prompt-library-for-startups
Provides searchable copy-paste prompts and installable agents for AWS tasks including MVP scaffolding, RAG chatbots with Bedrock, security evaluation, cost…
Identity proven by GitHub's verified organisation badge (aws, awslabs)
- Agents
- Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode, claude.ai and API
- License
- Apache-2.0 (permissive)
- Pin
- df2ab44pinned Oct 9, 2026
- Context cost
- about 2,700 tokenswhen the skill loads
- GitHub stars
- 2,830on aws/agent-toolkit-for-aws
- Scripts
- None found
What it does
“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 downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, Azure to AWS, OpenAI/Gemini to Bedrock), route to the migration skills in this plugin (`gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`). 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.”
Generated summary from the skill's own text
Provides searchable copy-paste prompts and installable agents for AWS tasks including MVP scaffolding, RAG chatbots with Bedrock, security evaluation, cost monitoring, GPU quota requests, and EKS deployment. The skill surfaces prompts from an AWS-curated library and can execute, adapt, or provide them as references without requiring the user to copy them elsewhere.
When to use it
- Building an MVP, RAG chatbot, or Bedrock LLM application on AWS
- Evaluating AWS security baselines, costs, quotas, or Well-Architected fitness
- Setting up multi-account infrastructure, Bedrock model availability lookup, or database selection
When not to
- Asking about AWS Activate programs, credits, or eligibility questions
- Needing AWS learn articles or sample architectures beyond the prompt library
- Seeking prompts not in the bundled references directory
Install
These commands install from the publisher's repository and need no account.
skills CLI
npx skills add aws/agent-toolkit-for-aws --skill prompt-library-for-startupsInstalls from the repository's default branch, which may have changed since the commit we checked.
GitHub CLI 2.90 or later
gh skill install aws/agent-toolkit-for-aws prompt-library-for-startups@df2ab44e485b28358353d827e5ebafbe267cce9fInstalls the commit we checked (df2ab44).
Copy by hand
Download the folder at df2ab44 and put it in .claude/skills/prompt-library-for-startups for Claude Code and in .agents/skills/prompt-library-for-startups for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode.
Claude Code plugin
/plugin install amazon-selling-partner@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Claude Code plugin
/plugin install aws-agents@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Claude Code plugin
/plugin install aws-agents-for-devsecops@claude-plugins-officialThe publisher's plugin in Claude's official marketplace. It may hold more than this skill, and we have not pinned it.
Copy for your agent
A prompt for any coding agent. It installs this skill from GitHub at the pinned commit, copies the files as they are, and runs nothing unless you ask.
Prompt
Install the agent skill "prompt-library-for-startups" by Amazon (AWS). Source, pinned to commit df2ab44e485b28358353d827e5ebafbe267cce9f: https://github.com/aws/agent-toolkit-for-aws/tree/df2ab44e485b28358353d827e5ebafbe267cce9f/plugins/aws-startup-advisor/skills/prompt-library-for-startups 1. Download that folder at exactly this commit. Do not use the default branch. 2. Copy every file unchanged, keeping the folder structure, into .claude/skills/prompt-library-for-startups/ for Claude Code and .agents/skills/prompt-library-for-startups/ for Codex, Cursor, Gemini CLI, GitHub Copilot and OpenCode. Create the folders if they do not exist. 3. Do not edit the files, and do not run any script in the folder unless I ask you to. 4. When you are done, list the files you copied and where you put them. Listing and checks: https://www.agentnative.dev/skills/amazon-aws/prompt-library-for-startups-agent-toolkit-for-aws
SKILL.md at the pin
--- name: prompt-library-for-startups description: "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 downloadable installable agents (Multi-Account Transition Advisor, Bill Shock Preventer, Service Quota Agent, Bedrock Model Availability Agent, AWS DB Advisor). Use when the user asks for a prompt to do X on AWS, wants an installable agent for multi-account / cost monitoring / quota management / Bedrock model availability / database selection, or asks how to use AWS prompts. For migration intent (GCP to AWS, Azure to AWS, OpenAI/Gemini to Bedrock), route to the migration skills in this plugin (`gcp-to-aws`, `azure-to-aws`, `heroku-to-aws`, `llm-to-bedrock`). 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 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](https://aws.amazon.com/startups/prompt-library). **Last updated:** 2026-09-24 --- ## Where to start Open [`references/prompt-library.md`](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: 1. **Prompts — searchable index** — copy-paste prompts. 2. **Downloadable agents** — installable agents that clone from a GitHub repo. 3. **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: 1. Read the index in `references/prompt-library.md`, filter by keyword, identify the matching slug. 2. Open `references/prompt-library/<slug>.md` and read the full System Prompt. 3. 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?"_ 4. 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 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.
From aws/agent-toolkit-for-aws at df2ab44, shown as plain text under its license: Apache-2.0 (permissive). The license text is in LICENSE.
View SKILL.md on GitHub at df2ab44Files
- SKILL.md12 KB · 7c008403d965
- references/
- prompt-library.md28 KB · 858e038c2634
- prompt-library/
- ai-support-ticket-triage-and-routing-assistant.md5.4 KB · ac68f071f9d8
- aws-architecture-assessment-with-mcp-integration.md23 KB · 5dbd69e57aa8
- aws-cdk-typescript-pipeline-generator.md3.2 KB · 998864bf06ed
- aws-ecs-express-deployment-assistant.md4.6 KB · 4acc57c2d56a
- aws-guardduty.md4.2 KB · c7783b566f81
- aws-security-baseline-terraform-deployment-kit.md3.9 KB · 7ecdd0f308be
- awsome-mvp-builder.md5.5 KB · f2bf89b0213d
- bedrock-quota-manager.md25 KB · e4b74120f71a
- container-orchestration.md3.8 KB · 01eb2df49cab
- cost-anomaly-detection.md22 KB · 734aa95a6d5f
- cost-optimized-eks-with-spot-instances.md2.5 KB · de4b51848098
- day-one-aws-foundation-setup.md5.5 KB · 5d361f6cac24
- deploy-github-repo.md3.8 KB · 57877b4a7981
- elasticsearch-to-opensearch-migration.md14 KB · 255a99f0a4ec
- full-aws-deployment-agent.md4.8 KB · 8fa53ea1cea5
- gpu-instance-quota-assistant.md17 KB · e4319153a7c7
- kiro-project-init.md24 KB · 70f6a4c60129
- local-code-to-cloud.md3.5 KB · 1cf81fbeb0be
- multi-region-assessment.md50 KB · 0b44da45adc1
- mvsp.md13 KB · e7bbd7009993
- open-source-llm-inference.md11 KB · 2c7e27ebc56a
- openapi-to-agentcore-gateway-deployment.md11 KB · 0227e59e21cd
- opensearch-cluster-operational-review.md3.2 KB · 1cf7be805eee
- rag-chatbot-with-claude.md2.9 KB · d3155e796821
- resiliency-baseline-evaluation.md30 KB · a11446ffae14
- security-baseline-evaluation.md30 KB · 3565520cb22d
- startup-landing-page-deployment.md4.1 KB · 5b5c84386e76
- startup-pitch.md2.7 KB · 89f22cba243e
- well-architecture-review.md4.8 KB · c5df0ddc5ac2
31 files, 377 KB in total. Each file has a sha256 in the pin's manifest; the first 12 characters are shown.
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