Kubernetes Skills
Analysis
The skill is coherent for Velero-based Kubernetes backups, but it documents high-impact cluster restore and persistent scheduling actions without clear approval or scoping guardrails.
Findings (4)
Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.
Checks for instructions or behavior that redirect the agent, misuse tools, execute unexpected code, cascade across systems, exploit user trust, or continue outside the intended task.
velero_restore_create_tool(name="my-restore", backup_name="my-backup") ... kubectl_apply(manifest="""apiVersion: velero.io/v1\nkind: Schedule ... includedNamespaces:\n - production""")
These instructions use cluster-mutating restore and manifest-apply tools, including a production schedule, without documented confirmation, dry-run, target validation, or containment steps.
kind: Schedule ... schedule: "0 2 * * *" # 2 AM daily ... includedNamespaces:\n - production
The scheduled backup example creates a persistent Kubernetes/Velero resource that continues running daily after the immediate interaction.
Manage backups and restores using kubectl-mcp-server's Velero tools.
The skill depends on external MCP Velero tools, but the provided artifact set contains only instructions and no reviewed implementation or install declaration for those tools.
Checks whether tool use, credentials, dependencies, identity, account access, or inter-agent boundaries are broader than the stated purpose.
velero_backup_create_tool(name="daily-backup", namespaces=["production"], ttl="720h") ... include_resources=["configmaps", "secrets"]
The examples show access to production namespaces and Kubernetes secrets, which requires sensitive Kubernetes/Velero permissions even though that access is expected for backup and restore work.
