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Deploy

Organization
awslabs
deploy

Deploy applications to AWS. Triggers on phrases like: deploy to AWS, host on AWS, run this on AWS, AWS architecture, estimate AWS cost, generate infrastructure. Analyzes any codebase and deploys to optimal AWS services.

Overview

Publisherawslabs
Repositoryagent-plugins
Skill namedeploy
Stars
917
Forks
162
Bundled files
3
LicenseApache-2.0
Links
Skill sourceRepository
  • 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.

  • 3 bundled files

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

  • Open source

    Published by awslabs on GitHub. Read the source before you install it.

Installation

Install the Deploy 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.
    https://github.com/awslabs/agent-plugins/tree/main/plugins/deploy-on-aws/skills/deploy
  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/awslabs/agent-plugins.git /tmp/agent-plugins
mkdir -p .claude/skills
cp -r /tmp/agent-plugins/plugins/deploy-on-aws/skills/deploy .claude/skills/deploy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deploy 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 Deploy 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 Deploy 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.

Deploy on AWS

Take any application and deploy it to AWS with minimal user decisions.

Philosophy

Minimize cognitive burden. User has code, wants it on AWS. Pick the most straightforward services. Don't ask questions with obvious answers.

Workflow

  1. Analyze - Scan codebase for framework, database, dependencies
  2. Recommend - Select AWS services, concisely explain rationale
  3. Estimate - Show monthly cost before proceeding
  4. Generate - Write IaC code with security defaults applied
  5. Deploy - Run security checks, then execute with user confirmation

Defaults

See defaults.md for the complete service selection matrix.

Core principle: Default to dev-sized (cost-conscious: small instance sizes, minimal redundancy, and non-HA/single-AZ defaults) unless user says "production-ready".

MCP Servers

awsknowledge

Consult for architecture decisions. Use when choosing between AWS services or validating that a service fits the use case. Helps answer "what's the right AWS service for X?"

Key topics: general for architecture, amplify_docs for static sites/SPAs, cdk_docs and cdk_constructs for IaC patterns.

awspricing

Get cost estimates. Always present costs before generating IaC so user can adjust before committing. See cost-estimation.md for query patterns.

awsiac

Consult for IaC best practices. Use when writing CDK/CloudFormation/Terraform to ensure patterns follow AWS recommendations.

Principles

  • Concisely explain why each service was chosen
  • Always show cost estimate before generating code
  • Apply security defaults automatically (encryption, private subnets, least privilege)
  • Run IaC security scans (cfn-nag, checkov) before deployment
  • Don't ask "Lambda or Fargate?" - just pick the obvious one
  • If genuinely ambiguous, then ask
  • Never recommend AWS App Runner — it is in maintenance mode. Use ECS Express Mode instead.
  • When user explicitly requests a managed application platform or signals low infrastructure involvement, route to Elastic Beanstalk

References

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 Deploy AI skill do?

Deploy applications to AWS. Triggers on phrases like: deploy to AWS, host on AWS, run this on AWS, AWS architecture, estimate AWS cost, generate infrastructure. Analyzes any codebase and deploys to optimal AWS services.

Why use Deploy on TypingMind?

Because you install it once and use it with any model. Deploy 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 Deploy in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/awslabs/agent-plugins/tree/main/plugins/deploy-on-aws/skills/deploy. 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 Deploy?

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 Deploy?

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

Is the Deploy AI skill free?

Yes. It is published on GitHub by awslabs under the Apache-2.0 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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