Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/quay/ai-helpersnpx agentmods add skills/quay/ai-helpers/cluster-provisionWrote 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/quay/ai-helpers/cluster-provision)<a href="https://agentmods.dev/skills/quay/ai-helpers/cluster-provision"><img src="https://agentmods.dev/badge/skills/quay/ai-helpers/cluster-provision.svg" alt="Measured on agentmods" 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 | $0.00084 | $0.00609 |
| Opus 5 | $0.00042 | $0.00304 |
| Sonnet 5 | $0.00017 | $0.00122 |
| Haiku 4.5 | $0.00008 | $0.00061 |
Grade A, and why
cluster-provision 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 2d 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.
What it actually says
Cluster Provision
Provision an ephemeral OpenShift cluster from a Hive ClusterPool via the OpenShift CI Gangway REST API.
Arguments
Parse $ARGUMENTS into at most two values before invoking Bash:
- Arg 1: KUBECONFIG path (default:
/tmp/k) - Arg 2: OCP version (default:
4.18)
Set variables from $ARGUMENTS:
KUBECONFIG_PATH = first arg or /tmp/k
OCP_VERSION = second arg or 4.18
Step 1: Provision the cluster
bash .claude/scripts/cluster-provision.sh up "$KUBECONFIG_PATH" "$OCP_VERSION"
The script handles everything: triggering the Gangway API, polling for readiness, downloading the kubeconfig, and validating connectivity. Wait for the === Cluster Ready === output.
Step 2: Verify
oc --kubeconfig="$KUBECONFIG_PATH" whoami
oc --kubeconfig="$KUBECONFIG_PATH" get nodes
Step 3: Report
Summarize connection status and remind user:
- The cluster is ready
- Kubeconfig path
- Cluster server URL
- Cluster auto-expires in ~4 hours
- Prow job URL for reference
Status
bash .claude/scripts/cluster-provision.sh status
Teardown
bash .claude/scripts/cluster-provision.sh down
Troubleshooting
| Error | Fix |
|---|---|
GANGWAY_TOKEN is not set |
Run: oc login https://api.ci.l2s4.p1.openshiftapps.com:6443 --web && export GANGWAY_TOKEN=$(oc whoami -t) |
HTTP 401 |
Token expired — re-authenticate with oc login |
KUBECONFIG_ENCRYPTION_KEY is not set |
Contact the CI team for the decryption passphrase |
| Timeout after 40 min | Pool exhausted or job stuck — check the Prow job URL |
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.
- 2d ago First seen · 76 lines · 84 tokens per session scan A 45c191e75ee8
cluster-provision is a skill published in the GitHub repository quay/ai-helpers (3 stars, last pushed 20d ago), licensed MIT. It adds 84 tokens to every session and 609 once invoked, about $0.0004 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 2026-09-04.
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-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…
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).
nemo-automodel-launcher-config
Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution.
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".
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…