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://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/kiro-project-init.md
source_url: https://aws.amazon.com/startups/prompt-library/kiro-project-init title: "Kiro Project Init: Automated Spec-Driven Development Setup" tags: ["Prototyping", "Deployment", "Kiro", "Lambda", "Beginner", "DynamoDB", "API Gateway"]
Kiro Project Init: Automated Spec-Driven Development Setup
One-command project setup with AI-powered specs, automated testing, and AWS integrations. Generates structured requirements, design docs, and deployment-ready code—eliminating hours of manual setup.
System Prompt
Project Setup - modify this to describe what needs to be built
App Name:PROJECTNAME - e.g. MyLittle Project
Description: Use Case: A TODO list
Features: Key features: add/remove tasks, assign to people, mark as done, view all tasks, view tasks for a person
You are setting up a specification-driven development environment with steering files, agent hooks, and the unified AWS MCP Server.
PROJECT CONTEXT
Extract from Project Setup above. Use these defaults if not specified:
Project Type: Full-stack web application
Tech Stack: React frontend, Python backend, AWS services
AWS Services: Lambda, DynamoDB, S3, API Gateway (simplest options)
Team Size: Solo developer
Security: Standard
Target Users: Development teams
TASK 1: CREATE STRUCTURE
[PROJECT_NAME]/
├── .kiro/
│ ├── steering/ # 6 files: product, tech, structure, api-standards, testing-standards, security-policies
│ ├── hooks/ # 4 files: test-sync, documentation-update, security-scan, cost-check
│ └── specs/.gitkeep
├── .vscode/mcp.json
├── .cursor/mcp.json
├── .gitignore
├── .env.example
└── README.mdTASK 2: STEERING FILES
.kiro/steering/product.md
---
inclusion: always
---
# Product Overview: [PROJECT_NAME]
## Purpose
[2-3 paragraphs: what it does, why it exists]
## Target Users
[Who uses this]
## Key Features
[3-7 core features]
## Business Objectives
[Business goals]
## Success Metrics
[3-5 key metrics].kiro/steering/tech.md
---
inclusion: always
---
# Technology Stack: [PROJECT_NAME]
## Primary Technologies
- **Frontend**: [e.g., React 18, TypeScript, Vite]
- **Backend**: [e.g., Python 3.12, FastAPI]
- **Database**: [e.g., DynamoDB, Aurora PostgreSQL]
- **Infrastructure**: [e.g., AWS CDK, Lambda, API Gateway]
- **Testing**: [e.g., Jest, Pytest, Playwright]
## AWS Services
- **Compute**: [Lambda, ECS, EC2]
- **Storage**: [S3, DynamoDB, Aurora]
- **Networking**: [API Gateway, CloudFront, VPC]
- **AI/ML**: [Bedrock, SageMaker]
- **Monitoring**: [CloudWatch, X-Ray, CloudTrail]
## MCP Servers Configured
- **aws-mcp** (unified AWS MCP Server): AWS service management, AWS documentation search and reads, regional availability, and AWS skills — one server covering all AWS access for this project
## Development Tools
- **IDE**: [VS Code, Cursor]
- **Version Control**: [Git, GitHub]
- **CI/CD**: [GitHub Actions, CodePipeline]
- **Package Management**: [npm, pip, poetry]
## Technical Constraints
[Limitations, requirements]
## Architecture Decisions
[Key choices and rationale].kiro/steering/structure.md
---
inclusion: always
---
# Project Structure: [PROJECT_NAME]
## Directory Organizationsrc/ ├── components/ # Reusable UI ├── pages/ # Page-level ├── services/ # Business logic ├── utils/ # Helpers ├── types/ # TypeScript types ├── hooks/ # Custom hooks └── config/ # Configuration
## Naming Conventions
- **Components**: PascalCase (`UserProfile.tsx`)
- **Utilities**: camelCase (`formatDate.ts`)
- **Tests**: `.test.ts` suffix (`UserProfile.test.tsx`)
- **Types**: `.types.ts` suffix (`User.types.ts`)
## Import Patterns
- Absolute imports: `@/components/Button`
- Group: external, internal, types, styles
- Prefer named exports
## Infrastructure Location
[e.g., `infrastructure/`, `cdk/`].kiro/steering/api-standards.md
---
inclusion: fileMatch
fileMatchPattern: "**/{api,routes,endpoints,controllers}/**/*.{ts,js,py}"
---
# API Standards: [PROJECT_NAME]
## REST Conventions
- Plural nouns: `/users`, `/products`
- Methods: GET (read), POST (create), PUT (update), DELETE (delete)
- Status: 200 (success), 201 (created), 400 (client error), 500 (server error)
## Response Format
```typescript
// Success
{ "data": {}, "meta": { "timestamp": "ISO 8601", "requestId": "uuid" }}
// Error
{ "error": { "code": "ERROR_CODE", "message": "...", "details": {} }, "meta": {...}}
```Authentication
[JWT, API keys, OAuth, etc.]
Validation
Validate all inputs at API boundary
Use schema validation (Zod, Joi, Pydantic)
Return field-level errors
Documentation
OpenAPI 3.0 specs in
api-specs/Use
aws___search_documentation/aws___read_documentationfor AWS patterns
### .kiro/steering/testing-standards.md
```markdown
---
inclusion: fileMatch
fileMatchPattern: "**/*.{test,spec}.{ts,js,tsx,jsx,py}"
---
# Testing Standards: [PROJECT_NAME]
## Organization
- Co-locate: `Component.tsx` → `Component.test.tsx`
- Or mirror in `__tests__/`
## Structure
```typescript
describe('[ComponentName]', () => {
describe('[method]', () => {
it('should [behavior] when [condition]', () => {
// Arrange, Act, Assert
});
});
});Principles
Unit: Isolated functions/components
Integration: Module interactions
E2E: Complete workflows
Coverage: Minimum [80%]
AWS Testing
SDK mocks for unit tests
LocalStack for integration
Document which
aws-mcptools each test path relies on
### .kiro/steering/security-policies.md
```markdown
---
inclusion: always
---
# Security Policies: [PROJECT_NAME]
## Credential Management
- NEVER commit secrets
- Use environment variables
- Store in Secrets Manager/Parameter Store
- Document in `.env.example`
## Input Validation
- Validate ALL inputs
- Parameterized queries
- CSRF protection
- Length limits
## Authentication & Authorization
[Auth flows, authorization rules]
## Data Protection
[Encryption at rest/transit, PII handling]
## Compliance
[HIPAA, GDPR, SOC 2, PCI DSS]
## Security Scanning
- cdk-nag for CDK stacks
- Checkov for Terraform
- Well-Architected Framework review guidance via `aws___search_documentation` / `aws___read_documentation`
## Incident Response
[Procedures]TASK 3: AGENT HOOKS
.kiro/hooks/test-sync.kiro.hook
{
"name": "Test File Synchronization",
"description": "Auto-creates/updates test files on save",
"version": "1",
"when": {
"type": "fileSaved",
"patterns": ["src/**/*.{ts,tsx,js,jsx}"]
},
"then": {
"type": "askAgent",
"prompt": "Source file saved:\n1. Check for test file (.test.ts/.test.tsx)\n2. If missing: Create with tests for all exports per testing-standards.md\n3. If exists: Add tests for untested functionality\n4. Follow structure.md conventions\n5. Don't modify source\n\nRef: #[[file:.kiro/steering/testing-standards.md]] #[[file:.kiro/steering/structure.md]]"
}
}.kiro/hooks/documentation-update.kiro.hook
{
"name": "API Documentation Updater",
"description": "Updates API docs on API file changes",
"version": "1",
"when": {
"type": "fileSaved",
"patterns": ["src/{api,routes,endpoints,controllers}/**/*.{ts,py}"]
},
"then": {
"type": "askAgent",
"prompt": "API file modified:\n1. Analyze endpoint/parameter/response changes\n2. Update OpenAPI spec in api-specs/\n3. Use aws___search_documentation / aws___read_documentation for AWS patterns\n4. Update README API section\n5. Update JSDoc/docstrings\n6. Verify api-standards.md compliance\n\nRef: #[[file:.kiro/steering/api-standards.md]]"
}
}.kiro/hooks/security-scan.kiro.hook
{
"name": "Security Validation Scanner",
"description": "Pre-commit security scan",
"version": "1",
"when": { "type": "manual" },
"then": {
"type": "askAgent",
"prompt": "Security scan:\n1. Scan for: credentials, API keys, console.log with sensitive data, SQL injection, unsafe eval()\n2. Infrastructure: run cdk-nag against CDK stacks and Checkov against Terraform\n3. Verify security-policies.md: input validation, auth checks, encryption\n4. Report: issues by severity (CRITICAL/HIGH/MEDIUM/LOW), locations, fixes, pass/fail\n\nRef: #[[file:.kiro/steering/security-policies.md]]"
}
}.kiro/hooks/cost-check.kiro.hook
{
"name": "Infrastructure Cost Estimator",
"description": "Estimates cost impact",
"version": "1",
"when": {
"type": "fileSaved",
"patterns": ["{infrastructure,cdk,terraform}/**/*", "**/*.template.{json,yaml,yml}"]
},
"then": {
"type": "askAgent",
"prompt": "Infrastructure modified:\n1. Identify added/modified/removed resources\n2. Price each resource with the AWS Price List Query API (`aws pricing get-products`, via aws___call_aws) or the AWS Pricing Calculator: costs per resource, region pricing, data transfer, compare previous\n3. Report: monthly estimate, delta, optimizations, unexpected costs\n4. Append to infrastructure/cost-estimates.md\n5. Flag if increase > $[THRESHOLD, e.g., 500]\n\nNote: cost figures are estimates — state assumptions explicitly"
}
}TASK 4: MCP CONFIGURATION
Both .vscode/mcp.json and .cursor/mcp.json (identical)
Declare exactly one MCP server — the unified AWS MCP Server. It covers AWS API calls, AWS documentation, and regional availability, so no per-service AWS MCP servers are needed.
{
"mcpServers": {
"aws-mcp": {
"command": "uvx",
"args": [
"mcp-proxy-for-aws-cli@latest",
"https://aws-mcp.us-east-1.api.aws/mcp",
"--skip-auth"
],
"env": {
"AWS_REGION": "[us-east-1]",
"AWS_PROFILE": "[profile-name]"
}
}
}
}TASK 5: SUPPORTING FILES
.gitignore
mcp.json.local
.env
*.log
mcp-*.log
.mcp-cache/
.aws/
.vscode/
.cursor/
.idea/
node_modules/
__pycache__/
.venv/
venv/
dist/
build/
*.js.map
.DS_Store
Thumbs.db.env.example
AWS_REGION=us-east-1
AWS_PROFILE=your-profile
DATABASE_CLUSTER_ARN=arn:aws:rds:...
DATABASE_SECRET_ARN=arn:aws:secretsmanager:...
# API_KEY=your-key
COST_ALERT_THRESHOLD=500README.md
# [PROJECT_NAME]
[Brief description]
## Structure
- `.kiro/steering/` - AI context, standards
- `.kiro/hooks/` - Automated workflows
- `.kiro/specs/` - Feature specs (requirements, design, tasks)
- `.vscode/mcp.json`, `.cursor/mcp.json` - MCP configs
## Prerequisites
1. **uv**: install per the official guide (https://docs.astral.sh/uv/getting-started/installation/), e.g. `brew install uv` or `pipx install uv`
2. **Python 3.10+**: `uv python install 3.10`
3. **AWS CLI**: Configured
4. **Node.js**: [version]
### AWS Setup
```bash
aws configure --profile [PROFILE]
export AWS_PROFILE=[PROFILE]
export AWS_REGION=[REGION]
```Getting Started
## Install
[npm install / pip install]
## Configure
cp .env.example .env
## Edit .env
## Verify MCP
timeout 15s uvx mcp-proxy-for-aws-cli@latest https://aws-mcp.us-east-1.api.aws/mcp --skip-auth 2>&1 || echo "OK"Workflow
Spec-Driven Development
Create spec in AI assistant
Requirements → Design → Tasks
Execute tasks
Iterate
Agent Hooks
Test Sync: Auto-creates tests on save
Doc Update: Updates API docs
Security Scan: Manual pre-commit scan
Cost Check: Estimates infrastructure costs
MCP Usage
"Use aws-mcp to read CloudWatch error logs from the last hour"
"Use aws-mcp to query the AWS Price List API and estimate costs for 3 Lambda functions"MCP Servers
One server: aws-mcp, the unified AWS MCP Server. Tools it exposes:
aws___call_aws,aws___run_script- AWS API calls and scripted AWS CLI workflowsaws___search_documentation,aws___read_documentation,aws___recommend- AWS documentationaws___list_regions,aws___get_regional_availability- region and service availability dataaws___retrieve_skill,aws___get_tasks,aws___get_presigned_url- AWS skills and task helpers
Troubleshooting
MCP Issues
## Logs
tail -f ~/Library/Logs/Claude/mcp*.log # Mac
tail -f %APPDATA%/Claude/mcp*.log # Windows
## Clear cache
uv cache clean mcp-proxy-for-aws-cli
## Test
timeout 15s uvx mcp-proxy-for-aws-cli@latest https://aws-mcp.us-east-1.api.aws/mcp --skip-auth 2>&1Auth Errors
aws sts get-caller-identity --profile [PROFILE]Resources
## TASK 6: INITIAL FEATURE SPEC
Create `.kiro/specs/[app-name]-core/` with three files:
### requirements.md
```markdown
# Requirements: [FEATURE_NAME]
## Overview
[2-3 paragraphs from PROJECT CONTEXT]
## User Personas
[From PROJECT CONTEXT]
## User Story 1: [From Core Features]
As a [persona]
I want to [action]
So that [benefit]
### Acceptance Criteria
WHEN [action/event]
THE SYSTEM SHALL [behavior]
AND THE SYSTEM SHALL [behavior]
WHEN [error condition]
THE SYSTEM SHALL [error handling]
[Repeat for each core feature]
## Non-Functional Requirements
### Performance
- Response time: [define]
- Throughput: [define]
- Scalability: [define]
### Security
- Authentication: [from PROJECT CONTEXT]
- Authorization: [define]
- Data protection: [encryption, PII]
### Reliability
- Availability: [define]
- Error handling: [define]
- Monitoring: [define]
## External Dependencies
[List with integration requirements]
## Data Requirements
[Schema, access patterns, retention]
## Out of Scope
[What's NOT included]design.md
# Design: [FEATURE_NAME]
## Architecture
[High-level using tech stack from PROJECT CONTEXT]
```text
[ASCII component diagram]
```Components
Component 1: [Name]
Purpose: [What it does] Technology: [From tech stack] Responsibilities:
[Responsibility 1]
[Responsibility 2] Interfaces:
Input: [What it receives]
Output: [What it produces]
Dependencies: [What it calls] [Repeat for each component]
Data Model
Entity 1: [Name]
Storage: [DynamoDB/Aurora/S3] Schema:
{
id: string;
[field]: type;
createdAt: timestamp;
updatedAt: timestamp;
}Access Patterns:
Query by [field]: [use case]
List by [criteria]: [use case] Indexes: [GSIs/LSIs] [Repeat for each entity]
API Design
[METHOD] /[path]
Purpose: [What it does] Auth: [Required level] Request:
{ [param]: type; }Response (200):
{ data: {...}, meta: {...} }Errors: 400, 401, 500 [Repeat for each endpoint]
AWS Services
[Service 1]
Purpose: [How used] Config: Runtime, Memory, Timeout, Env vars Triggers: [What invokes] Permissions: [IAM] [Repeat for each service]
Security
Auth Flow
[Describe + ASCII diagram]
Authorization
[RBAC, ABAC, etc.]
Data Protection
At rest: [approach]
In transit: [TLS]
PII: [handling]
Secrets: [Secrets Manager]
Error Handling
Client (4xx): [approach]
Server (5xx): [approach]
External: [retry, circuit breakers]
Validation: [approach]
Logging
App: CloudWatch structured JSON
Access: API Gateway/ALB
Audit: CloudTrail
Metrics: CloudWatch custom
Testing
Unit: Isolated, mocked, [coverage%]
Integration: Component interactions, LocalStack
E2E: Full workflows, deployed env
Deployment
IaC
Tool: AWS CDK Structure:
infrastructure/
├── lib/[feature]-stack.ts
└── bin/app.tsEnvironments
Dev, Staging, Production: [configs]
CI/CD
Commit → 2. Tests → 3. Security scan → 4. Deploy staging → 5. E2E → 6. Approval → 7. Production
Monitoring
Metrics
[Metric 1]: [how to measure]
Alarms
[Alarm 1]: Threshold, action
Dashboards
[Dashboard 1]: [what it shows]
Performance
Optimization: [strategies]
Caching: [what, where]
Scalability: [how components scale]
Cost
Total: $[total]/month
Optimizations: [opportunities]
Migration & Rollback
Deployment: [blue/green, canary, rolling]
Rollback: [how to rollback]
Open Questions
[Design decisions needing clarification]
References
#[[file:.kiro/steering/tech.md]]
#[[file:.kiro/steering/api-standards.md]]
#[[file:.kiro/steering/security-policies.md]]
### tasks.md
```markdown
# Tasks: [FEATURE_NAME]
## Task 1: Setup Infrastructure
**Status**: pending | **Depends**: none | **Effort**: 2-4h
### Description
Create base infrastructure: VPC, security groups, foundational resources
### Acceptance Criteria
- [ ] CDK initialized
- [ ] VPC with subnets
- [ ] Security groups
- [ ] IAM roles (least-privilege)
- [ ] CDK Nag passes
- [ ] Deploys to dev
### Files
- `infrastructure/lib/foundation-stack.ts`
- `infrastructure/bin/app.ts`
### Testing
- Deploy to dev
- Verify in Console
- Run CDK Nag
---
## Task 2: Data Layer
**Status**: pending | **Depends**: Task 1 | **Effort**: 3-5h
### Description
Database tables/resources, data access layer
### Acceptance Criteria
- [ ] Database with schema
- [ ] Indexes for access patterns
- [ ] CRUD operations
- [ ] Connection pooling
- [ ] Error handling
- [ ] Unit tests (>80%)
### Files
- `infrastructure/lib/database-stack.ts`
- `src/data/[entity]-repository.ts`
- `src/data/[entity]-repository.test.ts`
### Testing
- Unit tests
- Integration with LocalStack
- Verify in AWS
---
## Task 3: [Component] Service
**Status**: pending | **Depends**: Task 2 | **Effort**: 4-6h
### Description
Business logic per design.md
### Acceptance Criteria
- [ ] All methods from design
- [ ] Input validation
- [ ] Error handling
- [ ] Structured logging
- [ ] Unit tests (>80%)
- [ ] Integration tests
### Files
- `src/services/[component]-service.ts`
- `src/services/[component]-service.test.ts`
### Testing
- Unit tests
- Error scenarios
- Edge cases
---
## Task 4: API Endpoints
**Status**: pending | **Depends**: Task 3 | **Effort**: 4-6h
### Description
API endpoints per design.md, api-standards.md
### Acceptance Criteria
- [ ] All endpoints
- [ ] Standard request/response format
- [ ] Auth middleware
- [ ] Authorization checks
- [ ] Input validation
- [ ] Error responses
- [ ] OpenAPI spec
- [ ] Unit tests (>80%)
### Files
- `src/api/[resource]-controller.ts`
- `src/middleware/auth.ts`
- `api-specs/[feature].openapi.yaml`
### Testing
- Endpoint tests
- Auth/authz
- Validation errors
---
## Task 5: Deploy Lambda
**Status**: pending | **Depends**: Task 4 | **Effort**: 2-3h
### Description
Package and deploy Lambda functions
### Acceptance Criteria
- [ ] Lambda in CDK
- [ ] Env vars
- [ ] IAM permissions
- [ ] CloudWatch Logs
- [ ] Layers (if needed)
- [ ] Deploys successfully
- [ ] Cold start <3s
### Files
- `infrastructure/lib/lambda-stack.ts`
- `src/lambda/[function]-handler.ts`
### Testing
- Local invocation
- Deploy to dev
- Test via API Gateway
- Check logs
---
## Task 6: Authentication
**Status**: pending | **Depends**: Task 4 | **Effort**: 3-5h
### Description
Auth flow per design.md security
### Acceptance Criteria
- [ ] Auth mechanism
- [ ] Token generation/validation
- [ ] Session management
- [ ] Secure storage
- [ ] Middleware protects endpoints
- [ ] Unit tests (>80%)
- [ ] Integration tests
### Files
- `src/auth/auth-service.ts`
- `src/middleware/auth.ts`
### Testing
- Successful auth
- Invalid credentials
- Token expiration
- Unauthorized access
---
## Task 7: Monitoring & Logging
**Status**: pending | **Depends**: Task 5 | **Effort**: 2-3h
### Description
Monitoring, logging, alarms per design.md
### Acceptance Criteria
- [ ] Structured logging
- [ ] CloudWatch Logs with retention
- [ ] Custom metrics
- [ ] Alarms
- [ ] Dashboard
- [ ] X-Ray (if applicable)
### Files
- `infrastructure/lib/monitoring-stack.ts`
- `src/utils/logger.ts`
### Testing
- Generate logs, verify
- Trigger alarms
- View dashboard
---
## Task 8: Security Hardening
**Status**: pending | **Depends**: Task 6 | **Effort**: 2-4h
### Description
Security controls per security-policies.md
### Acceptance Criteria
- [ ] CDK Nag passes
- [ ] Secrets in Secrets Manager
- [ ] Encryption at rest
- [ ] TLS/HTTPS enforced
- [ ] CORS configured
- [ ] Rate limiting
- [ ] Input sanitization
- [ ] Security headers
### Files
- `infrastructure/lib/security-stack.ts`
- `src/middleware/security.ts`
### Testing
- CDK Nag scan
- Rate limiting
- Encryption
- CORS
- Penetration testing
---
## Task 9: Integration Testing
**Status**: pending | **Depends**: Task 7, 8 | **Effort**: 3-5h
### Description
Integration tests for all user stories
### Acceptance Criteria
- [ ] Tests for each user story
- [ ] Happy paths
- [ ] Error scenarios
- [ ] Edge cases
- [ ] All acceptance criteria verified
- [ ] CI/CD integration
- [ ] Automated cleanup
### Files
- `tests/integration/[feature].test.ts`
### Testing
- Full suite
- Verify user stories
- Coverage report
---
## Task 10: Documentation
**Status**: pending | **Depends**: Task 9 | **Effort**: 2-3h
### Description
Comprehensive documentation
### Acceptance Criteria
- [ ] API docs (OpenAPI)
- [ ] README updated
- [ ] Architecture diagrams
- [ ] Deployment guide
- [ ] Troubleshooting guide
- [ ] Code comments
- [ ] Operations runbook
### Files
- `docs/[feature]/README.md`
- `docs/[feature]/architecture.md`
### Testing
- Review completeness
- Follow deployment guide
- Verify links
---
## Task 11: Performance Testing
**Status**: pending | **Depends**: Task 9 | **Effort**: 2-4h
### Description
Performance testing for non-functional requirements
### Acceptance Criteria
- [ ] Load tests
- [ ] Meets performance requirements
- [ ] Scalability verified
- [ ] Bottlenecks documented
- [ ] Cost under budget
- [ ] Results documented
### Files
- `tests/performance/[feature]-load.test.ts`
### Testing
- Load tests (expected traffic)
- Stress tests (2x traffic)
- Monitor costs
- Verify auto-scaling
---
## Task 12: Production Deployment
**Status**: pending | **Depends**: Task 10, 11 | **Effort**: 2-3h
### Description
Deploy to production with safeguards
### Acceptance Criteria
- [ ] Staging deployment
- [ ] E2E tests pass (staging)
- [ ] Security scan passed
- [ ] Cost reviewed
- [ ] Rollback plan documented
- [ ] Production deployment
- [ ] Smoke tests pass
- [ ] Monitoring healthy
### Files
- `.github/workflows/deploy-production.yml`
- `docs/[feature]/rollback-plan.md`
### Testing
- Deploy staging
- Full test suite
- Deploy production
- Smoke tests
- Monitor 24h
---
## Summary
**Total**: 12 tasks
**Effort**: [sum estimates]
**Critical Path**: 1→2→3→4→5→6→7→8→9→10→11→12
## Notes
- Parallelize where possible
- Review before marking complete
- Update as requirements changeCOMPLETION CHECKLIST
[ ] Directory structure (.kiro/, .vscode/, .cursor/)
[ ] 6 steering files
[ ] 4 hooks
[ ] 2 MCP configs (identical, single
aws-mcpserver)[ ] .gitignore, .env.example, README.md
[ ] Replace all [PLACEHOLDER] values
[ ] Initial spec: requirements.md, design.md, tasks.md
POST-SETUP
Set region and profile for the
aws-mcpserver in mcp.jsonAdd custom steering files
Customize hook prompts
Review/refine generated spec
Create additional specs
Keep docs current
SECURITY
Never commit credentials
Gitignore .env
Use Secrets Manager
Review MCP permissions
Run security scan before commits
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
A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.
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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Download ZIP
The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download prompt-library-for-startups.zip