Communitygithub.com

curiositech/windags-skills

Constructor de infraestructura AWS CDK usando TypeScript con constructos L2/L3 y patrones de Well-Architected. Activar en: AWS CDK, CDK construct, CDK stack, CDK pipeline, AWS infrastructure as code TypeScript, L2 construct, CDK patterns. NO para: Terraform IaC (usar terraform-module-builder), Kubernetes manifests (usar kubernetes-manifest-generator), serverless framework (usar devops-automator).

¿Qué es windags-skills?

Este skill especializa a un agente de IA como constructor experto de infraestructura AWS utilizando CDK (Cloud Development Kit) con TypeScript, enfocándose en constructos L2/L3 y patrones del Marco de Well-Architected. Está diseñado para desarrolladores que trabajan con CDK 2.180+, CDK CLI, y servicios como Lambda, API Gateway, ECS Fargate, y S3. El skill guía al usuario en la creación de stacks organizados (stateful vs stateless), el uso de constructos de alto nivel para evitar configuraciones inseguras, y la implementación de CDK Pipelines auto-mutantes para CI/CD. Además, promueve buenas prácticas como la validación de cumplimiento con cdk-nag (AwsSolutions, NIST, HIPAA, PCI) y pruebas de snapshot. Es útil para cualquier desarrollador que desee construir infraestructura AWS mantenible, segura y siguiendo estándares recomendados. Sin embargo, no está destinado a Terraform, Kubernetes o Serverless Framework, que tienen skills dedicados. El agente activa automáticamente este skill cuando detecta términos como "AWS CDK", "CDK construct", "CDK stack" o "cdk deploy".

Compatible con~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/curiositech/windags-skills/tree/HEAD/skills/aws-cdk-builder

Preguntar en tu IA favorita

Abre un nuevo chat con esta habilidad de agente ya precargada.

Documentación

Constructor AWS CDK

Experto en construir infraestructura AWS usando CDK con TypeScript, aprovechando constructos L2/L3 y patrones del Marco de Well-Architected.

Disparadores de Activación

Activar en: "AWS CDK", "CDK construct", "CDK stack", "CDK pipeline", "AWS IaC TypeScript", "L2 construct", "CDK patterns", "cdk deploy", "cdk synth"

NO para: Terraform IaC → terraform-module-builder | Manifiestos Kubernetes → kubernetes-manifest-generator | Serverless Framework → devops-automator

Inicio Rápido

  1. Inicializar app CDK — npx cdk init app --language typescript
  2. Diseñar estructura de stacks — separar stateful (bases de datos, buckets) de stateless (cómputo, APIs)
  3. Usar constructos L2 — preferir constructos de alto nivel sobre recursos L1 de CloudFormation
  4. Agregar CDK Nag — verificación automatizada de cumplimiento Well-Architected
  5. Desplegar con CDK Pipelines — pipeline CI/CD auto-mutante

Capacidades Principales

DominioTecnologías
CDK CoreCDK 2.180+, Constructs library, CDK CLI, cdk.json
Constructos L2/L3aws-lambda, aws-apigateway, aws-ecs-patterns, aws-rds
Cumplimientocdk-nag (paquetes AwsSolutions, NIST, HIPAA, PCI)
CI/CDCDK Pipelines, CodePipeline, CodeBuild, auto-mutación
PatronesPatrones ECS Fargate, API Gateway + Lambda, S3 + CloudFront

Patrones de Arquitectura

Organización de Stacks (Stateful vs Stateless)

// bin/app.ts — app de nivel superior con separación de entornos
const app = new cdk.App();

// Stack stateful — rara vez cambia, cuidado con actualizaciones
const dataStack = new DataStack(app, 'Data-Prod', {
  env: { account: '123456789', region: 'us-east-1' },
});

// Stack stateless — desplegado frecuentemente, seguro de destruir/recrear
const apiStack = new ApiStack(app, 'Api-Prod', {
  env: { account: '123456789', region: 'us-east-1' },
  database: dataStack.database,
  bucket: dataStack.bucket,
});

// Pipeline stack — CI/CD auto-mutante
new PipelineStack(app, 'Pipeline', {
  env: { account: '123456789', region: 'us-east-1' },
});

Constructo L2 con Mejores Prácticas

// lib/api-stack.ts
export class ApiStack extends cdk.Stack {
  constructor(scope: Construct, id: string, props: ApiStackProps) {
    super(scope, id, props);

    const handler = new lambda.Function(this, 'Handler', {
      runtime: lambda.Runtime.NODEJS_22_X,
      handler: 'index.handler',
      code: lambda.Code.fromAsset('lambda/'),
      memorySize: 256,
      timeout: cdk.Duration.seconds(30),
      tracing: lambda.Tracing.ACTIVE,       // X-Ray
      insightsVersion: lambda.LambdaInsightsVersion.VERSION_1_0_229_0,
      environment: {
        TABLE_NAME: props.table.tableName,
        POWERTOOLS_SERVICE_NAME: 'api',     // Lambda Powertools
      },
    });

    props.table.grantReadWriteData(handler); // Mínimo privilegio

    const api = new apigw.RestApi(this, 'Api', {
      deployOptions: {
        tracingEnabled: true,
        metricsEnabled: true,
        throttlingRateLimit: 1000,
        throttlingBurstLimit: 500,
      },
    });

    api.root.addResource('items').addMethod('GET',
      new apigw.LambdaIntegration(handler));
  }
}

CDK Pipelines (Auto-Mutantes)

Fuente (GitHub) → Synth (cdk synth) → Auto-Mutación
    │                                      │
    ▼                                      ▼
UpdatePipeline ─── Desplegar Staging ─── Aprobación Manual ─── Desplegar Prod
                        │                                      │
                    Pruebas de Integración                 Pruebas de Humo

Anti-Patrones

  1. Constructos L1 en todas partes — usar CfnBucket en lugar de s3.Bucket. Los constructos L2 codifican mejores prácticas (cifrado, registro, control de acceso) por defecto.
  2. Stacks monolíticos — un stack con 200+ recursos alcanza límites de CloudFormation y se despliega lentamente. Dividir en stacks stateful/stateless con referencias entre stacks.
  3. Falta de cdk-nag — desplegar sin verificaciones de cumplimiento. Agregar Aspects.of(app).add(new AwsSolutionsChecks()) para detectar problemas de seguridad antes del despliegue.
  4. Cuenta/región hardcodeadas — account: '123456789' en código de constructo. Usar contexto de cdk.json o búsqueda cdk.Environment para portabilidad.
  5. Sin pruebas de snapshot — CDK genera plantillas CloudFormation que cambian inesperadamente. Agregar pruebas expect(template).toMatchSnapshot() para detectar cambios no intencionados.

Lista de Verificación de Calidad

[ ] Stacks separados: stateful (datos) vs stateless (cómputo)
[ ] Constructos L2/L3 usados (no CloudFormation L1 directo)
[ ] cdk-nag habilitado con paquete AwsSolutions
[ ] Pruebas de snapshot para todos los stacks
[ ] CDK Pipelines para CI/CD auto-mutante
[ ] IAM de mínimo privilegio mediante métodos grant (grantRead, grantWrite)
[ ] cdk synth produce CloudFormation válido
[ ] Referencias entre stacks usan salidas exportadas
[ ] Políticas de eliminación establecidas (RETAIN para datos de producción, DESTROY para desarrollo)
[ ] Etiquetas aplicadas mediante Aspects para asignación de costos
[ ] cdk diff revisado antes de cada despliegue
[ ] Funciones Lambda usan Powertools para observabilidad

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

curiositech/windags-skills

Expert in 2000s-era music visualization (Milkdrop, AVS, Geiss) and modern WebGL implementations. Specializes in Butterchurn integration, Web Audio API AnalyserNode FFT data, GLSL shaders for audio-reactive visuals, and psychedelic generative art. Activate on "Milkdrop", "music visualization", "WebGL visualizer", "Butterchurn", "audio reactive", "FFT visualization", "spectrum analyzer". NOT for simple bar charts/waveforms (use basic canvas), video editing, or non-audio visuals.

curiositech/windags-skills

Expert legal research agent for finding and scraping expungement data state by state. Knows authoritative sources, URL patterns, Firecrawl configuration, and 2026 legal landscape.

curiositech/windags-skills

Expert in 3D computer vision labeling tools, workflows, and AI-assisted annotation for LiDAR, point clouds, and sensor fusion. Covers SAM4D/Point-SAM, human-in-the-loop architectures, and vertical-specific training strategies. Activate on '3D labeling', 'point cloud annotation', 'LiDAR labeling', 'SAM 3D', 'SAM4D', 'sensor fusion annotation', '3D bounding box', 'semantic segmentation point cloud'. NOT for 2D image labeling (use clip-aware-embeddings), general ML training (use ml-engineer), video annotation without 3D (use computer-vision-pipeline), or VLM prompt engineering (use prompt-engineer).

curiositech/windags-skills

Implement WCAG 2.2 AA/AAA compliance with automated testing, keyboard navigation, screen reader support, and focus management. Activate on: accessibility audit, WCAG compliance, keyboard navigation, screen reader, aria attributes, axe-core, focus trap. NOT for: design-level accessibility review (use design-accessibility-auditor), color contrast only (use css-in-js-architect).

curiositech/windags-skills

Time-blind friendly planning, executive function support, and daily structure for ADHD brains. Specializes in realistic time estimation, dopamine-aware task design, and building systems that actually work for neurodivergent minds.

curiositech/windags-skills

Designs digital experiences for ADHD brains using neuroscience research and UX principles. Expert in reducing cognitive load, time blindness solutions, dopamine-driven engagement, and compassionate design patterns. Activate on 'ADHD design', 'cognitive load', 'accessibility', 'neurodivergent UX', 'time blindness', 'dopamine-driven', 'executive function'. NOT for general accessibility (WCAG only), neurotypical UX design, or simple UI styling without ADHD context.

curiositech/windags-skills

>- Apply crisis decision-making research to agent routing, uncertainty triage, and coordination failure analysis in time-pressured systems. Use when diagnosing handoff failures, analytical paralysis, or expert judgment under incomplete information. NOT for routine coding, simple CRUD design, or static single-agent tasks with complete information.

curiositech/windags-skills

Extend and modify the admin dashboard, developer portal, and operations console. Use when adding new admin tabs, metrics, monitoring features, or internal tools. Activates for dashboard development, analytics, user management, and internal tooling.

curiositech/windags-skills

Conversation patterns and interaction protocols for multi-agent systems. Covers request/response, pub/sub, blackboard, delegation chains, debate, critique, consensus, fan-out/fan-in, supervisor-worker, and peer negotiation. Deep analysis of AutoGen conversation patterns, CrewAI delegation, LangGraph state passing, and FIPA-ACL performatives. Teaches how to design what agents say to each other and in what order. Activate on: "agent conversation", "agent protocol", "multi-agent debate", "agent delegation", "supervisor worker pattern", "agent voting", "consensus protocol", "fan-out fan-in", "agent negotiation", "blackboard pattern", "agent dialogue", "conversation topology", "agent handoff". NOT for: wire format or serialization (use agent-interchange-formats), orchestration infrastructure (use agentic-infrastructure-2026), single agent behavior (use agentic-patterns).

curiositech/windags-skills

Meta-agent for creating new custom agents, skills, and MCP integrations. Expert in agent design, MCP development, skill architecture, and rapid prototyping. Activate on 'create agent', 'new skill', 'MCP server', 'custom tool', 'agent design'. NOT for using existing agents (invoke them directly), general coding (use language-specific skills), or infrastructure setup (use deployment-engineer).

curiositech/windags-skills

AI-powered calendar management and agent-based scheduling coordination. Covers calendar APIs (Google Calendar, CalDAV/iCal), AI scheduling assistants (Reclaim, Clockwise, Motion, Cal.com), building custom calendar agents with MCP, multi-calendar merging, timezone management, focus block protection, meeting fatigue detection, and agent-to-agent meeting negotiation protocols. Activate on: "calendar agent", "AI scheduling", "calendar coordination", "meeting scheduling", "calendar API", "focus time protection", "calendar optimization", "Google Calendar MCP", "Reclaim", "Clockwise", "Motion", "Cal.com", "smart scheduling", "calendar-aware agent", "timezone scheduling", "agent negotiation meetings". NOT for: manual calendar UI component design (use form-validation-architect), project management scheduling or Gantt charts (use project-management-guru-adhd), general time-tracking or pomodoro apps (use adhd-daily-planner for time-awareness), building the agent itself from scratch (use agent-creator).

curiositech/windags-skills

Build and adopt production AI agent infrastructure in 2026. Covers framework selection (LangGraph, CrewAI, AutoGen, MCP), orchestration patterns, evaluation, observability, memory systems, and tool use. Also covers the SOCIAL dimension: how to sell agent infrastructure internally, change management, measuring ROI, building trust in autonomous systems, and scaling adoption across teams. Activate on: "agent infrastructure", "agent framework comparison", "which agent framework", "sell AI tools internally", "agent adoption", "agent observability", "agent evaluation", "MCP architecture", "agentic mesh", "enterprise AI agents", "AI change management", "agent ROI". NOT for: building specific agents (use ai-engineer), designing agent behavior patterns (use agentic-patterns), prompt tuning (use prompt-engineer).

curiositech/windags-skills

Fundamental patterns for effective agentic behavior. Teaches decomposition, tool orchestration, error recovery, context management, quality self-assessment, and knowing when to stop. Model-agnostic principles that make any agent more effective regardless of domain. Activate on: "how should I structure this agent", "agentic workflow", "agent patterns", "multi-step task", "tool orchestration", "/agentic-patterns", "decompose this", "agent best practices", "chain of actions", "when should the agent stop", "agent loop design". NOT for: creating agent infrastructure (use agent-creator), building DAGs (use windags-architect), specific tool implementation.

curiositech/windags-skills

Automated discovery and matching of agent skills for dynamic task routing and capability assessment

curiositech/windags-skills

Cryptographic security for agentic systems — zero-trust agent networking, signed message envelopes (JWS/JWE), capability-based security (ocaps), Merkle tree audit trails, WASM sandboxing, and formal verification. Covers CLI dev tool security, mTLS between agents, permission boundaries (least privilege for AI agents), and supply chain security for skills/plugins. Activate on: "agent security", "zero trust agents", "secure agent communication", "capability-based security", "ocap", "signed messages between agents", "agent audit trail", "sandbox agent execution", "agent permissions", "mTLS agents", "cryptographic verification", "agent supply chain", "OWASP agentic", "prove agent did X", "tamper-proof agent logs". NOT for: application-level SAST scanning (use security-auditor), network firewall rules (use infrastructure), SOC2/HIPAA compliance (organizational), or prompt injection defense (use prompt-engineer).

curiositech/windags-skills

Data structures and serialization formats for agent-to-agent communication. Covers message envelopes, structured output schemas, capability declarations, task handoff payloads, error/retry signaling, and context windows as data structures. Deep comparison of A2A protocol, MCP, OpenAI function calling, and LangChain message types. Teaches when to use rigid schemas vs free-form with validation, typed vs untyped, streaming vs batch. Activate on: "agent message format", "agent communication schema", "agent-to-agent protocol", "A2A protocol", "MCP message format", "structured output for agents", "agent interop", "interchange format", "agent serialization", "task handoff format", "capability declaration". NOT for: what agents say to each other (use agent-conversation-protocols), orchestration topology (use multi-agent-coordination), building agent infrastructure (use agentic-infrastructure-2026).

curiositech/windags-skills

Logic-based agent programming language implementing BDI architecture for practical autonomous agent development

curiositech/windags-skills

>- Design AgentSpeak(L)-style BDI agents with context-guarded plans, selection functions, and intention stacks. Use for interruptible autonomy, agent policy, and multi-agent orchestration in dynamic environments. NOT for simple rule engines, static planners, or centralized workflows.

curiositech/windags-skills

Foundational concurrent computation model where actors communicate exclusively through asynchronous message passing

curiositech/windags-skills

license: Apache-2.0 NOT for unrelated tasks outside this domain.

Skills relacionados