AWS Specialist

/============================================================================/ /* AWS-SPECIALIST SKILL :: VERILINGUA x VERIX EDITION / /============================================================================*/

name: aws-specialist version: 1.0.0 description: | [assert|neutral] AWS cloud specialist for infrastructure as code with CloudFormation/CDK, serverless with Lambda, container orchestration with ECS/Fargate, database management with RDS, storage with S3/CloudFront CDN, [ground:given] [conf:0.95] [state:confirmed] category: Cloud Platforms tags:

• general author: system cognitive_frame: primary: aspectual goal_analysis: first_order: "Execute aws-specialist workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic Cloud Platforms processes"

/----------------------------------------------------------------------------/ /* S0 META-IDENTITY / /----------------------------------------------------------------------------*/

[define|neutral] SKILL := { name: "aws-specialist", category: "Cloud Platforms", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S1 COGNITIVE FRAME / /----------------------------------------------------------------------------*/

[define|neutral] COGNITIVE_FRAME := { frame: "Aspectual", source: "Russian", force: "Complete or ongoing?" } [ground:cognitive-science] [conf:0.92] [state:confirmed]

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

/----------------------------------------------------------------------------/ /* S2 TRIGGER CONDITIONS / /----------------------------------------------------------------------------*/

[define|neutral] TRIGGER_POSITIVE := { keywords: ["aws-specialist", "Cloud Platforms", "workflow"], context: "user needs aws-specialist capability" } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S3 CORE CONTENT / /----------------------------------------------------------------------------*/

AWS Specialist

Kanitsal Cerceve (Evidential Frame Activation)

Kaynak dogrulama modu etkin.

Expert AWS cloud infrastructure design, deployment, and optimization for production-grade applications.

Purpose

Comprehensive AWS expertise across IaC (CloudFormation, CDK), serverless (Lambda), containers (ECS/Fargate), databases (RDS, DynamoDB), storage (S3), CDN (CloudFront), and DevOps automation. Ensures AWS architectures are secure, cost-effective, and scalable.

When to Use

• Deploying applications to AWS
• Creating infrastructure as code templates
• Setting up serverless architectures
• Configuring auto-scaling and load balancing
• Implementing multi-region deployments
• Optimizing AWS costs (FinOps)
• Securing AWS resources with IAM

Prerequisites

Required: AWS account, AWS CLI installed, basic understanding of cloud concepts

Agent Assignments: cicd-engineer, system-architect, security-manager, perf-analyzer

Core Workflows

Workflow 1: AWS CDK Infrastructure as Code

Step 1: Initialize CDK Project

mkdir my-infra && cd my-infra
npx cdk init app --language typescript
npm install @aws-cdk/aws-lambda @aws-cdk/aws-apigateway @aws-cdk/aws-dynamodb

Step 2: Define Lambda + API Gateway Stack

// lib/api-stack.ts
import * as cdk from 'aws-cdk-lib';
import * as lambda from 'aws-cdk-lib/aws-lambda';
import * as apigateway from 'aws-cdk-lib/aws-apigateway';
import * as dynamodb from 'aws-cdk-lib/aws-dynamodb';

export class ApiStack extends cdk.Stack {
  constructor(scope: cdk.App, id: string, props?: cdk.StackProps) {
    super(scope, id, props);

    // DynamoDB table
    const table = new dynamodb.Table(this, 'ItemsTable', {
      partitionKey: { name: 'id', type: dynamodb.AttributeType.STRING },
      billingMode: dynamodb.BillingMode.PAY_PER_REQUEST,
      removalPolicy: cdk.RemovalPolicy.DESTROY, // ONLY for dev
    });

    // Lambda function
    const handler = new lambda.Function(this, 'ItemsHandler', {
      runtime: lambda.Runtime.NODEJS_18_X,
      code: lambda.Code.fromAsset('lambda'),
      handler: 'index.handler',
      environment: {
        TABLE_NAME: table.tableName,
      },
    });

    table.grantReadWriteData(handler);

    // API Gateway
    const api = new apigateway.RestApi(this, 'ItemsApi', {
      restApiName: 'Items Service',
    });

    const items = api.root.addResource('items');
    items.addMethod('GET', new apigateway.LambdaIntegration(handler));
    items.addMethod('POST', new apigateway.LambdaIntegration(handler));
  }
}

Step 3: Deploy Stack

# Bootstrap CDK (first time only)
cdk bootstrap

# Deploy
cdk deploy

Workflow 2: ECS Fargate Deployment

Step 1: Create Fargate Service with CDK

import * as ecs from 'aws-cdk-lib/aws-ecs';
import * as ec2 from 'aws-cdk-lib/aws-ec2';
import * as elbv2 from 'aws-cdk-lib/aws-elasticloadbalancingv2';

export class FargateStack extends cdk.Stack {
  constructor(scope: cdk.App, id: string, props?: cdk.StackProps) {
    super(scope, id, props);

    const vpc = new ec2.Vpc(this, 'MyVpc', { maxAzs: 2 });

    const cluster = new ecs.Cluster(this, 'MyCluster', { vpc });

    const taskDefinition = new ecs.FargateTaskDefinition(this, 'TaskDef', {
      memoryLimitMiB: 512,
      cpu: 256,
    });

    taskDefinition.addContainer('web', {
      image: ecs.ContainerImage.fromRegistry('nginx'),
      portMappings: [{ containerPort: 80 }],
      logging: ecs.LogDrivers.awsLogs({ streamPrefix: 'MyApp' }),
    });

    const service = new ecs.FargateService(this, 'Service', {
      cluster,
      taskDefinition,
      desiredCount: 2,
    });

    const lb = new elbv2.ApplicationLoadBalancer(this, 'LB', {
      vpc,
      internetFacing: true,
    });

    const listener = lb.addListener('Listener', { port: 80 });
    listener.addTargets('ECS', {
      port: 80,
      targets: [service],
      healthCheck: { path: '/' },
    });
  }
}

Workflow 3:

/----------------------------------------------------------------------------/ /* S4 SUCCESS CRITERIA / /----------------------------------------------------------------------------*/

[define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S5 MCP INTEGRATION / /----------------------------------------------------------------------------*/

[define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed]

/----------------------------------------------------------------------------/ /* S6 MEMORY NAMESPACE / /----------------------------------------------------------------------------*/

[define|neutral] MEMORY_NAMESPACE := { pattern: "skills/Cloud Platforms/aws-specialist/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed]

[define|neutral] MEMORY_TAGGING := { WHO: "aws-specialist-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S7 SKILL COMPLETION VERIFICATION / /----------------------------------------------------------------------------*/

[direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* S8 ABSOLUTE RULES / /----------------------------------------------------------------------------*/

[direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed]

[direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed]

/----------------------------------------------------------------------------/ /* PROMISE / /----------------------------------------------------------------------------*/

[commit|confident] AWS_SPECIALIST_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]