k8s-aiops
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TDQS
Scored across 55 tools
All tools target distinct Kubernetes resources with clear actions (e.g., node_list vs node_describe, deployment_get vs pod_get). Even closely related tools like rollouts are differentiated by action (status, history, pause, etc.). There is no ambiguity between tools.
Naming follows a consistent pattern: read operations use resource_verb (e.g., pod_list, deployment_get) and write operations use verb_resource (e.g., delete_pod, scale_deployment). This pattern is applied uniformly across all 55 tools.
At 55 tools, the count is well above the recommended range for a well-scoped server. While the coverage is broad, many tools are simple list/get pairs that could be merged or omitted, making the surface feel heavy for typical use.
The tool surface covers many Kubernetes resources but has notable gaps: no tools for creating deployments, statefulsets, jobs, or configmaps/secrets/ingresses. The focus on reads and delete/scale operations suggests a troubleshooting role, but missing creates limit full lifecycle management.