Prompt Library For Startups
AWSOfficialPublished by AWS
- Skill
- Tool integration
- Cloud and DevOps
- Apache-2.0
- Low risk
AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
The AWS Startups Prompt & Agent Library provides a searchable collection of expert-designed prompts and operational agents tailored for AWS environments. It is designed to be used directly within AI coding assistants to help founders and developers scaffold projects, evaluate security, manage costs, and automate infrastructure tasks. The library includes both copy-paste system prompts for immediate use and guidance on installing specialized operational agents for tasks like multi-account management and service quota monitoring.
What it does
- Provides a searchable index of AWS-curated prompts for AI coding tools.
- Offers installable agents for multi-account, cost, and quota management.
- Surfaces verbatim system prompts for infrastructure and development tasks.
- Integrates with AI coding agents to execute, adapt, or copy infrastructure prompts.
- Provides guidance on AWS foundation setup and security baselines.
- Routes complex migration requests to specialized sibling skills.
When to use it
- When you need a proven prompt to scaffold an AWS-based MVP or RAG chatbot.
- When you want to perform a security baseline or Well-Architected review.
- When you need to manage AWS service quotas or detect cost anomalies.
- When you are looking for an installable agent to handle multi-account transitions.
- When you need to identify the right AWS database for your specific use case.
Advantages
- Reduces planning time by using AWS-curated best practices.
- Ensures consistency by using engineered system prompts.
- Provides a direct path to execute infrastructure tasks within your AI agent.
- Offers clear separation between copy-paste prompts and installable operational agents.
- Maintains a structured, searchable library for rapid development.
Usage examples
- “Give me a prompt for an MVP.”
- The agent will reference the awsome-mvp-builder.md file and offer to run, adapt, or copy the prompt for your project.
- “How do I prevent bill shock on AWS?”
- The agent will recommend the AWS Bill Shock Preventer downloadable agent and provide the link to its repository.
- “I need to set up a RAG chatbot on Bedrock.”
- The agent will surface the rag-chatbot-with-claude.md prompt and offer to execute it against your current setup.
- “How do I get a GPU instance quota raised?”
- The agent will provide the gpu-instance-quota-assistant.md prompt and offer to help you adapt it for your specific region and instance type.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/aws/prompt-library-for-startups/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip prompt-library-for-startups.zip -d .agents/skills
Documentation by AWS
AWS Startups Prompt & Agent Library
Searchable index of AWS-curated prompts for AI coding tools (Kiro, Claude Code, Cursor, etc.) plus downloadable installable agents. Content is verbatim from aws.amazon.com/startups/prompt-library.
Last updated: 2026-09-24
Where to start
Open references/prompt-library.md — it's the index. Filter by the Keywords column (e.g., RAG, Security & Compliance, Cost Optimization, EKS, Beginner, Bedrock), then open the linked detail file under references/prompt-library/<slug>.md. Each detail file carries the full verbatim System Prompt plus a How to use? section where available.
The index has three sections:
Prompts — searchable index — copy-paste prompts.
Downloadable agents — installable agents that clone from a GitHub repo.
Frequently Asked Questions — guidance on writing a good prompt, costs, safety, no-technical-background usage, monitoring.
Handing over a prompt — match the host context
You ARE already inside an AI coding agent (Claude Code / Kiro / Cursor / etc.). Don't tell the user to "paste this into your AI tool" — you ARE the AI tool.
When the user asks for a prompt:
Read the index in
references/prompt-library.md, filter by keyword, identify the matching slug.Open
references/prompt-library/<slug>.mdand read the full System Prompt.Surface the prompt to the user as a reference from the AWS Startups Prompt Library, then offer them three paths:
"Here's the AWS Startups reference prompt for
<task>. I can: - run it against your setup (I'll show you each command before executing), - adapt it to your specific requirements (different region, services, language, etc.), or - you can copy it as a starting point.How would you like to proceed?"
Don't assume intent. Wait for the user's call (execute / adapt / copy) before acting.
Downloadable agents — different surface from prompts
The Downloadable agents section of references/prompt-library.md lists installable agents, not copy-paste prompts:
AWS Multi-Account Transition Advisor — guides single-account → multi-account (AWS Organizations + OUs).
AWS Bill Shock Preventer — proactive cost-spike detection and alerting.
AWS Service Quota Agent — auditing and requesting quota increases.
Bedrock Model Availability Agent — finds Amazon Bedrock model availability across AWS regions.
AWS DB Advisor — selecting and operating the right AWS database (selection, HA/DR, cost, migrations).
When the user's intent matches one of these — "set up multi-account", "prevent bill shock", "audit service quotas", "which Bedrock model / region", "which database should I use" — recommend the matching agent by title and use-case, then hand over the GitHub repo / install link from the index file. Make clear it installs separately from this skill into the user's AI coding agent.
For migration intent, route to the matching migration skill in this plugin: gcp-to-aws ("GCP to AWS", move off Google Cloud), heroku-to-aws ("migrate off Heroku"), llm-to-bedrock ("move off OpenAI/Gemini to Bedrock" — SDK rewrite), or agent-advisor (agent runtime / architecture on AWS).
Routing hints — common queries → which entry
| Query | Entry |
|---|---|
| "Give me a prompt for an MVP" | awsome-mvp-builder.md |
| "Prompt for a RAG chatbot on Bedrock" | rag-chatbot-with-claude.md |
| "How do I set up AWS for the first time?" | day-one-aws-foundation-setup.md |
| "Security baseline / production-readiness audit" | security-baseline-evaluation.md, aws-security-baseline-terraform-deployment-kit.md |
| "How do I get a GPU instance quota raised?" | gpu-instance-quota-assistant.md |
| "Bedrock model quota / TPM / RPM" | bedrock-quota-manager.md |
| "Cost anomaly / spend monitoring" | cost-anomaly-detection.md |
| "EKS with cost-optimized Spot instances" | cost-optimized-eks-with-spot-instances.md |
| "Open-source LLM inference" | open-source-llm-inference.md |
| "Well-Architected Review" | well-architecture-review.md |
| "Multi-region security assessment" | multi-region-assessment.md |
| "Migrate Elasticsearch to OpenSearch" | elasticsearch-to-opensearch-migration.md |
| "OpenAPI to MCP / AgentCore Gateway" | openapi-to-agentcore-gateway-deployment.md |
| "Deploy a GitHub repo to AWS" | deploy-github-repo.md |
| "Help me migrate workloads to AWS" | gcp-to-aws / heroku-to-aws / llm-to-bedrock skills (siblings in this plugin) |
| "Set up multi-account on AWS Organizations" | Downloadable: Multi-Account Transition Advisor |
| "Stop bill shock / detect cost spikes proactively" | Downloadable: AWS Bill Shock Preventer |
| "Manage / request service quotas" | Downloadable: Service Quota Agent |
| "Which Bedrock model is available in which region" | Downloadable: Bedrock Model Availability Agent |
| "Which AWS database should I use" | Downloadable: AWS DB Advisor |
For anything else, filter references/prompt-library.md by keyword.
Companion skills — when to defer
This skill is prompts and installable agents only. Two sibling skills cover adjacent jobs:
knowledge-base-for-startups— AWS Startups knowledge base (Activate FAQ, credits, programs, partner offers, sample architectures, hundreds of learn articles). When the user asks factual questions about AWS Activate, eligibility, accelerators, or wants a learn article on a topic, hand off to that skill.start-building-for-startups— interactive discovery + implementation workflow that gathers requirements via picker questions and then writes code directly. When the user wants to build or scaffold an app, hand off to that skill — it may consult this skill mid-flow to source the right starter prompt.
Boundary cases — invoke both. Example: "how do I start with RAG on Bedrock?" → this skill for the starter prompt (rag-chatbot-with-claude.md) AND knowledge-base-for-startups for the deeper learn article on RAG architecture patterns.
Answer style
MUST read the detail file before quoting a System Prompt. The full prompt only lives in the detail file; opening it is non-negotiable. Do not quote a System Prompt from memory or from the index alone.
MUST quote the System Prompt verbatim. The wording is engineered — do not paraphrase, summarize, or shorten the prompt itself. You may summarize what the prompt does in your own words; the prompt content stays exact.
MUST cite
source_url. Every file's frontmatter carries one — that's the canonical URL to include in your answer. Never construct or guess a URL.MUST NOT tell the user to paste the prompt elsewhere. You ARE the AI coding agent (see "Handing over a prompt" above). Surface the prompt as a reference and offer to execute / adapt / copy — let the user decide.
MUST surface the validation disclaimer when the user is about to execute a prompt that touches infrastructure, billing, or security. From the source page: "You are solely responsible for reviewing and validating any outputs generated from your use of the prompts."
Context loading rule
Open references/prompt-library.md first, filter by keyword, then open at most one prompt detail file per question. MUST NOT speculatively load multiple detail files. If a query plausibly matches several entries, list the candidates by title from the index and ask the user which one they want before opening a detail file.
Scope notes
This skill cannot:
Answer factual questions about AWS Activate, credits, programs, or partner offers — defer to
knowledge-base-for-startups.Provide prompts that are not in the bundled
references/prompt-library/tree. If no matching prompt exists, say so plainly rather than improvising one.Install the downloadable agents on the user's behalf. They install separately from this skill into the user's AI coding agent — surface the GitHub repo / install link from the index file.
Override the source-page disclaimer. The user remains responsible for reviewing and validating outputs from any executed prompt.
Freshness check — surface after every answer
After answering the user's question, compare the Last updated: date at the top of this file against today's date. If the gap is more than 6 months, append a short note to your reply suggesting the user refresh the skill:
"This skill's content was last refreshed on
<Last updated date>, more than 6 months ago — some prompts and downloadable agents may have been added, removed, or revised. To pull the latest content, run:
npx skills update prompt-library-for-startups— update the installed copy to the latest versionThen restart your AI agent so the new content is picked up."
Do not show this note when the skill is fresh (≤6 months). Do not repeat it within a single conversation; once is enough.
Files
- ATTRIBUTION.mdAdded by AutoGineer935 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md11.4 KiB
- references/prompt-library.md27.2 KiB
- references/prompt-library/ai-support-ticket-triage-and-routing-assistant.md5.3 KiB
- references/prompt-library/aws-architecture-assessment-with-mcp-integration.md22.7 KiB
- references/prompt-library/aws-cdk-typescript-pipeline-generator.md3.1 KiB
- references/prompt-library/aws-ecs-express-deployment-assistant.md4.5 KiB
- references/prompt-library/aws-guardduty.md4.1 KiB
- references/prompt-library/aws-security-baseline-terraform-deployment-kit.md3.8 KiB
- references/prompt-library/awsome-mvp-builder.md5.3 KiB
- references/prompt-library/bedrock-quota-manager.md24.2 KiB
- references/prompt-library/container-orchestration.md3.7 KiB
- references/prompt-library/cost-anomaly-detection.md21.3 KiB
- references/prompt-library/cost-optimized-eks-with-spot-instances.md2.4 KiB
- references/prompt-library/day-one-aws-foundation-setup.md5.4 KiB
- references/prompt-library/deploy-github-repo.md3.8 KiB
- references/prompt-library/elasticsearch-to-opensearch-migration.md13.4 KiB
- references/prompt-library/full-aws-deployment-agent.md4.6 KiB
- references/prompt-library/gpu-instance-quota-assistant.md16.5 KiB
- references/prompt-library/kiro-project-init.md23.1 KiB
- references/prompt-library/local-code-to-cloud.md3.4 KiB
- references/prompt-library/multi-region-assessment.md49.3 KiB
- references/prompt-library/mvsp.md12.9 KiB
- references/prompt-library/open-source-llm-inference.md10.7 KiB
- references/prompt-library/openapi-to-agentcore-gateway-deployment.md10.7 KiB
- references/prompt-library/opensearch-cluster-operational-review.md3.1 KiB
- references/prompt-library/rag-chatbot-with-claude.md2.9 KiB
- references/prompt-library/resiliency-baseline-evaluation.md28.9 KiB
- references/prompt-library/security-baseline-evaluation.md29.4 KiB
- references/prompt-library/startup-landing-page-deployment.md4.0 KiB
- references/prompt-library/startup-pitch.md2.6 KiB
- references/prompt-library/well-architecture-review.md4.7 KiB
references/prompt-library/cost-optimized-eks-with-spot-instances.md
source_url: https://aws.amazon.com/startups/prompt-library/cost-optimized-eks-with-spot-instances title: "Karpenter + KEDA: Cost-Optimized EKS with Spot Instances" tags: ["Cost Optimization", "Deployment", "Advanced", "EKS", "EC2"]
Karpenter + KEDA: Cost-Optimized EKS with Spot Instances
Deploy production-ready EKS with Karpenter auto-scaling, KEDA pod management, and Spot instance prioritization. Includes Bottlerocket OS, encryption, and multi-AZ high availability—optimized for cost.
System Prompt
Deploy Cost-Optimized Karpenter on EKS with Bottlerocket, Spot Instances, and KEDA
Act as a DevOps engineer and help me deploy Karpenter on an EKS cluster with the following requirements:
Cluster Elasticity & Scaling:
Configure Karpenter to make the cluster as elastic as possible Set up KEDA to manage pod scaling based on CPU usage Karpenter should handle node provisioning based on pod demands Node Provisioning Strategy:
Provision general-purpose nodes only Prioritize Spot instances and check Spot availability first Fall back to On-Demand instances only when Spot is unavailable Enable consolidation for cost optimization Security & Hardening:
Use Bottlerocket OS for all nodes Disable SSH access completely Enable EBS volume encryption High Availability:
Deploy across multiple availability zones to maximize Spot availability Implementation:
Use Terraform with the official EKS module to provision the EKS cluster infrastructure Use kubectl to connect to the Kubernetes API for deployment and configuration (or a Kubernetes MCP server, if you already have one configured — this plugin does not ship one) Provide all necessary Terraform configurations for EKS cluster setup Provide all necessary Kubernetes manifests, Karpenter NodePool/EC2NodeClass configurations, and KEDA ScaledObject definitions Include any required IAM roles, policies, and service account configurations Please create a complete, production-ready setup with all configuration files needed.
Error Management:
Use kubectl to connect to the Kubernetes API and verify if the EKS cluster exists If the cluster doesn't exist, ask me if I want to create it and provide the creation steps using Terraform Check the Kubernetes cluster version and verify compatibility with Karpenter Recommend the appropriate Karpenter version based on the cluster version If there's a version incompatibility, suggest either upgrading the cluster or using a compatible Karpenter version
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.
Needs: Needs Node.js
Security
What our scanner noticed· Low risk
- Instructions that use the network
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Attribution and licence
- Published by
- AWS
- Publisher
- AWS (Official)
- Source
- aws/agent-toolkit-for-aws · plugins/aws-startup-advisor/skills/prompt-library-for-startups · commit 0a218f8
- Licence
- Apache License 2.0 (redistribution allowed)
- LICENSE (added by AutoGineer from LICENSE)
- NOTICE (added by AutoGineer from NOTICE)
- ATTRIBUTION.md (written by AutoGineer)
- Synced
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