Explorar skills

Provides AWS CloudFormation patterns for VPC foundations, including subnets, route tables, internet and NAT gateways, endpoints, and reusable outputs. Use when creating a new network baseline, segmenting public and private workloads, or preparing CloudFormation networking stacks for application deployments.

Provides AWS Lambda integration patterns for Java with cold start optimization. Use when deploying Java functions to AWS Lambda, choosing between Micronaut and Raw Java approaches, optimizing cold starts below 1 second, configuring API Gateway or ALB integration, or implementing serverless Java applications. Triggers include "create lambda java", "deploy java lambda", "micronaut lambda aws", "java

Provides security review capability for TypeScript/Node.js applications, validates code against XSS, injection, CSRF, JWT/OAuth2 flaws, dependency CVEs, and secrets exposure. Use when performing security audits, before deployment, reviewing authentication/authorization implementations, or ensuring OWASP compliance for Express, NestJS, and Next.js. Triggers on "security review", "check for security

ML engineering skill for productionizing models, building MLOps pipelines, and integrating LLMs. Covers model deployment, feature stores, drift monitoring, RAG systems, and cost optimization.

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom mode

Use when designing GitHub Actions workflows, creating CI/CD pipelines, planning multi-environment deployments, optimizing pipeline cost and execution time, or implementing deployment strategies (blue-green, canary, rolling). Generates production-ready workflow YAML, analyzes existing pipelines for optimization, and creates deployment plans.

Programmatic page generation at scale using template-based SEO, data pipelines, and automated content production. Covers keyword pattern mining, template architecture, data sourcing, quality control, and indexation strategy for 100-100K+ page deployments.

Structured data implementation, validation, and optimization. Covers JSON-LD patterns for 20+ schema types, rich snippet eligibility, AI search visibility, Knowledge Graph optimization, and CMS-specific deployment guides.

EU AI Act (Regulation EU 2024/1689) compliance specialist. Use when classifying AI systems by risk tier, assessing provider or deployer obligations, evaluating GPAI model compliance, running conformity assessments, performing bias detection and fairness testing, building AI governance programs, or preparing for EU AI Act enforcement deadlines. Covers the full regulatory lifecycle from system inven

Expert MLOps engineering covering model deployment, ML pipelines, model monitoring, feature stores, and infrastructure automation. Use when deploying models to production, building training pipelines, setting up drift detection, configuring feature stores, or automating ML CI/CD workflows.

AI/ML feature PRD scaffolding for the modern AI product manager. Extends the standard 8-section PRD with 3 AI-specific sections covering model selection, evals, guardrails, data flow, deployment, failure modes, human-in-the-loop, AI metrics, ethical review, and cost monitoring.

Expert delivery management for release planning, deployment coordination, incident response, change management, and SLA tracking across continuous delivery pipelines. Use when planning a release, coordinating a deployment, responding to a production incident, evaluating change requests, calculating SLA/error budgets, or assessing delivery maturity.