| name | prompt-library-for-startups |
| description | 29+ AWS-curated copy-paste prompts for AI coding agents (MVP scaffolding, RAG chatbot with Claude on Bedrock, security baseline evaluation, cost anomaly detection, GPU quota requests, EKS deployment, Well-Architected review, etc.) plus 4 downloadable installable agents (AWS Migration Agent, Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent). Use when the user asks for a prompt to do X on AWS, wants an installable agent for migration / multi-account / cost monitoring / quota management, or asks how to use AWS prompts. Do not use for: factual AWS Activate / programs / credits questions, learn articles, sample architectures, or for prompts that are not in the bundled `references/prompt-library/` tree. |
AWS Startups Prompt & Agent Library
Searchable index of 29+ AWS-curated prompts for AI coding tools (Kiro, Claude Code, Cursor, etc.) plus 4 downloadable installable agents. Content is verbatim from aws.amazon.com/startups/prompt-library.
Last updated: 2026-05-12
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 (29+ entries) — copy-paste prompts.
- Downloadable agents (4 entries) — 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>.md and 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:
- execute it as-is against your setup,
- 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 4 entries in the Downloadable agents section of references/prompt-library.md are installable agents, not copy-paste prompts:
- AWS Migration Agent — Terraform-based discovery + migration of GCP / OpenAI / Gemini workloads to AWS. Repo: https://github.com/aws-samples/sample-agent-skills-for-aws-migration
- 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.
When the user's intent matches one of these — "help me migrate to AWS", "set up multi-account", "prevent bill shock", "audit service quotas" — 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.
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" | Downloadable: AWS Migration Agent |
| "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 |
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, 277+ 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 version
Then 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.
