以下为本文档的中文说明

amazon-alexa 技能提供了与 Amazon Alexa 平台的完整集成能力,专注于创建智能语音技能、将 Alexa 设备转变为以 Claude 为 AI 大脑的超智能助手(项目代号 Auri),并与 AWS 生态系统深度整合。该技能的核心功能涵盖多个层面:语音技能开发方面,可以利用 Alexa Skills Kit 创建自定义语音交互应用;智能增强方面,通过将 Claude 作为大语言模型后端,赋予 Alexa 高级对话理解和生成能力;AWS 生态集成方面,与 Lambda 无服务器计算、DynamoDB 数据库、Polly 语音合成、Transcribe 语音识别、Lex 对话机器人和 Smart Home 智能家居等多项 AWS 服务无缝对接。使用场景包括:构建具备自然对话能力的智能语音助手;开发智能家居控制语音接口;创建面向特定业务领域的 Alexa Skill;以及将现有 Alexa 设备升级为具备 AI 大脑的智能终端。核心特点是将 Alexa 的语音交互前端能力与 Claude 的高级语言理解能力相结合,实现神经网络语音合成、持久化记忆和全面的设备控制。该技能要求开发者具备 Alexa 技能开发和 AWS 服务使用的基础知识,但提供了一套完整的工作流来指导从需求分析到部署上线的全过程。通过这种集成,开发者可以创造出远超传统语音助手能力的智能语音应用。

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


## 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": {"va
lue": "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\
ri 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

<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, conte
xt):
    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: `asse
ts/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.
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