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kubesense-ai

@kubesense-ai source repo

8 published skills

  1. ▌
    Kubesense Skills · kubesense-ai bundle
    KubeSense observability skills for AI agents — query logs, traces, and metrics from Kubernetes clusters, inspect cluster inventory, and generate alert and dashboard configuration.
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    Kubesense MCP · kubesense-ai bundle
    The KubeSense MCP tool layer — connection and auth, the full 29-tool inventory, tool selection, the discovery-first rule, the catalog-label field contract shared by every logs/traces query, WHERE syntax, multi-datasource formula queries, and how to read the TSV/columnar output formats. Read this when a tool returns a field-name or WHERE error.
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  3. ▌
    Kubesense Logs · kubesense-ai
    Search and aggregate Kubernetes logs via KubeSense MCP — the exact log field catalog (type, instance, container, node — not level/pod_name/host), WHERE syntax, body text search, counts and percentiles, and window-based pagination.
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    Kubesense Infra · kubesense-ai
    Inventory and topology of the monitored Kubernetes estate via KubeSense MCP — clusters, nodes, pods, workloads, detected issues, infra failures (OOM/CrashLoop/probe/scheduling), and recent deploys/scaling changes. Use for "what is running", "what is broken at the k8s layer", and "what changed".
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    Kubesense Alerts · kubesense-ai bundle
    Work with KubeSense alerts — survey what is firing, inspect a rule's breaching condition and history, and create rules either via the create-alert MCP tool or as import JSON over metrics, logs, and traces. Includes validate-alert-json for checking hand-built rule JSON, the alert engine's own field allow-lists, which differ from the query engine's, and translating Datadog monitors.
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  6. ▌
    Kubesense Traces · kubesense-ai
    Query spans and distributed traces via KubeSense MCP — latency percentiles, error rates, the exact trace field catalog (service, role, method, status_code, resource — not app_service/kind/subtype/return_code), duration units, and the distributed-trace waterfall for root-causing which hop broke or burned the time.
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  7. ▌
    Kubesense Metrics · kubesense-ai bundle
    Query Kubernetes, infrastructure and cloud-provider metrics from KubeSense with PromQL/MetricsQL — metric discovery, label inspection, the metric families KubeSense actually collects (kube-state-metrics, cAdvisor, node-exporter, OTel hostmetrics, DCGM GPU, JVM, and AWS/GCP/Azure/MongoDB Atlas/Confluent/Kong cloud resources), and the label conventions (clusterId, kubesense_cloud_resource_metric) needed to write a query that returns data.
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  8. ▌
    Kubesense Dashboards · kubesense-ai bundle
    Create KubeSense dashboards over metrics, logs, and traces — either directly with the create-dashboard MCP tool or as preset JSON the user imports — with the exact schema, the fields that hard-fail import, and the fields that silently discard your data instead of erroring. Includes validate-dashboard-json for checking a preset before you commit to it.
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