Kubernetes
Kubernetes orchestration
encore-getting-started
by encoredev
Get started with Encore.ts - create and run your first app.
analyzing-source
by Sawyer-Middeleer
Conducts in-depth analysis of a specific source or topic, producing comprehensive summaries for research synthesis. Use when you need detailed analysis and documentation of individual sources as part of a larger research effort.
coolify-deploy
by v1truv1us
Deploy to Coolify with best practices
flux
by vdesjardins
FluxCD is the standard GitOps approach for Kubernetes - diagnose issues, manage resources, and optimize deployments using declarative configuration synced from Git
looking-up-docs
by julianobarbosa
Look up library documentation using Context7. Use when needing API reference, library docs, framework documentation, or technical documentation lookup. Provides up-to-date, version-specific docs and code examples.
cloudflare-zero-trust
by acedergren
Use when working with Cloudflare Tunnel or Access - tunnel setup, authentication configuration, 502 Bad Gateway errors, Docker/Kubernetes deployment, service token management, private network routing (SSH/RDP/databases), WebSocket/gRPC connection issues, replica scaling problems, WARP routing, Terraform/IaC automation, local development with quick tunnels, audit logging setup, compliance requirements (SOC2/HIPAA), or advanced network debugging. Keywords - cloudflared, 502 error, service tokens, terraform, metrics port 20241, trycloudflare, Logpush, SIEM. CRITICAL - Authentication mandatory not optional.
mermaid
by ahgraber
Generate Mermaid diagrams for chatbot flows that render in Markdown, including choosing diagram types, producing valid Mermaid code blocks, and validating or rendering diagrams locally via the bundled scripts. Use when a user asks for chatbot flowcharts/sequence/state diagrams, wants Mermaid syntax, or needs to verify/render Mermaid without a web service.
effect-ts
by PaulRBerg
This skill should be used when the user asks about Effect-TS patterns, services, layers, error handling, service composition, or writing/refactoring code that imports from 'effect'. Also covers Effect + Next.js integration with @prb/effect-next.
configuring-firewalls
by ancoleman
Configure host-based firewalls (iptables, nftables, UFW) and cloud security groups (AWS, GCP, Azure) with practical rules for common scenarios like web servers, databases, and bastion hosts. Use when exposing services, hardening servers, or implementing network segmentation with defense-in-depth strategies.
Bankr Agent - Token Deployment
by BankrBot
This skill should be used when the user asks to "deploy token", "create token", "launch token", "Clanker", "claim fees", "token metadata", "update token", "mint new token", or any token deployment operation. Provides guidance on deploying ERC20 tokens via Clanker.
docker-containerization
by ailabs-393
This skill should be used when containerizing applications with Docker, creating Dockerfiles, docker-compose configurations, or deploying containers to various platforms. Ideal for Next.js, React, Node.js applications requiring containerization for development, production, or CI/CD pipelines. Use this skill when users need Docker configurations, multi-stage builds, container orchestration, or deployment to Kubernetes, ECS, Cloud Run, etc.
helm-charts
by cosmonic-labs
Expert guidance for authoring and maintaining Helm charts following standardized conventions, global registry support, templating best practices, and Kubernetes deployment patterns.
helm-best-practices
by cosmonic-labs
Expert guidance for authoring and maintaining Helm charts following standardized conventions, global registry support, templating best practices, and Kubernetes deployment patterns.
vercel-deploy
by JochenYang
Deploy projects to Vercel with one command. Use when user wants to deploy to Vercel, publish website, or needs production/preview deployment. Triggers on: "deploy to vercel", "vercel deploy", "发布到vercel", "部署到线上".
load-balancing-patterns
by ancoleman
When distributing traffic across multiple servers or regions, use this skill to select and configure the appropriate load balancing solution (L4/L7, cloud-managed, self-managed, or Kubernetes ingress) with proper health checks and session management.
optimizing-costs
by ancoleman
Optimize cloud infrastructure costs through FinOps practices, commitment discounts, right-sizing, and automated cost management. Use when reducing cloud spend, implementing budget controls, or establishing cost visibility across AWS, Azure, GCP, and Kubernetes environments.
model-serving
by ancoleman
LLM and ML model deployment for inference. Use when serving models in production, building AI APIs, or optimizing inference. Covers vLLM (LLM serving), TensorRT-LLM (GPU optimization), Ollama (local), BentoML (ML deployment), Triton (multi-model), LangChain (orchestration), LlamaIndex (RAG), and streaming patterns.
deploying-on-azure
by ancoleman
Design and implement Azure cloud architectures using best practices for compute, storage, databases, AI services, networking, and governance. Use when building applications on Microsoft Azure or migrating workloads to Azure cloud platform.
implementing-gitops
by ancoleman
Implement GitOps continuous delivery for Kubernetes using ArgoCD or Flux. Use for automated deployments with Git as single source of truth, pull-based delivery, drift detection, multi-cluster management, and progressive rollouts.
implementing-service-mesh
by ancoleman
Implement production-ready service mesh deployments with Istio, Linkerd, or Cilium. Configure mTLS, authorization policies, traffic routing, and progressive delivery patterns for secure, observable microservices. Use when setting up service-to-service communication, implementing zero-trust security, or enabling canary deployments.
implementing-mlops
by ancoleman
Strategic guidance for operationalizing machine learning models from experimentation to production. Covers experiment tracking (MLflow, Weights & Biases), model registry and versioning, feature stores (Feast, Tecton), model serving patterns (Seldon, KServe, BentoML), ML pipeline orchestration (Kubeflow, Airflow), and model monitoring (drift detection, observability). Use when designing ML infrastructure, selecting MLOps platforms, implementing continuous training pipelines, or establishing model governance.
administering-linux
by ancoleman
Manage Linux systems covering systemd services, process management, filesystems, networking, performance tuning, and troubleshooting. Use when deploying applications, optimizing server performance, diagnosing production issues, or managing users and security on Linux servers.
deploying-on-gcp
by ancoleman
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.
deploying-on-aws
by ancoleman
Selecting and implementing AWS services and architectural patterns. Use when designing AWS cloud architectures, choosing compute/storage/database services, implementing serverless or container patterns, or applying AWS Well-Architected Framework principles.