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 nebius/nebius-physical-ai --skill soperatorgit clone --depth 1 https://github.com/nebius/nebius-physical-aiWrote 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/nebius/nebius-physical-ai/soperator)<a href="https://agentmods.dev/skills/nebius/nebius-physical-ai/soperator"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/soperator/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/nebius/nebius-physical-ai/soperator"><img src="https://agentmods.dev/badge/skills/nebius/nebius-physical-ai/soperator.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 | $0.00064 | $0.03432 |
| Opus 5 | $0.00032 | $0.01716 |
| Sonnet 5 | $0.00013 | $0.00686 |
| Haiku 4.5 | $0.00006 | $0.00343 |
Grade C, and why
soperator scanned grade C with 1 finding 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 8d 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.
Reaches for credential fileshighPrivilege escalation
SSH keys, cloud credentials, git-credentials, .npmrc, /etc/shadow: reading these is how a config file becomes a credential leak.
`NPA_SSH_PUBLIC_KEY` path, then `~/.ssh/id_ed25519.pub` / `id_rsa.pub` / How it starts
The opening of the file, as written. The whole thing — 226 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Soperator (Slurm-on-Kubernetes)
When To Use
Use when a customer wants a managed Slurm cluster on Nebius (foundation-model
pretraining, large eval sweeps, HPC batch) instead of, or alongside, SkyPilot —
and wants npa to drive it. npa soperator deploy wraps the public
nebius/nebius-solutions-library soperator Terraform recipe from a compact
declarative spec, so customers get a working Slurm cluster without hand-editing
the recipe's large tfvars.
Three-tier contract:
- CLI:
npa soperator plan|deploy --spec <cluster.yaml>,npa soperator status --name <n>,npa soperator destroy --name <n>. - SDK:
npa.sdk.soperator.plan(spec)/deploy(spec)/destroy(name)withSoperatorSpec/WorkerPoolSpec. - YAML / agent:
apiVersion: npa.soperator/v0.0.1spec; workflowtoolRef: infra.soperator.deploy. - Fleet:
npa.fleet/v0.0.1targets may selectbackend: soperatorand embed this same spec undersoperator:. Standalone, SDK, and fleet call the same backend lifecycle; fleet remains responsible for identity, selection, concurrency, inventory, and shared-network ownership. Soperator names are fleet-wide physical/context identities and therefore must be unique even when targets belong to different projects.
Spec (npa.soperator/v0.0.1)
Multiple worker pools with different presets are first-class; each pool can
enable a node-local Docker/Enroot image cache disk (NETWORK_SSD_IO_M3) so
large GPU tool images don't thrash the boot disk.
apiVersion: npa.soperator/v0.0.1
name: npasop # company_name; kube context = nebius-<name>-slurm
region: us-central1 # or resolved from ~/.npa config
control_plane:
system: { min_size: 3, max_size: 24 } # preset omitted: derive XS..XL upstream
controller: {} # preset omitted: derive with same tier
login: { preset: 16vcpu-64gb } # login needs >= 16vcpu (sufficiency)
workers:
- name: cpu8
platform: cpu-d3
preset: 8vcpu-32gb
docker_cache: true # node-local IO_M3 image cache
docker_cache_gib: 930 # divisible by 93
- name: gpu
platform: gpu-b200-sxm
preset: 8gpu-160vcpu-1792gb # GPU workers must be fabric-capable (8-GPU SXM)
size: 2
fabric: us-central1-b # required for GPU presets; 1-GPU can't cluster
preemptible: true # on-demand GPU quota is often 0; preemptible works
# For reserved capacity, set preemptible: false and exactly one runtime
# selector. Never commit a live ID/name:
# capacity_block_group: <capacity-block-group-id>
# capacity_block_group_name: <unique-capacity-block-group-name>
docker_cache: true
accounting: false
# omitted REST preserves the legacy default (follows accounting); GPU checks still run directly
slurm_operator_version: "4.1.6"
k8s_version: "1.34"
node_group_version: "72"
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.
- 8d ago First seen · 226 lines · 64 tokens per session scan C a4d2a6210e4f
soperator is a skill published in the GitHub repository nebius/nebius-physical-ai (29 stars, last pushed today), licensed Apache-2.0. It adds 64 tokens to every session and 3,432 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (reaches for credential files). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
gke-compute-classes
Configures, optimizes, and troubleshoots GKE ComputeClasses. Use when configuring Spot VMs with on-demand fallback, targeting specific accelerators (GPUs/TPUs) or machine families, restricting ComputeClass access, or debugging pending pods related to node pool auto-creation. Do not use for cluster-level Node Auto…
gke-reliability
Improves GKE workload reliability, using PDBs, health probes, and topology spread constraints. Use when configuring GKE workload reliability, setting up PDBs, or configuring GKE health probes (liveness, readiness, startup). Don't use for disaster recovery setup or full cluster backups (use gke-backup-dr instead).
gke-workload-security
Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running cluster security audits (auditcluster.sh), configuring Workload Identity Federation (impersonation, KSA/GSA binding, and pod setup), enforcing Network Policies (default-deny…
azure-mgmt-botservice-dotnet
Azure Resource Manager SDK for Bot Service in .NET. Management plane operations for creating and managing Azure Bot resources, channels (Teams, DirectLine, Slack), and connection settings. Triggers: "Bot Service", "BotResource", "Azure Bot", "DirectLine channel", "Teams channel", "bot management .NET", "create bot".
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
cloud-architect
Designs cloud architectures, creates migration plans, generates cost optimization recommendations, and produces disaster recovery strategies across AWS, Azure, and GCP. Use when designing cloud architectures, planning migrations, or optimizing multi-cloud deployments. Invoke for Well-Architected Framework, cost…