kubesphere-volcano
KubeSphere Volcano job management Skill. Use when user asks to create, list, update, delete Jobs (Volcano Jobs), manage Queues, create PyTorch/TensorFlow/MPI training jobs, or troubleshoot Volcano scheduling issues in KubeSphere. Includes built-in YAML templates, scheduling policy recommendations, and best practices for resource configuration. Handles both KubeSphere API and kubectl operations.
npx skills add kubesphere/kubesphere --skill kubesphere-volcano --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.
What it does
Describes a skill that enables the agent to manage Volcano-based jobs in KubeSphere, including creating, listing, updating, and deleting Jobs, managing Queues, generating YAML templates for PyTorch, TensorFlow, MPI, and batch jobs, and troubleshooting scheduling issues.
How it works
- It instructs the agent to use the resource type Job (not VolcanoJob) for all Kubernetes interactions.
- It supports operations via two API paths: the KubeSphere extension API (/kapis) and the Kubernetes native API (/apis). It provides explicit curl-based API usage examples and kubectl commands.
- It includes concrete commands and YAML snippets for creating, listing, deleting, and inspecting Jobs and Queues, as well as built-in YAML templates for common training workloads.
- It warns that deleting a Job will terminate all running pods and shows how to perform deletions via API or kubectl.
- It emphasizes using short names vcjob or vj for querying, and it covers both host and member cluster contexts with examples for kubeconfig switching.
When to use it
- Use for full Volcano lifecycle operations: create, list, update, delete Volcano Jobs; manage Queues; generate training YAMLs; troubleshoot pending/pod creation/scheduling issues.
- Use the KubeSphere API path for multi-cluster queries and extension status, and kubectl for direct Kubernetes resource operations.
What it can touch
- API endpoints under /kapis/batch.volcano.sh and /kapis/scheduling.volcano.sh for Jobs, PodGroups, and Queues.
- Kubernetes resources via kubectl for jobs.batch.volcano.sh, vcjob, vj, queue, podgroup, and CRDs related to Volcano.
- YAML templates for Job manifests (PyTorch, TensorFlow, MPI, etc.).
Caveats
- Out of scope by default includes advanced Volcano CRDs like JobFlow, JobTemplate, or Command, deep scheduler config without cluster evidence, and Volcano system installation.
- For deletions, the risk of terminating running pods is explicitly stated.
- The skill mandates avoiding guessing optional fields and omitting them instead, per its guidance.
# KubeSphere Volcano Management **Environment (this KubeSphere instance):** - KubeSphere: Set `KS_HOST` environment variable (e.g., http://<kubesphere-host>:30880) - Username: admin (default) - Password: Set `KS_PASSWORD` environment variable - Clusters: Run `kubectl get clusters` or `ks_api GET /kapis/cluster.kubesphere.io/v1alpha1/clusters` - Volcano Extension: Run `kubectl get extension volcano -n kubesphere-system` or check via KubeSphere console Use this skill for the full Volcano lifecycle in KubeSphere: - Create, list, update, delete Volcano Jobs - Manage Queues for job scheduling - Generate YAML templates for PyTorch, TensorFlow, MPI, and batch jobs - Troubleshoot job pending, pod creation, and scheduling issues Out of scope by default: - Advanced Volcano CRDs not requested by the user, such as `JobFlow`, `JobTemplate`, or `Command` - Deep scheduler configuration without cluster evidence - Volcano system installation (assume extension is already installed) If the user explicitly asks for those, acknowledge that they are Volcano capabilities but treat them as a follow-up task. ## Response Rules - Prefer executable output: `Job` YAML, `Queue` YAML, kubectl commands, or a shor
- Response Rules
- API Usage
- API Endpoints
- Discovery Commands
- Option 1: Using KubeSphere API (curl)
- Option 2: Using kubectl (Direct Cluster Access)
- Option 3: Multi-Cluster Query (kubeconfig extraction)
- When to Use Which Approach
- Common Operations
- List Jobs
- Get Job Details
- Create Job
- Delete Job
- List Queues
export KS_HOST="http://<kubesphere-host>:30880" # KubeSphere console URL (required)
export KS_USERNAME="admin" # Username (default)
export KS_PASSWORD="<password>" # Password (optional if KS_TOKEN is set)
export KS_TOKEN="<token>" # Pre-generated OAuth token (optional, takes priority)
Get OAuth token - prefer KS_TOKEN if set, otherwise use password
if [ -n "${KS_TOKEN}" ]; then
echo "$KS_TOKEN"
return
fi
if [ -z "${KS_PASSWORD}" ]; thenWhat does the kubesphere-volcano skill do?
KubeSphere Volcano job management Skill. Use when user asks to create, list, update, delete Jobs (Volcano Jobs), manage Queues, create PyTorch/TensorFlow/MPI training jobs, or troubleshoot Volcano scheduling issues in KubeSphere. Includes built-in YAML templates, scheduling policy recommendations, and best practices for resource configuration. Handles both KubeSphere API and kubectl operations.
How do I install it?
Run `npx skills add kubesphere/kubesphere --skill kubesphere-volcano --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 kubesphere/kubesphere, a repository with 17,016 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.