DevOps & Infra

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Use this skill when building with Deno — TypeScript runtime, Deno Deploy, Fresh framework, Deno std library. This skill enforces: permission-based security, URL import system, std lib usage over npm, Fresh island architecture. Do NOT use for: Node.js projects, Bun projects, browser-only TypeScript.

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Trigger: "Azure", "Microsoft Azure", "Azure DevOps", "Azure Kubernetes", "AKS", "Azure Functions", "Azure App Service", "Azure Storage", "Azure SQL", "ARM template", "Bicep", "Azure CLI", "Azure pipeline", "Azure AD", "Managed Identity", "Azure Policy", "Azure Monitor", "Log Analytics", "Key Vault", "Azure Front Door", "Azure Firewall", "Private Link". Covers: compute (AKS, App Service, Functions, VMs), storage (Blob, Disk, Files), database (Azure SQL, Cosmos DB), networking (VNet, VPN, ExpressRoute), IaC (Bicep, ARM), security (Azure AD, Key Vault, Policy), monitoring, cost management, landing zone design (CAF). Exclusion: Not for AWS or GCP — use those specific skills.

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Use this skill when implementing MLOps: ML CI/CD pipelines, model deployment pipelines, model registry CI/CD, canary deploy ML, A/B testing ML, model monitoring, model drift, model rollback, feature store CI/CD. This skill enforces: CI/CD for model pipeline, registry promotion, canary/blue-green deployment, drift monitoring, rollback strategy. Do NOT use for: model training (use ml-training), feature engineering (use feature-engineering), data pipeline CI/CD (use devops-dataops).

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Use this skill when the user says 'Vault', 'HashiCorp Vault', 'secrets management', 'dynamic secrets', 'transit engine', 'Vault policy', 'Vault auth method', 'Vault agent', 'Vault injector', 'Vault API', 'kv-v2', 'PKI secrets engine', 'database secrets engine', 'Vault role', 'Vault token'. Covers: Vault setup, secrets engines, policies, auth methods, dynamic secrets, transit encryption, Vault Agent, Vault+Kubernetes integration. Do NOT use this for: AWS Secrets Manager, Azure Key Vault, or non-HashiCorp secret stores.

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Use this skill when asked about BI, dashboard, Metabase, Superset, Looker, Tableau, PowerBI, reporting, data visualization, business intelligence, KPI dashboards, semantic layer, embedded analytics, or LookML. This skill enforces: tool selection based on team size and use case, semantic layer design with business-friendly metrics, dashboard layout patterns (KPI, trend, comparison, funnel), embedded analytics via SDK/iFrame, data source configuration, caching strategy, permissions model with row-level security, and scheduling. Do NOT use for: data warehouse schema design, ETL pipeline configuration, or ad-hoc SQL queries.

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Trigger: "Docker", "container", "docker run", "docker compose", "Dockerfile", "containerize", "docker build", "docker network", "docker volume", "registry", "docker swarm", "container runtime", "OCI", "container security". Covers: Docker Engine, Docker Compose, multi-stage builds, registries, networking, volumes, security, CI/CD integration, Swarm orchestration, image optimization. Do NOT use for: Kubernetes (use kubernetes-patterns), CI pipeline design (use cicd-pipeline).

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Trigger: "FinOps", "cloud cost", "cost optimization", "cloud spend", "cost allocation", "reserved instance", "savings plan", "cost tagging", "cloud budget", "cost governance", "FinOps framework", "cloud economics" Exclusion: Not for infra provisioning -- use cloud-specific skills.

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Use this skill when the user says 'GitOps', 'ArgoCD', 'Flux', 'Git as source of truth', 'sync policy', 'drift detection', 'multi-env GitOps', 'Application CRD', 'Kustomize', 'Helm with GitOps', 'sync waves', 'phased rollouts'. Covers: declarative deployments, ArgoCD setup, Flux setup, sync strategies, drift detection, multi-environment promotion, secrets in GitOps. Do NOT use this for: plain Kubernetes manifests (use kubernetes-patterns), CI pipeline design, or monorepo tooling.

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Use this skill when the user says 'ABAC', 'attribute-based access control', 'fine-grained permissions', 'policy-based access control', 'OPA', 'Rego', 'XACML', 'attribute policies', 'context-aware authorization', 'dynamic permissions', 'risk-based access', 'environment-aware auth', 'conditional access', or when role-based permissions are insufficient and you need fine-grained control based on user attributes, resource properties, and environmental context. This skill covers: ABAC model (subject/resource/action/environment attributes), policy structure and combining algorithms, OPA/Rego implementation, hybrid RBAC-ABAC patterns, ABAC in applications, policy testing and simulation. Do NOT use for: basic role-based authorization, authentication flows, infrastructure policy (Kyverno/Gatekeeper), or Kubernetes admission control.

j4flmao Skill

Deploy the project to production. Only user-invocable — never auto-trigger.

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Use this skill when asked about data mesh, data product, domain ownership, self-serve data platform, federated governance, data-as-a-product, compute-plane architecture, or data topology. This skill enforces: data mesh four principles (domain ownership, data as product, self-serve platform, federated governance), data product definition with input/output ports, domain decomposition, cross-domain data sharing, and platform capability mapping. Do NOT use for: centralized data warehouse design, monolithic data platform architecture, or ETL pipeline implementation within a single domain.

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Use this skill when the user says 'Ansible', 'ansible-playbook', 'ansible-galaxy', 'playbook', 'inventory', 'role', 'task', 'module', 'ad-hoc command', 'configuration management', 'infrastructure automation', 'idempotent', 'Ansible Tower', 'AWX', 'Ansible Automation Platform'. Covers: playbooks, roles, inventory management, modules, variables, conditionals, loops, Jinja2 templates, vault encryption, Tower/AWX, collection development, CI/CD integration, idempotent automation. Do NOT use for: Terraform (use terraform), Puppet, Chef, SaltStack, or other configuration management tools.

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Use this skill when the user says 'ArgoCD', 'Argo CD', 'GitOps', 'ApplicationSet', 'Sync Policy', 'Sync Wave', 'Application Controller', 'argocd CLI', 'Declarative GitOps', 'Progressive Delivery', 'Rollback', 'Multi-cluster ArgoCD', 'ArgoCD RBAC', 'ArgoCD SSO', 'ArgoCD Project'. Covers: application deployment, sync strategies, application sets, multi-cluster management, RBAC, SSO integration, monitoring, rollback, disaster recovery, CLI usage, declarative setup. Do NOT use for: Flux (use gitops skill), generic GitOps concepts, Kubernetes cluster setup, CI/CD pipeline design.

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Use this skill when implementing DataOps: CI/CD for data pipelines, dbt CI/CD, SQLFluff, Great Expectations, data pipeline versioning, data testing in CI, data environment management, data contract CI, data lineage in CI/CD. Do NOT use for: data warehouse schema design (use data-warehouse), ETL pipeline design (use etl-pipeline), general CI/CD (use cicd-pipeline).

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Use this skill when the user says 'hetzner', 'hetzner cloud', 'hcloud', 'hetzner dedicated', 'hetzner robot', 'hetzner auction', 'hetzner server', 'hetzner kubernetes', 'hcloud terraform', 'hcloud packer', 'hcloud cli', 'CX', 'CCX', 'CAX', 'Hetzner Storage Box', 'Hetzner vSwitch', 'Hetzner Firewall', 'Hetzner Load Balancer', 'Hetzner Floating IP', 'Hetzner Placement Group', 'Hetzner ISO'. Covers: Hetzner Cloud resources (servers, networks, firewalls, load balancers, volumes), Hetzner Dedicated (Robot servers), Hetzner Storage Boxes, Kubernetes on Hetzner, cost optimization. Do NOT use for: other cloud providers (AWS, Azure, GCP, Oracle, IBM).

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Use this skill when the user says 'jenkins', 'jenkins pipeline', 'jenkinsfile', 'declarative pipeline', 'scripted pipeline', 'jenkins shared library', 'jenkins agent', 'jenkins node', 'jenkins plugin', 'jenkins blue ocean', 'jenkins credentials', 'jenkins multibranch', 'jenkins folder', 'jenkins job', 'jenkins groovy', 'pipeline as code', 'agent any', 'post block', 'when block', 'parallel pipeline', 'stage', 'declarative pipeline', 'scripted pipeline', 'pipeline syntax', 'jenkinsfile best practices', 'jenkins security', 'jenkins high availability', 'jenkins backup', 'jenkins casC', 'configuration as code', 'jenkins operator', 'jcasc', 'shared library', 'pipeline utility steps', 'jenkinsfile generator'. Covers: Jenkins pipeline development, shared libraries, multibranch pipelines, security hardening, high availability, configuration as code, plugin management, and operations.

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Use this skill when the user says 'CDN', 'edge', 'content delivery', 'CloudFront', 'Cloud CDN', 'Azure CDN', 'Akamai', 'Fastly', 'Cloudflare', 'edge computing', 'edge functions', 'WAF', 'DDoS protection', 'cache invalidation', 'signed URL', 'origin shield'. Covers: CDN architecture, caching strategies, edge computing (CloudFront Functions, Lambda@Edge, Cloudflare Workers, Fastly Compute@Edge), WAF rules, DDoS mitigation, CDN provider comparison, origin configuration, SSL/TLS, signed URLs/cookies. Do NOT use for: general DNS, Kubernetes ingress.

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Use this skill when the user says 'CircleCI', 'circleci config', 'orb', 'workflows', 'jobs', 'steps', 'executors', 'Docker executor', 'machine executor', 'CircleCI runner', 'pipeline', 'context', 'store_artifacts', 'save_cache', 'restore_cache', 'parallelism', 'circleci local', 'SSH debug'. Covers: CircleCI configuration (config.yml), executors, jobs, workflows, caching, orbs, matrix builds, contexts, parallel execution, self-hosted runners, pipeline parameters, triggers, artifacts, test splitting, SSH debug. Do NOT use for: GitHub Actions, GitLab CI, Jenkins, or other CI systems.

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Use this skill when deploying and managing Longhorn distributed storage on Kubernetes -- installation, volume management, backup, disaster recovery, performance tuning, monitoring. This skill enforces: minimum 3 nodes for production, replica count 3 for all production volumes, S3-compatible backup target, monitoring alerts for volume degraded and disk space. Do NOT use for: non-Kubernetes storage solutions, other CSI drivers, cloud-managed storage (EBS, GCE PD).

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Use this skill when asked about scikit-learn, XGBoost, LightGBM, CatBoost, regression, classification, clustering, ensemble, random forest, gradient boosting, SVM, PCA, feature importance, or cross-validation. This skill enforces: supervised learning pipelines (regression and classification metrics), ensemble methods (bagging, boosting, stacking), gradient boosting hyperparameter tuning (XGBoost, LightGBM, CatBoost), unsupervised learning (clustering dimensionality reduction), scikit-learn Pipeline and ColumnTransformer, cross-validation strategies, and imbalanced data handling. Do NOT use for: deep neural networks, reinforcement learning, or transformer models.

j4flmao Bundle

Use this skill when the user says 'backup', 'disaster recovery', 'DR', 'RPO', 'RTO', 'backup strategy', '3-2-1 rule', 'business continuity', 'disaster recovery plan', 'failover', 'failback', 'replication', 'snapshot', 'backup automation', 'backup validation', 'offsite backup', 'immutable backup', 'ransomware protection'. Covers: backup strategies (3-2-1 rule), disaster recovery planning, RPO/RTO definition, backup automation, replication, failover testing, cloud DR (pilot light, warm standby, multi-region), backup validation, compliance (SOC 2, HIPAA, PCI), ransomware recovery. Do NOT use for: database-specific replication (use database-migration), storage architecture design (use storage-infrastructure).

j4flmao Bundle

GitLab CI/CD pipeline configuration and management. Covers: .gitlab-ci.yml structure, stages, jobs, parallel, needs, artifacts, cache, child/parent pipelines, multi-project pipelines, rules, YAML anchors, templates, includes, Container Registry, Kaniko, security scanning (SAST, DAST, dependency), runner management, autoscaling. Do NOT use for: GitHub Actions, CircleCI, Jenkins, or other CI/CD platforms.

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Use this skill when the user says 'ibm cloud', 'ibm cloud infrastructure', 'ibm cloud services', 'ibm cloud pak', 'ibm cloud foundry', 'ibm cloud kubernetes', 'iks', 'ibm cloud satellite', 'ibm cloud schematics', 'ibm cloud terraform', 'ibm cloud iam', 'ibm cloud vpc', 'ibm cloud vsi', 'ibm cloud load balancer', 'ibm cloud dns', 'ibm cloud direct link', 'ibm cloud cos', 'ibm cloud object storage', 'ibm cloud databases', 'ibm cloud data engines', 'ibm cloud event streams', 'ibm cloud api gateway', 'ibm cloud functions', 'ibm cloud code engine', 'ibm cloud monitoring', 'ibm cloud logging', 'ibm cloud activity tracker', 'ibm cloud security groups', 'ibm cloud acl', 'ibm cloud transit gateway', 'watson', 'ibm cloud pak for data', 'ibm cloud pak for applications', 'ibm cloud pak for integration'. Covers: IBM Cloud VPC, IKS (Kubernetes), Object Storage, VSI, IAM, networking, terraform provider, Satellite, Schematics.

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Use this skill when provisioning infrastructure with Terraform — module structure, state management, remote backends, workspaces, CI/CD integration, policy as code. This skill enforces: environment directory structure, remote backends with state locking, semantic versioning for modules, no hardcoded values, sensitive output marking, plan review before apply. Do NOT use for: configuration management (use Ansible), Kubernetes application deployment (use Helm), non-HashiCorp IaC tools.

j4flmao Bundle

Use this skill when asked about PyTorch, TensorFlow, Keras, neural network, CNN, RNN, LSTM, transformer, GAN, autoencoder, training loop, backpropagation, gradient descent, CUDA, distributed training, or mixed precision. This skill enforces: PyTorch training loop with nn.Module and DataLoader, TensorFlow Keras Sequential/Functional APIs, CNN architectures (ResNet, EfficientNet), RNN/LSTM/GRU for sequences, transformer implementations (self-attention, positional encoding), distributed training (DDP, FSDP), mixed precision (AMP), and CUDA optimization. Do NOT use for: classical ML models, feature engineering, or MLOps pipeline configuration.

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Use this skill when designing feature stores: Feast, Tecton, online features, offline features, point-in-time join, feature serving, feature registry, feature transformation, feature validation. This skill enforces: feature repository structure, point-in-time correctness, online/offline serving separation, feature validation with freshness checks, feature registry with documentation. Do NOT use for: model training pipeline, embedding storage, vector database configuration.

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Use this skill when deploying models for inference: TorchServe, BentoML, Ray Serve, KServe, Seldon Core, model deployment, A/B testing, autoscaling, canary deployment, model versioning, inference optimization. This skill enforces: framework selection based on model type, deployment strategy documentation, autoscaling configuration, model versioning scheme, rollback procedure, inference optimization. Do NOT use for: model training, feature store serving, pipeline orchestration, prompt engineering.

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Use this skill when asked about data lineage, OpenLineage, Marquez, DataHub, column-level lineage, impact analysis, data provenance, data dependency tracking, or lineage graph models. This skill enforces: OpenLineage integration for standardized lineage collection, Marquez or DataHub deployment for lineage storage and querying, column-level lineage with SQL parsing, impact analysis for downstream dependency detection, and lineage graph visualization. Do NOT use for: data pipeline orchestration (use data-etl-pipeline), data quality validation (use data-data-quality), or data catalog search (use data-catalog).

j4flmao Bundle

Use this skill when asked about data quality, data validation, data profiling, Great Expectations, dbt tests, data observability, Soda, Monte Carlo, data contracts, schema validation, or data SLAs. This skill enforces: data quality dimensions (completeness, accuracy, timeliness, consistency, uniqueness, integrity), automated validation with Great Expectations (expectations suites, data docs, checkpoints) and dbt tests (singular, generic, freshness), data observability with Soda/Monte Carlo monitoring, data SLAs with escalation, and data contract enforcement between producers and consumers. Do NOT use for: ETL pipeline design, data warehouse schema design, or BI dashboard configuration.

j4flmao Bundle

Use this skill when asked about data testing, dbt unit testing, data-diff, datafold, Soda, Great Expectations, data regression testing, data quality testing, data contract testing, or data validation automation. This skill enforces: dbt unit testing with dbt-unit-testing package, regression detection with data-diff and datafold, data quality validation with Soda and Great Expectations, data contract enforcement, and CI/CD integration for automated data testing. Do NOT use for: pipeline monitoring (use data-observability), schema design (use data-warehouse), or generic software testing (use testing skill).

j4flmao Bundle

Use this skill when asked about ETL, ELT, data pipeline, Airflow, dbt, data transformation, data ingestion, batch processing, or pipeline orchestration. This skill enforces: pipeline architecture with Airflow DAG design, dbt transformation with incremental loading, error handling with retry and dead-letter, data validation checks, and observability. Do NOT use for: real-time streaming (Kafka/Flink), data warehouse schema design, or BI dashboard configuration.

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Use this skill when the user says 'bare metal', 'physical server', 'provisioning', 'PXE boot', 'IPMI', 'BMC', 'iDRAC', 'iLO', 'RMM', 'server lifecycle', 'burn-in testing', 'firmware update', 'RAID', 'BIOS configuration', 'server automation', 'MAAS', 'Metal3', 'Rack deployment', 'data center hardware', 'server imaging'. Covers: server provisioning (PXE, iPXE, MAAS), firmware lifecycle, IPMI/BMC management, RAID configuration, burn-in testing, server automation, hardware asset management, BIOS tuning. Do NOT use for: cloud infrastructure (use cloud-specific skills), Kubernetes on bare metal (use kubernetes-patterns).

j4flmao Bundle

Use this skill when the user says 'datacenter', 'data center', 'DC', 'rack', 'power', 'cooling', 'PDU', 'UPS', 'Tier classification', 'N+1 redundancy', '2N redundancy', 'cabling', 'fiber', 'copper', 'hot aisle', 'cold aisle', 'rack density', 'kW per rack', 'DCIM', 'data center operations', 'colocation'. Covers: datacenter tier classification (Tier I-IV), power and cooling design, rack layout, cabling standards, DCIM tools, capacity planning, redundancy models, environmental monitoring, colocation selection. Do NOT use for: cloud infrastructure (use cloud-specific skills), server provisioning (use bare-metal skill).

j4flmao Bundle

Use this skill for Kubernetes cluster administration, architecture, operations, and production best practices. Covers: cluster architecture (control plane, etcd, worker nodes), networking (CNI, Service, Ingress, NetworkPolicies), storage (CSI, PVC, StorageClasses), security (RBAC, PodSecurity, secrets), scheduling (taints/tolerations, node affinity, topology spread), upgrades, backup/DR, and cluster autoscaling. Do NOT use for: application-level Kubernetes patterns (kubernetes-patterns), Helm chart design (helm-patterns), service mesh (service-mesh), or cloud-specific managed Kubernetes (aws/gcp/azure).

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Use this skill when configuring observability and monitoring stack — Prometheus, Grafana, Loki, ELK Stack. This skill enforces: Prometheus scrape configs with relabeling, Grafana dashboard folder hierarchy, Loki log label strategy, Alertmanager routing by severity, SLO tracking with error budgets. Do NOT use for: application-level instrumentation, CI/CD pipeline monitoring, infrastructure provisioning.

j4flmao Bundle

Use this skill when the user says 'serverless', 'lambda', 'aws lambda', 'functions', 'function as a service', 'faas', 'azure functions', 'google cloud functions', 'knative', 'openfaas', 'serverless framework', 'chalice', 'zappa', 'apigw', 'api gateway', 'event-driven', 'cold start', 'provisioned concurrency', 'reserved concurrency', 'lambda layers', 'step functions', 'durable functions', 'serverless observability', 'serverless monitoring', 'serverless security', 'serverless cost', 'serverless best practices', 'serverless framework deployment'. Covers: AWS Lambda, Azure Functions, Google Cloud Functions, serverless framework, event-driven patterns, cold start optimization, monitoring, security, and cost management.