
Amazon Alexa Integration
FreeTransform Alexa into an intelligent voice assistant.
Free · Opens the source repo
What Amazon Alexa Integration does
The Amazon Alexa Integration skill provides a comprehensive solution for creating intelligent voice skills using Amazon Alexa, leveraging Claude as the backend intelligence. This integration allows developers to harness the full capabilities of the AWS ecosystem, including services like Lambda, DynamoDB, Polly, Transcribe, and Lex. By combining these technologies, users can create sophisticated voice applications that respond intelligently to user queries and control smart home devices.
This skill is particularly useful for developers and designers who are looking to enhance their Alexa skills with advanced features such as natural language understanding, speech recognition, and smart home integration. The architecture described in the documentation outlines how user input flows from Alexa devices through the Alexa Cloud to AWS services, where Claude processes the information and generates responses. This enables the creation of a seamless voice interaction experience.
The skill supports various intents, such as handling user queries through the ChatIntent, managing smart home devices via the SmartHomeIntent, and executing routines with the RoutineIntent. This flexibility allows for the development of personalized and context-aware applications that can adapt to user preferences and historical interactions. With the ability to store user preferences in DynamoDB, the skill can provide a more tailored experience over time.
Overall, this skill is designed for those who want to build advanced voice applications that go beyond basic interactions, making it ideal for projects that require a high level of customization and integration with AWS services.
When to use it
Use this skill when you want to develop sophisticated voice applications that leverage AWS services and require advanced natural language processing capabilities.
When not to use it
Avoid this skill if your project does not involve Amazon Alexa or if you need a simpler solution that does not require extensive AWS integration.
What you can build with it
Building a Smart Home Assistant
Develop a voice skill that controls lights, thermostats, and other smart devices using Alexa.
Creating a Personal Assistant
Use the skill to create a personal assistant that answers questions and manages tasks using natural language.
Integrating with AWS Services
Leverage AWS services to enhance your Alexa skills with data storage, processing, and intelligent responses.
How to install Amazon Alexa Integration
View source1. Install with the skills CLI
npx skills add sickn33/agentic-awesome-skills/amazon-alexa --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by sickn33AMAZON ALEXA — Voz Inteligente com Claude
Overview
Integracao completa com Amazon Alexa para criar skills de voz inteligentes, transformar Alexa em assistente com Claude como cerebro (projeto Auri) e integrar com AWS ecosystem (Lambda, DynamoDB, Polly, Transcribe, Lex, Smart Home).
When to Use This Skill
- When you need specialized assistance with this domain
Do Not Use This Skill When
- The task is unrelated to amazon alexa
- A simpler, more specific tool can handle the request
- The user needs general-purpose assistance without domain expertise
How It Works
Voce e o especialista em Alexa e AWS Voice. Missao: transformar qualquer dispositivo Alexa em assistente ultra-inteligente usando Claude como LLM backend, com voz neural, memoria persistente e controle de Smart Home. Projeto-chave: AURI.
1. Visao Geral Do Ecossistema
[Alexa Device] → [Alexa Cloud] → [AWS Lambda] → [Claude API]
Fala Transcricao Logica Inteligencia
↑ ↑ ↑ ↑
Usuario Intent Handler Anthropic
+ DynamoDB
+ Polly TTS
+ APL Visual
Componentes Da Arquitetura Auri
| Componente | Servico AWS | Funcao |
|---|---|---|
| Voz → Texto | Alexa ASR nativo | Reconhecimento de fala |
| NLU | ASK Interaction Model + Lex V2 | Extrair intent e slots |
| Backend | AWS Lambda (Python/Node.js) | Logica e orquestracao |
| LLM | Claude API (Anthropic) | Inteligencia e respostas |
| Persistencia | Amazon DynamoDB | Historico e preferencias |
| Texto → Voz | Amazon Polly (neural) | Fala natural da Auri |
| Interface Visual | APL (Alexa Presentation Language) | Telas em Echo Show |
| Smart Home | Alexa Smart Home API | Controle de dispositivos |
| Automacao | Alexa Routines API | Rotinas inteligentes |
2.1 Pre-Requisitos
## Ask Cli
npm install -g ask-cli
ask configure
## Aws Cli
pip install awscli
aws configure
Criar Skill Com Template
ask new
--template hello-world
--skill-name auri
--language pt-BR
└── .Ask/Ask-Resources.Json
## 2.3 Configurar Invocation Name
No arquivo `models/pt-BR.json`:
```json
{
"interactionModel": {
"languageModel": {
"invocationName": "auri"
}
}
}
3.1 Intents Essenciais Para Auri
{
"interactionModel": {
"languageModel": {
"invocationName": "auri",
"intents": [
{"name": "AMAZON.HelpIntent"},
{"name": "AMAZON.StopIntent"},
{"name": "AMAZON.CancelIntent"},
{"name": "AMAZON.FallbackIntent"},
{
"name": "ChatIntent",
"slots": [{"name": "query", "type": "AMAZON.SearchQuery"}],
"samples": [
"{query}",
"me ajuda com {query}",
"quero saber sobre {query}",
"o que voce sabe sobre {query}",
"explique {query}",
"pesquise {query}"
]
},
{
"name": "SmartHomeIntent",
"slots": [
{"name": "device", "type": "AMAZON.Room"},
{"name": "action", "type": "ActionType"}
],
"samples": [
"{action} a {device}",
"controla {device}",
"acende {device}",
"apaga {device}"
]
},
{
"name": "RoutineIntent",
"slots": [{"name": "routine", "type": "RoutineType"}],
"samples": [
"ativa rotina {routine}",
"executa {routine}",
"modo {routine}"
]
}
],
"types": [
{
"name": "ActionType",
"values": [
{"name": {"value": "liga", "synonyms": ["acende", "ativa", "liga"]}},
{"name": {"value": "desliga", "synonyms": ["apaga", "desativa", "desliga"]}}
]
},
{
"name": "RoutineType",
"values": [
{"name": {"value": "bom dia", "synonyms": ["acordar", "manhã"]}},
{"name": {"value": "boa noite", "synonyms": ["dormir", "descansar"]}},
{"name": {"value": "trabalho", "synonyms": ["trabalhar", "foco"]}},
{"name": {"value": "sair", "synonyms": ["saindo", "goodbye"]}}
]
}
]
}
}
}
4.1 Handler Principal Python
import os
import time
import anthropic
import boto3
from ask_sdk_core.skill_builder import SkillBuilder
from ask_sdk_core.handler_input import HandlerInput
from ask_sdk_core.utils import is_intent_name, is_request_type
from ask_sdk_model import Response
from ask_sdk_dynamodb_persistence_adapter import DynamoDbPersistenceAdapter
## ============================================================
@sb.request_handler(can_handle_func=is_request_type("LaunchRequest"))
def launch_handler(handler_input: HandlerInput) -> Response:
attrs = handler_input.attributes_manager.persistent_attributes
name = attrs.get("name", "")
greeting = f"Oi{', ' + name if name else ''}! Eu sou a Auri. Como posso ajudar?"
return (handler_input.response_builder
.speak(greeting).ask("Em que posso ajudar?").response)
@sb.request_handler(can_handle_func=is_intent_name("ChatIntent"))
def chat_handler(handler_input: HandlerInput) -> Response:
try:
# Obter query
slots = handler_input.request_envelope.request.intent.slots
query = slots["query"].value if slots.get("query") else None
if not query:
return (handler_input.response_builder
.speak("Pode repetir? Nao entendi bem.").ask("Pode repetir?").response)
# Carregar historico
attrs = handler_input.attributes_manager.persistent_attributes
history = attrs.get("history", [])
# Montar mensagens para Claude
messages = history[-MAX_HISTORY:]
messages.append({"role": "user", "content": query})
# Chamar Claude
client = anthropic.Anthropic(api_key=os.environ["ANTHROPIC_API_KEY"])
response = client.messages.create(
model=CLAUDE_MODEL,
max_tokens=512,
system=AURI_SYSTEM_PROMPT,
messages=messages
)
reply = response.content[0].text
# Truncar para nao exceder timeout
if len(reply) > MAX_RESPONSE_CHARS:
reply = reply[:MAX_RESPONSE_CHARS] + "... Quer que eu continue?"
# Salvar historico
history.append({"role": "user", "content": query})
history.append({"role": "assistant", "content": reply})
attrs["history"] = history[-50:] # Manter ultimas 50
handler_input.attributes_manager.persistent_attributes = attrs
handler_input.attributes_manager.save_persist
### 4.2 Variaveis De Ambiente Lambda
ANTHROPIC_API_KEY=sk-... (armazenar em Secrets Manager) DYNAMODB_TABLE=auri-users AWS_REGION=us-east-1
### 4.3 Requirements.Txt
ask-sdk-core>=1.19.0 ask-sdk-dynamodb-persistence-adapter>=1.19.0 anthropic>=0.40.0 boto3>=1.34.0
---
### 5.1 Criar Tabela
```bash
aws dynamodb create-table \
--table-name auri-users \
--attribute-definitions AttributeName=userId,AttributeType=S \
--key-schema AttributeName=userId,KeyType=HASH \
--billing-mode PAY_PER_REQUEST \
--region us-east-1
5.2 Schema Do Usuario
{
"userId": "amzn1.ask.account.XXXXX",
"name": "Joao",
"history": [
{"role": "user", "content": "..."},
{"role": "assistant", "content": "..."}
],
"preferences": {
"language": "pt-BR",
"voice": "Vitoria",
"personality": "assistente profissional"
},
"smartHome": {
"devices": {},
"routines": {}
},
"updatedAt": 1740960000,
"ttl": 1748736000
}
5.3 Ttl Automatico (Expirar Dados Antigos)
import time
## Adicionar Ttl De 180 Dias Ao Salvar
attrs["ttl"] = int(time.time()) + (180 * 24 * 3600)
6.1 Vozes Disponiveis (Portugues)
| Voice | Idioma | Tipo | Recomendado |
|---|---|---|---|
Vitoria | pt-BR | Neural | ✅ Auri PT-BR |
Camila | pt-BR | Neural | Alternativa |
Ricardo | pt-BR | Standard | Masculino |
Ines | pt-PT | Neural | Portugal |
6.2 Integrar Polly Na Resposta
import boto3
import base64
def synthesize_polly(text: str, voice_id: str = "Vitoria") -> str:
"""Retorna URL de audio Polly para usar em Alexa."""
client = boto3.client("polly", region_name="us-east-1")
response = client.synthesize_speech(
Text=text,
OutputFormat="mp3",
VoiceId=voice_id,
Engine="neural"
)
# Salvar em S3 e retornar URL
# (necessario para usar audio customizado no Alexa)
return upload_to_s3(response["AudioStream"].read())
def speak_with_polly(handler_input, text, voice_id="Vitoria"):
"""Retornar resposta usando voz Polly customizada via SSML."""
audio_url = synthesize_polly(text, voice_id)
ssml = f'<speak><audio src="{audio_url}"/></speak>'
return handler_input.response_builder.speak(ssml)
6.3 Ssml Para Controle De Voz
<speak>
<prosody rate="90%" pitch="+5%">
Oi! Eu sou a Auri.
</prosody>
<break time="0.5s"/>
<emphasis level="moderate">Como posso ajudar?</emphasis>
</speak>
7.1 Template De Chat
{
"type": "APL",
"version": "2023.3",
"theme": "dark",
"mainTemplate": {
"parameters": ["payload"],
"items": [{
"type": "Container",
"width": "100%",
"height": "100%",
"backgroundColor": "#1a1a2e",
"items": [
{
"type": "Text",
"text": "AURI",
"fontSize": "32px",
"color": "#e94560",
"textAlign": "center",
"paddingTop": "20px"
},
{
"type": "Text",
"text": "${payload.lastResponse}",
"fontSize": "24px",
"color": "#ffffff",
"padding": "20px",
"maxLines": 8,
"grow": 1
},
{
"type": "Text",
"text": "Diga algo para continuar...",
"fontSize": "18px",
"color": "#888888",
"textAlign": "center",
"paddingBottom": "20px"
}
]
}]
}
}
7.2 Adicionar Apl Na Resposta
@sb.request_handler(can_handle_func=is_intent_name("ChatIntent"))
def chat_with_apl(handler_input: HandlerInput) -> Response:
# ... obter reply do Claude ...
# Verificar se device suporta APL
supported = handler_input.request_envelope.context.system.device.supported_interfaces
has_apl = getattr(supported, "alexa_presentation_apl", None) is not None
if has_apl:
apl_directive = {
"type": "Alexa.Presentation.APL.RenderDocument",
"token": "auri-chat",
"document": CHAT_APL_DOCUMENT,
"datasources": {"payload": {"lastResponse": reply}}
}
handler_input.response_builder.add_directive(apl_directive)
return handler_input.response_builder.speak(reply).ask("Mais alguma coisa?").response
8.1 Ativar Smart Home Skill
No skill.json, adicionar:
{
"apis": {
"smartHome": {
"endpoint": {
"uri": "arn:aws:lambda:us-east-1:123456789:function:auri-smart-home"
}
}
}
}
8.2 Handler De Smart Home
def handle_smart_home_directive(event, context):
namespace = event["directive"]["header"]["namespace"]
name = event["directive"]["header"]["name"]
endpoint_id = event["directive"]["endpoint"]["endpointId"]
if namespace == "Alexa.PowerController":
state = "ON" if name == "TurnOn" else "OFF"
# Chamar sua API de smart home
control_device(endpoint_id, {"power": state})
return build_smart_home_response(endpoint_id, "powerState", state)
elif namespace == "Alexa.BrightnessController":
brightness = event["directive"]["payload"]["brightness"]
control_device(endpoint_id, {"brightness": brightness})
return build_smart_home_response(endpoint_id, "brightness", brightness)
8.3 Discovery De Dispositivos
def handle_discovery(event, context):
return {
"event": {
"header": {
"namespace": "Alexa.Discovery",
"name": "Discover.Response",
"payloadVersion": "3"
},
"payload": {
"endpoints": [
{
"endpointId": "light-sala-001",
"friendlyName": "Luz da Sala",
"displayCategories": ["LIGHT"],
"capabilities": [
{
"type": "AlexaInterface",
"interface": "Alexa.PowerController",
"version": "3"
},
{
"type": "AlexaInterface",
"interface": "Alexa.BrightnessController",
"version": "3"
}
]
}
]
}
}
}
Deploy Completo (Skill + Lambda)
cd auri/ ask deploy
Verificar Status
ask status
Testar No Simulador
ask dialog --locale pt-BR
Teste Especifico De Intent
ask simulate
--text "abrir auri"
--locale pt-BR
--skill-id amzn1.ask.skill.YOUR-SKILL-ID
## Criar Lambda Manualmente
aws lambda create-function \
--function-name auri-skill \
--runtime python3.11 \
--role arn:aws:iam::ACCOUNT:role/auri-lambda-role \
--handler lambda_function.handler \
--timeout 8 \
--memory-size 512 \
--zip-file fileb://function.zip
## Adicionar Trigger Alexa
aws lambda add-permission \
--function-name auri-skill \
--statement-id alexa-skill-trigger \
--action lambda:InvokeFunction \
--principal alexa-appkit.amazon.com \
--event-source-token amzn1.ask.skill.YOUR-SKILL-ID
Usar Secrets Manager
aws secretsmanager create-secret
--name auri/anthropic-key
--secret-string '{"ANTHROPIC_API_KEY": "sk-..."}'
Lambda Acessa Via Sdk:
import boto3, json def get_secret(secret_name): client = boto3.client('secretsmanager') response = client.get_secret_value(SecretId=secret_name) return json.loads(response['SecretString'])
---
## Fase 1 — Setup (Dia 1)
[ ] Conta Amazon Developer criada [ ] Conta AWS configurada (free tier) [ ] ASK CLI instalado e configurado [ ] IAM Role criada com permissoes: Lambda, DynamoDB, Polly, Logs [ ] Anthropic API key armazenada em Secrets Manager
## Fase 2 — Skill Base (Dia 2-3)
[ ] ask new --template hello-world --skill-name auri [ ] Interaction model definido (pt-BR.json) [ ] LaunchRequest handler funcionando [ ] ChatIntent handler com Claude integrado [ ] ask deploy funcionando [ ] Teste basico no ASK simulator
## Fase 3 — Persistencia (Dia 4)
[ ] DynamoDB table criada [ ] Persistencia de historico funcionando [ ] TTL configurado [ ] Preferencias do usuario salvas
## Fase 4 — Polly + Apl (Dia 5-6)
[ ] Polly integrado com voz Vitoria (neural) [ ] APL template de chat criado [ ] APL renderizando em Echo Show simulator
## Fase 5 — Smart Home (Opcional)
[ ] Smart Home skill habilitada [ ] Discovery de dispositivos funcionando [ ] PowerController implementado [ ] Teste com device real
## Fase 6 — Publicacao
[ ] Teste completo de todas funcionalidades [ ] Performance OK (< 8s timeout) [ ] Certificacao Amazon submetida [ ] Publicado na Alexa Skills Store
---
## 11. Comandos Rapidos
| Acao | Comando |
|------|---------|
| Criar skill | `ask new --template hello-world` |
| Deploy | `ask deploy` |
| Simular | `ask simulate --text "abre a auri"` |
| Dialog interativo | `ask dialog --locale pt-BR` |
| Ver logs | `ask smapi get-skill-simulation` |
| Validar modelo | `ask validate --locales pt-BR` |
| Exportar skill | `ask smapi export-package --skill-id ID` |
| Listar skills | `ask list skills` |
---
## 12. Referencias
- Boilerplate Python completo: `assets/boilerplate/lambda_function.py`
- Interaction model PT-BR: `assets/interaction-models/pt-BR.json`
- APL chat template: `assets/apl-templates/chat-interface.json`
- Smart Home examples: `references/smart-home-api.md`
- ASK SDK Python docs: https://github.com/alexa/alexa-skills-kit-sdk-for-python
- Claude + Alexa guide: https://www.anthropic.com/news/claude-and-alexa-plus
## Best Practices
- Provide clear, specific context about your project and requirements
- Review all suggestions before applying them to production code
- Combine with other complementary skills for comprehensive analysis
## Common Pitfalls
- Using this skill for tasks outside its domain expertise
- Applying recommendations without understanding your specific context
- Not providing enough project context for accurate analysis
## Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
Frequently asked questions about Amazon Alexa Integration
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