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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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Install

skills CLI npx skills add https://github.com/sickn33/agentic-awesome-skills/tree/main/skills/amazon-alexa
Claude Code claude plugin marketplace add https://llmmart.ai/marketplace.json && claude plugin install sickn33-agentic-awesome-skills@llmmart
Git git clone https://github.com/sickn33/agentic-awesome-skills.git

The skills CLI installs just this skill, for any of its supported agents. Claude Code installs the whole sickn33/agentic-awesome-skills collection as a plugin from our marketplace. Git is the plain clone.

Skill manifest

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": {"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.
Files (agentic-awesome-skills)
  • SKILL.md 17.5 KB
    ---
    name: amazon-alexa
    description: "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)."
    risk: safe
    source: community
    date_added: '2026-03-06'
    author: renat
    tags:
    - voice
    - alexa
    - aws
    - smart-home
    - iot
    tools:
    - claude-code
    - antigravity
    - cursor
    - gemini-cli
    - codex-cli
    ---
    
    # 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
    
    ## 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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