Aws Compute

OrganizationPopular

aws

aws-compute

Provisions, scales, and operates Amazon EC2 virtual-machine workloads: instance-type selection (Graviton/Arm64, burstable T credits, GPU, instance store vs EBS), launch templates, Auto Scaling groups (scaling policies, instance refresh, mixed instances, Spot, warm pools, lifecycle hooks), IMDSv2, placement groups, Elastic IPs, AMI lifecycle, and Systems Manager fleet operations (Session Manager, Run Command, Patch Manager). Applies to EC2 instance and fleet questions, InsufficientInstanceCapacity, CPU-credit/surplus charges, IMDSv2 401s, instances stuck in Pending:Wait, ASG not replacing unhealthy instances, status-check failures, SSH refused/timed out, or instances missing as SSM managed nodes. For a single secure instance launch, the launching-ec2-instance-with-best-practices skill is more appropriate; for instance profiles, see setting-up-ec2-instance-profiles; for Image Builder, see amazon-ec2-image-builder. Does NOT cover Lambda, ECS/Fargate, EKS, VPC/ALB/NLB design, or IAM policy authoring.

Overview

Publisher	aws
Repository	`agent-toolkit-for-aws`
Skill name	`aws-compute`
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 Compute 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-compute

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-compute .claude/skills/aws-compute

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

Use it in TypingMind

Enable Aws Compute 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 Compute 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 Compute 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.

Amazon EC2 Compute

Best experience with the AWS MCP server; also works with the AWS CLI alone — no hard dependency on either.

Critical Warnings

Launch configurations are deprecated and do not support current EC2 instance types; new accounts cannot create them. Use launch templates for every new Auto Scaling group. See auto-scaling.md.

ASGs ignore ELB health checks by default: An Auto Scaling group only uses EC2 status checks unless you set --health-check-type ELB. Without it, instances failing the load balancer's health check stay in service forever. See auto-scaling.md.

IMDSv2 hop limit breaks containers: the default HttpPutResponseHopLimit of 1 makes the IMDSv2 token PUT response fail to reach a containerized process (the extra hop exceeds the response TTL), so the token request times out. Set HttpPutResponseHopLimit=2 for bridge/awsvpc container workloads. (If IMDSv2 is required, a subsequent tokenless GET returns 401; if optional, it silently falls back to IMDSv1.) See provisioning.md.

T3/T3a/T4g default to unlimited mode: Unlike T2 (standard), these burst without throttling but bill surplus CPU credits when 24h-average CPU exceeds baseline — a silent cost leak. See instance-selection.md.

Instance store is ephemeral: Data on instance store volumes is lost on stop, hibernate, terminate, instance-type change, and host failure — it survives only a reboot. Put anything durable on EBS/EFS/S3. See instance-selection.md.

Which do you need?

If you're deciding...	Guidance
Instance family / size / Graviton / GPU / burstable	instance-selection.md — start with the workload→family table
How to define instances once and reuse (launch template)	provisioning.md
How to run many instances that scale automatically	auto-scaling.md
How to access/patch/manage instances without SSH keys	systems-manager.md

Quick Navigation

You want to...	Go to
Pick an instance type, Graviton vs x86, burstable credits, GPU, instance store vs EBS	instance-selection.md
Create a launch template, user data, key pairs, IMDSv2, placement groups, Elastic IPs	provisioning.md
Set up or fix an Auto Scaling group, scaling policies, instance refresh, Spot, lifecycle hooks	auto-scaling.md
Get SSH-less access, patch a fleet, or fix an instance not showing as a managed node	systems-manager.md
Create, share, or retire (deprecate/disable/deregister) an AMI	ami-management.md
Fix something broken (can't connect, status-check fail, capacity error, stuck instances)	troubleshooting.md

Common Workflows

"Stand up an autoscaling web fleet" → Create a launch template (AMI, type, IMDSv2), then an ASG referencing it with --health-check-type ELB and a target-tracking policy, see auto-scaling.md. For the public entry point, secure the load balancer (TLS/ACM, WAF, security response headers) per the Security Considerations below and the load-balancer notes in auto-scaling.md — the load-balancer build itself belongs to aws-networking.

"Roll out a new AMI to my fleet" → New launch template version → instance refresh; pin a numeric launch-template version so rollback works, see auto-scaling.md.

"Connect to a private instance without a bastion" → Give the instance SSM permissions (an instance profile with AmazonSSMManagedInstanceCore, or account-level DHMC) plus a network path, then use Session Manager, see systems-manager.md.

"Cut EC2 cost" → Right-size (burstable vs fixed-performance), Graviton where the app supports Arm64, Spot with price-capacity-optimized for fault-tolerant fleets, release idle Elastic IPs, see instance-selection.md.

Troubleshooting

Symptom	Likely cause	Quick fix
SSH "Connection timed out"	Network path (SG/NACL/route/no public IP)	Open TCP 22 from your IP; check route to IGW; verify public IP — see troubleshooting.md
SSH "Connection refused"	Host: sshd down or still booting	Wait for boot; check sshd/port via Session Manager or serial console
`InsufficientInstanceCapacity`	AWS lacks capacity of that type in the AZ (NOT a quota)	Try another AZ / instance type / retry; don't request a quota increase
`InstanceLimitExceeded`	vCPU quota reached (this IS a quota)	Request a Service Quotas increase for the instance family
ASG never replaces LB-unhealthy instances	Health check type still EC2	Set `--health-check-type ELB`
Instances stuck in `Pending:Wait`, terminated after ~1h	Lifecycle hook never completed (heartbeat 3600s, default ABANDON)	Call `complete-lifecycle-action` CONTINUE, or set DefaultResult CONTINUE
System status check failed	AWS host/hardware	Stop/start to migrate to new hardware (reboot won't)
Instance status check failed	Instance OS/network config	Reboot or fix the OS/network config

Full tables and more errors in troubleshooting.md.

Security Considerations

Enforce IMDSv2 (HttpTokens=required) on launch templates to block SSRF-based credential theft; set the account-level default per Region (applies to new launches only).
Prefer Session Manager over inbound SSH — no open port 22, no key management, and a CloudTrail record of session API calls; enable Session Manager session logging to CloudWatch Logs/S3 (off by default) to capture the in-session commands themselves — see systems-manager.md.
Use instance profiles, never embedded credentials; scope the role to least privilege.
Encrypt EBS/AMIs; to share an encrypted AMI cross-account, re-encrypt under a customer-managed KMS key (the default aws/ebs key can't be shared).
Enable CloudTrail in all Regions to audit EC2/ASG/SSM API activity, and alarm on sensitive actions (security-group changes, RunInstances/TerminateInstances from unexpected principals) so unauthorized changes surface.
For public-facing web fleets, encrypt traffic in transit with an ACM certificate on the load balancer's HTTPS listener and add AWS WAF for defense in depth against common web exploits — the load-balancer/WAF setup itself lives in aws-networking.
For hardening beyond this guidance, see AWS EC2 security best practices and CIS Benchmarks for the guest OS.

Not Covered By This Skill

Launching a single hardened instance with best-practice defaults → use the launching-ec2-instance-with-best-practices skill
Creating IAM roles / instance profiles for EC2 → use the setting-up-ec2-instance-profiles skill
Building AMIs with an Image Builder pipeline → use the amazon-ec2-image-builder skill
Lambda / serverless → aws-serverless; ECS/Fargate → aws-containers; EKS/Kubernetes → kubernetes
VPC, subnets, ALB/NLB, endpoints → aws-networking or built-in knowledge
IAM policy logic and CloudWatch dashboards/agent setup → aws-iam, aws-observability

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 Compute AI skill do?

Why use Aws Compute on TypingMind?

Because you install it once and use it with any model. Aws Compute 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 Compute 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-compute. 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 Compute?

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 Compute?

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

Is the Aws Compute 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.

View all

Land And Deploy

garrytan

CommunityPopular

Land and deploy workflow. (gstack)

Setup Deploy

Configure deployment settings for /land-and-deploy.

Caveman Compress

Compress a memory file such as CLAUDE.md or a todo list into caveman format to save input tokens, keeping a readable backup. Trigger: /caveman-compress.

Caveman Discover

Find and label every LLM workflow in the repository so Caveman Cloud groups spend by workflow instead of one bucket. Use for "discover workflows" or breaking LLM spend down by workflow.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Amazon EC2 Compute

Critical Warnings

Which do you need?

Quick Navigation

Common Workflows

Troubleshooting

Security Considerations

Not Covered By This Skill

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now