Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Aidas-dev/k8s-agent-skills --skill kubeflow-trainergit clone --depth 1 https://github.com/Aidas-dev/k8s-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/aidas-dev/k8s-agent-skills/kubeflow-trainer)<a href="https://agentmods.dev/skills/aidas-dev/k8s-agent-skills/kubeflow-trainer"><img src="https://agentmods.dev/badge/skills/aidas-dev/k8s-agent-skills/kubeflow-trainer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/aidas-dev/k8s-agent-skills/kubeflow-trainer"><img src="https://agentmods.dev/badge/skills/aidas-dev/k8s-agent-skills/kubeflow-trainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00056 | $0.03236 |
| Opus 5 | $0.00028 | $0.01618 |
| Sonnet 5 | $0.00011 | $0.00647 |
| Haiku 4.5 | $0.00006 | $0.00324 |
Grade A, and why
kubeflow-trainer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 430 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Kubeflow Trainer v2.2
Repository: github.com/kubeflow/trainer
Latest release: v2.2.0 (March 20, 2026)
API version: trainer.kubeflow.org/v1alpha1
Kubernetes: v1.36
Underlying orchestration: JobSet v0.10.1
Architecture
Single TrainJob CRD replaces framework-specific CRDs. TrainingRuntime defines the execution template. Framework-agnostic: one abstraction for PyTorch, TensorFlow, JAX, XGBoost, MPI, Flux.
TrainJob (training intent)
└─ runtimeRef ──> TrainingRuntime / ClusterTrainingRuntime (execution template)
└─ template ──> JobSet (underlying orchestration)
└─ replicatedJobs ──> Jobs ──> Pods
CRDs
TrainJob (namespaced)
Defines the training workload.
apiVersion: trainer.kubeflow.org/v1alpha1
kind: TrainJob
metadata:
name: pytorch-mnist
spec:
runtimeRef:
name: pytorch-mnist-runtime
apiGroup: trainer.kubeflow.org
# Trainer definition
trainer:
image: pytorch/pytorch:2.5.0-cuda12.4-cudnn9-runtime
command: ["python", "/workspace/train.py"]
numNodes: 4
env:
- name: EPOCHS
value: "10"
- name: BATCH_SIZE
value: "128"
resources:
requests:
cpu: 4
memory: 16Gi
limits:
nvidia.com/gpu: 2
# Optional: dataset/model initializer (sidecar that runs before training)
initializer:
storageUri: s3://bucket/datasets/mnist/
env:
- name: AWS_ENDPOINT_URL
value: s3.example.com
secretRef:
name: s3-credentials
# Runtime patches (replaces deprecated PodTemplateOverrides)
runtimePatches:
- managerKey: user-overrides
patch:
- op: add
path: /spec/replicatedJobs/0/template/spec/template/spec/containers/0/env/-
value:
name: LOG_LEVEL
value: debug
# Hard deadline
activeDeadlineSeconds: 3600
# Kueue integration
managedBy: kueue.x-k8s.io/multikueue
Spec Fields
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 430 lines · 56 tokens per session scan A 519749ab1d07
kubeflow-trainer is a skill published in the GitHub repository Aidas-dev/k8s-agent-skills (2 stars, last pushed 26d ago), licensed MIT. It adds 56 tokens to every session and 3,236 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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