kubeflow-pipeline-executor
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.
npx skills add a5c-ai/babysitter --skill kubeflow-pipeline-executor --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# kubeflow-pipeline-executor ## Overview Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML operations. ## Capabilities - Pipeline definition and compilation - Component creation and reuse - Pipeline versioning - Artifact tracking and lineage - Kubernetes resource management - Pipeline scheduling and triggering - Caching for component outputs - Visualization of pipeline runs ## Target Processes - Model Training Pipeline - Distributed Training Orchestration - Model Deployment Pipeline - ML Model Retraining Pipeline ## Tools and Libraries - Kubeflow Pipelines - KFP SDK (v2) - Kubernetes - Argo Workflows ## Input Schema ```json { "type": "object", "required": ["action"], "properties": { "action": { "type": "string", "enum": ["compile", "run", "schedule", "list", "get-run", "delete"], "description": "KFP action to perform" }, "pipelinePath": { "type": "string", "description": "Path to pipeline definition file" }, "pipelineConfig": { "type": "object", "properties": { "name": { "type": "string" }, "description": { "type": "string" }, "parameters": { "type": "object" } } }, "runConfig": { "type": "object", "properties": { "experimentName
- Overview
- Capabilities
- Target Processes
- Tools and Libraries
- Input Schema
- Output Schema
- Usage Example
What does the kubeflow-pipeline-executor skill do?
Kubeflow Pipelines skill for ML workflow orchestration, component management, and Kubernetes-native ML.
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill kubeflow-pipeline-executor --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.