Aws Deployment

Q: Why use Aws Deployment on TypingMind?

Because you install it once and use it with any model. Aws Deployment 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.

Q: How do I install Aws Deployment in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-core/skills/aws-deployment. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Aws Deployment?

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.

Q: How many AI models can I use with Aws Deployment?

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

Q: Is the Aws Deployment AI skill free?

Yes. It is published on GitHub by aws under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

Q: 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.

Q: 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.

OrganizationPopular

aws

aws-deployment

Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.

Overview

Publisher	aws
Repository	`agent-toolkit-for-aws`
Skill name	`aws-deployment`
Stars	2.7K
Forks	311
Bundled files	6
License	Apache-2.0
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 aws on GitHub. Read the source before you install it.

Installation

Install the Aws Deployment 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/aws/agent-toolkit-for-aws/tree/main/plugins/aws-core/skills/aws-deployment

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/aws/agent-toolkit-for-aws.git /tmp/agent-toolkit-for-aws
mkdir -p .claude/skills
cp -r /tmp/agent-toolkit-for-aws/plugins/aws-core/skills/aws-deployment .claude/skills/aws-deployment

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

Use it in TypingMind

Enable Aws Deployment 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 Aws Deployment 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 Aws Deployment 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.

AWS Deploy (CI/CD)

Works best with the AWS MCP server for running CLI commands and validating configurations directly. All guidance also works with standard AWS CLI.

Critical Warnings

CodeConnections PENDING trap: Connections created via CLI/CloudFormation remain PENDING indefinitely — MUST complete OAuth in the AWS Console. No API-only path exists.

Cross-account triple requirement: Cross-account deploys need ALL THREE: (1) KMS key policy granting target account (use key ID, not alias), (2) S3 bucket policy for target account, (3) cross-account IAM role with trust policy. Missing any one = cryptic Access Denied.

CodeDeploy ApplicationStop uses PREVIOUS revision: Broken stop scripts in a prior deployment block ALL future deploys. Make stop scripts idempotent (exit 0 if service absent). Unblock with --ignore-application-stop-failures.

CodeBuild VPC without NAT: Builds in VPC subnets without NAT gateway hang at DOWNLOAD_SOURCE silently. Private subnets MUST have NAT gateway or VPC endpoints.

CodeConnections IAM: Use codeconnections: prefix for API calls and IAM policy Actions. Resource ARNs must match exactly — new resources use codeconnections prefix, existing resources may use codestar-connections prefix. Specify both in Resource if you have mixed-age resources.

UseConnection is over-permissive: codeconnections:UseConnection grants access to ALL repositories the connection can reach. MUST specify condition keys (codeconnections:FullRepositoryId, codeconnections:ProviderAction, codeconnections:BranchName) to limit CodeBuild to only the required repository.

How These Services Compose

CodeConnections → CodeBuild → CodeDeploy, orchestrated by CodePipeline.

Layer	Service	Role
Source	CodeConnections	Authenticates to GitHub/GitLab/Bitbucket, delivers code
Packages	CodeArtifact	Private package registry, dependency caching from public registries
Build/Test	CodeBuild	Compiles, tests, packages artifacts
Deploy	CodeDeploy	Deploys to EC2/ECS/Lambda with traffic shifting strategies
Orchestrator	CodePipeline	Chains stages, manages transitions, approval gates

Default: V2 pipeline type with QUEUED execution mode. Use PARALLEL only when executions are fully independent.

Quick Navigation

You want to...	Go to
Create a pipeline (V2, triggers, variables, modes)	codepipeline.md
Connect GitHub/GitLab/Bitbucket source	codeconnections.md
Write buildspec.yml / configure builds	codebuild.md
Set up private package registry for builds	codeartifact.md
Configure deployment strategy (blue/green, canary)	codedeploy.md
Cross-account or cross-region deployment	codepipeline.md
Fix failing pipeline, build, or deployment	troubleshooting.md

Common Workflows

Task	Action	Reference
Pipeline from GitHub to ECS	Create connection → CodeBuild Docker stage → CodeDeploy ECS blue/green	codepipeline, codedeploy
Pipeline stuck at source	Check connection status; if PENDING, complete OAuth in AWS Console	troubleshooting
Build timing out	Check VPC/NAT, increase `timeoutInMinutes`, verify Docker privileged mode	codebuild
Deploy to another account	Configure KMS + S3 bucket policy + cross-account role, add `RoleArn` to action	codepipeline
Roll back failed deployment	Auto-rollback on alarm/failure; manual: `stop-deployment --auto-rollback-enabled`	codedeploy
Lambda canary deployment	CodeBuild packages → CodeDeploy Lambda with canary traffic shifting	codedeploy

Troubleshooting

Error/Symptom	Cause	Fix
`YAML_FILE_ERROR` in CodeBuild	Missing or malformed `runtime-versions` in buildspec (recommended for standard images)	Add `runtime-versions` block in install phase
`file already exists` on CodeDeploy	Redeployment without overwrite config	Set `file_exists_behavior: OVERWRITE`
Pipeline trigger not firing	File path filter checks only first 100 files in diff	Reduce path filter scope or merge smaller
PARALLEL mode wrong revision	Race between event and source action	Use QUEUED mode for sequential consistency
Docker: `Cannot connect to daemon`	Missing privileged mode	Set `privilegedMode: true` AND start dockerd in buildspec
`CODEBUILD_CLONE_REF` permission error	CodeBuild role missing UseConnection	Add `codeconnections:UseConnection` to CodeBuild service role
Deployment never completes	MinimumHealthyHosts too high for instance count	Ensure healthy threshold < total instances
ECS deployment stuck	Health check failing on new task set	Verify target group health check path/port

Security

MUST store secrets in Secrets Manager or Parameter Store; reference via CodeBuild type: SECRETS_MANAGER — MUST NOT embed in buildspec as PLAINTEXT
MUST use customer-managed KMS keys for cross-account artifact encryption (default encryption does not support cross-account)
SHOULD scope CodeBuild/CodeDeploy service roles to specific resource ARNs; MUST NOT use * for s3:GetObject or kms:Decrypt
MUST use CodeConnections (not personal access tokens) for source connections; OAuth tokens cannot be rotated automatically
See CodePipeline security best practices for comprehensive guidance

Not Covered

Topic	Use instead
CDK Pipelines (`aws-cdk-lib/pipelines`)	`aws-cdk`
`sam deploy` / SAM CLI	`aws-serverless`
ECS service deployment config (circuit breaker, rolling params)	`aws-containers`
GitHub Actions / GitLab CI	Third-party tools, not covered

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 Aws Deployment AI skill do?

Why use Aws Deployment on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/aws/agent-toolkit-for-aws/tree/main/plugins/aws-core/skills/aws-deployment. 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 Aws Deployment?

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 Aws Deployment?

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

Is the Aws Deployment AI skill free?

Yes. It is published on GitHub by aws 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

AWS Deploy (CI/CD)

Critical Warnings

How These Services Compose

Quick Navigation

Common Workflows

Troubleshooting

Security

Not Covered

Bundled files

Frequently asked questions

Related AI Skills

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