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Found 10 Skills
Design multi-stage CI/CD pipelines with approval gates, security checks, and deployment orchestration. Use when architecting deployment workflows, setting up continuous delivery, or implementing GitOps practices.
Design ETL workflows with data validation using tools like Pandas, Dask, or PySpark. Use when building robust data processing systems in Python.
Design and implement GitLab CI/CD pipelines with stages, jobs, artifacts, and caching. Configure runners, Docker integration, and deployment strategies.
Design data pipelines covering ETL vs ELT architectures, data source integration, scheduling, quality checks, and warehouse design. Use this skill when the user needs to move data between systems, build a data warehouse, automate data processing, or improve data reliability — even if they say 'move data from X to Y', 'build an ETL pipeline', 'our data is a mess', or 'set up a data warehouse'.
Azure DevOps pipeline best practices, patterns, and industry standards
Design and build SuperPlane workflow canvases from requirements. Translates workflow descriptions into canvas YAML with triggers, components, edges, and expressions. Use when the user wants to create a new workflow, build a canvas, design a pipeline, or wire up components. Triggers on "build canvas", "create workflow", "design pipeline", "automate".
Build new AI method from scratch using the MTHDS standard (.mthds bundle files). Use when user says "create a pipeline", "build a workflow", "new .mthds file", "make a method", "design a pipe", or wants to create any new method from scratch. Guides the user through a 10-phase construction process.
Compose multiple skills into a unified workflow pipeline. Combine research, creativity, review, and other skills into custom multi-step processes. Use when a task requires chaining skills together, creating custom workflows, or designing compound skill sequences. Triggers on "워크플로우", "workflow", "파이프라인", "pipeline", "스킬 조합", "combine skills", "복합 프로세스".
Use this skill when architecting on Google Cloud Platform, selecting GCP services, or implementing data and compute solutions. Triggers on Cloud Run, BigQuery, Pub/Sub, GKE, Cloud Functions, Cloud Storage, Firestore, Spanner, Cloud SQL, IAM, VPC, and any task requiring GCP architecture decisions or service selection.
Use when writing SQL queries, building analytics dashboards, tracking metrics, designing data pipelines, or analyzing user behavior and product usage