Haiku 4.5 | $0.00005 | $0.00488 |
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 1mo 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.
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 |
What ships with it
10 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- examples/cloudformation/lambda-api.yaml 16 KB
- outputs.yaml 9.4 KB
- references/compute-services.md 11 KB
- references/container-patterns.md 29 KB
- references/database-services.md 13 KB
- references/networking.md 4.5 KB
- references/security.md 8.4 KB
- references/serverless-patterns.md 24 KB
- references/storage-services.md 9.9 KB
- references/well-architected.md 12 KB
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.
- 1mo ago First seen · 592 lines · 45 tokens per session scan A 8a478f330ce7
deploying-on-aws is a skill published in the GitHub repository ancoleman/ai-design-components (525 stars, last pushed 10mo ago), licensed MIT. It adds 45 tokens to every session and 4,881 once invoked, about $0.0002 per session on Opus 5.5. 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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