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Found 70 Skills
The Fifteen-Factor App methodology for modern cloud-native SaaS applications. This skill should be automatically invoked when planning SaaS tools, product software architecture, microservices design, PRPs/PRDs, or cloud-native application development. Extends the original Twelve-Factor App principles with three additional factors (API First, Telemetry, Security). Trigger keywords include "fifteen factor", "12 factor", "SaaS architecture", "cloud-native design", "application architecture", "microservices best practices", or when in a planning/architecture session.
Implement applications using Google Cloud Platform (GCP) services. Use when building on GCP infrastructure, selecting compute/storage/database services, designing data analytics pipelines, implementing ML workflows, or architecting cloud-native applications with BigQuery, Cloud Run, GKE, Vertex AI, and other GCP services.
Twelve-factor app methodology. Use for cloud-native apps.
Adds .NET Aspire cloud-native orchestration to existing .NET solutions. Analyzes solution structure to identify services (APIs, web apps, workers), creates AppHost and ServiceDefaults projects, configures service discovery, adds NuGet packages, and sets up distributed application orchestration. Use when adding Aspire to .NET solutions or creating new cloud-ready distributed applications.
Set up and manage local Kubernetes clusters using KIND (Kubernetes IN Docker). Use when testing Kubernetes applications locally or developing cloud-native workloads.
Modern security standards including Zero Trust Architecture, supply chain security, DevSecOps integration, and cloud-native protection
Docker, Kubernetes, container orchestration, and cloud-native deployment for data applications
Comprehensive geospatial science skill covering remote sensing, GIS, spatial analysis, machine learning for earth observation, and 30+ scientific domains. Supports satellite imagery processing (Sentinel, Landsat, MODIS, SAR, hyperspectral), vector and raster data operations, spatial statistics, point cloud processing, network analysis, cloud-native workflows (STAC, COG, Planetary Computer), and 8 programming languages (Python, R, Julia, JavaScript, C++, Java, Go, Rust) with 500+ code examples. Use for remote sensing workflows, GIS analysis, spatial ML, Earth observation data processing, terrain analysis, hydrological modeling, marine spatial analysis, atmospheric science, and any geospatial computation task.
Java Quarkus development guidelines for building cloud-native applications with fast startup, minimal memory footprint, and GraalVM native builds
Guide for implementing HolmesGPT - an AI agent for troubleshooting cloud-native environments. Use when investigating Kubernetes issues, analyzing alerts from Prometheus/AlertManager/PagerDuty, performing root cause analysis, configuring HolmesGPT installations (CLI/Helm/Docker), setting up AI providers (OpenAI/Anthropic/Azure), creating custom toolsets, or integrating with observability platforms (Grafana, Loki, Tempo, DataDog).
Expert in Kubernetes and DevOps with infrastructure-as-code and cloud-native patterns
Aspire orchestration for cloud-native distributed applications in any language (C#, Python, Node.js, Go). Handles dependency management, local dev with Docker, Azure deployment, service discovery, and observability dashboards. Use when setting up microservices, containerized apps, or polyglot distributed systems.