amazon-alexa

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).

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Best use case

amazon-alexa is best used when you need a repeatable AI agent workflow instead of a one-off prompt. It is especially useful for teams working in multi. 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).

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).

Users should expect a more consistent workflow output, faster repeated execution, and less time spent rewriting prompts from scratch.

Practical example

Example input

Use the "amazon-alexa" skill to help with this workflow task. Context: 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).

Example output

A structured workflow result with clearer steps, more consistent formatting, and an output that is easier to reuse in the next run.

When to use this skill

  • Use this skill when you want a reusable workflow rather than writing the same prompt again and again.

When not to use this skill

  • Do not use this when you only need a one-off answer and do not need a reusable workflow.
  • Do not use it if you cannot install or maintain the related files, repository context, or supporting tools.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/amazon-alexa/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/amazon-alexa/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/amazon-alexa/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How amazon-alexa Compares

Feature / Agentamazon-alexaStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

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).

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# AMAZON 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

```bash

## 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

```json
{
  "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

```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

```json
{
  "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)

```python
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

```python
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

```xml
<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

```json
{
  "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

```python
@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:
```json
{
  "apis": {
    "smartHome": {
      "endpoint": {
        "uri": "arn:aws:lambda:us-east-1:123456789:function:auri-smart-home"
      }
    }
  }
}
```

## 8.2 Handler De Smart Home

```python
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

```python
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

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