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Found 430 Skills
Provides production-ready Kubernetes manifest guidance including resource management, security, high availability, and configuration best practices. This skill should be used when working with Kubernetes YAML files, deployments, pods, services, or when users mention k8s, container orchestration, or cloud-native applications.
Data lake and lakehouse platform patterns: ingestion/CDC, transformations, open table formats (Iceberg/Delta/Hudi), query and serving engines (Trino/ClickHouse/DuckDB), orchestration, governance/lineage, cost and operations. Self-hosted and cloud options.
Comprehensive infrastructure engineering covering DevOps, cloud platforms, FinOps, and DevSecOps. Platforms: AWS (EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation), Azure basics, Cloudflare (Workers, R2, D1, Pages), GCP (GKE, Cloud Run, Cloud Storage), Docker, Kubernetes. Capabilities: CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins), GitOps, infrastructure as code (Terraform, CloudFormation), container orchestration, cost optimization, security scanning, vulnerability management, secrets management, compliance (SOC2, HIPAA). Actions: deploy, configure, manage, scale, monitor, secure, optimize cloud infrastructure. Keywords: AWS, EC2, Lambda, S3, ECS, EKS, RDS, CloudFormation, Azure, Kubernetes, k8s, Docker, Terraform, CI/CD, GitHub Actions, GitLab CI, Jenkins, ArgoCD, Flux, cost optimization, FinOps, reserved instances, spot instances, security scanning, SAST, DAST, vulnerability management, secrets management, Vault, compliance, monitoring, observability. Use when: deploying to AWS/Azure/GCP/Cloudflare, setting up CI/CD pipelines, implementing GitOps workflows, managing Kubernetes clusters, optimizing cloud costs, implementing security best practices, managing infrastructure as code, container orchestration, compliance requirements, cost analysis and optimization.
CI/CD automation and workflow orchestration using GitHub Actions for builds, tests, deployments, and repository automation
Multi-agent orchestration for complex tasks. Use when tasks require parallel work, multiple agents, or sophisticated coordination. Triggers include requests for features, reviews, refactoring, testing, documentation, or any work that benefits from decomposition into parallel subtasks. This skill defines how to orchestrate work using cc-mirror tasks for persistent dependency tracking and TodoWrite for real-time session visibility.
Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".
Spec-driven development orchestration with context engineering for solo developers. Prevents context rot through fresh subagent contexts and atomic task execution. Use when: starting projects, planning features, executing development phases, or when user says "gsd", "plan", "new project", "execute phase". Triggers: /gsd init, /gsd plan, /gsd execute, /gsd status, /gsd verify
Amazon Bedrock Agents for building autonomous AI agents with foundation model orchestration, action groups, knowledge bases, and session management. Use when creating AI agents, orchestrating multi-step workflows, integrating tools with LLMs, building conversational agents, implementing RAG patterns, managing agent sessions, deploying production agents, or connecting knowledge bases to agents.
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.
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
Goal-based workflow orchestration - routes tasks to specialist agents based on user goals
Manage Alibaba Cloud Intelligent Cloud Editing (ICE) media workflows via OpenAPI/SDK. Use for media processing jobs, template/workflow orchestration, editing and production pipelines, and job status troubleshooting.