Query Grafana dashboards, alerts, and data sources such as Prometheus to investigate service health, infrastructure, and LLM performance. Retrieve time-sensitive metrics over a chosen period to examine latency, request rates, failures, and active alerts.
Query Grafana dashboards and Prometheus metrics for service health, LLM latency, and infrastructure monitoring. Use this skill when the user asks about service health, monitoring, alerts, or performance metrics.
Run score Not tested
See how to installReview the instructions the agent will receive before you install.
$GRAFANA_URL (e.g. https://your-org.grafana.net)Authorization: Bearer $GRAFANA_API_TOKEN (service account token)GRAFANA_URL, GRAFANA_API_TOKEN from Settings → Data sourcesgrafanacloud-promserver/lib/grafana.ts| Function | Description |
|---|---|
listDashboards(query?) | Search dashboards by query |
getDashboard(uid) | Full dashboard JSON with panels |
getDatasources() | List all datasources |
getAlertRules() | All alert rules (flattened from groups) |
getAlertInstances() | Currently firing alert instances |
queryDatasource(uid, queries[], from?, to?) | Proxy to Grafana's /api/ds/query |
| Route | Description |
|---|---|
GET /api/grafana/dashboards | Search dashboards |
GET /api/grafana/dashboard?uid=... | Full dashboard JSON |
GET /api/grafana/datasources | List datasources |
GET /api/grafana/alerts | Alert rules and firing instances |
POST /api/grafana/query | Query datasource (Prometheus, Loki, etc.) |
Use grafana for agent-facing Grafana work. Do not call /api/grafana/*
directly from the agent.
| Mode | Args | Description |
|---|---|---|
dashboards | search | Search dashboards |
dashboard | uid | Full dashboard JSON |
datasources | List datasources | |
alerts | Alert rules and firing instances | |
query | datasourceUid, queries, from, to | Query a datasource |
/adhoc/engineering — Engineering dashboard (mirrors a Grafana dashboard by UID){ results: { [refId]: { frames: [{ schema: { fields }, data: { values } }] } } }
values[0] = timestamps (epoch ms), values[1+] = metric valuesschema.fields[i].labels (e.g. { model: "claude-3.5" }){ time: number, [seriesName]: number }[]$CodegenMode → default quality-v4$AIModel → regex pattern, default .* (all)$environment → cloud or cloud-v2, default cloudvcpcodegen_completion_total, vcpcodegen_completion_latency_bucket, vcpcodegen_feedback_total, vcpcodegen_error_totalllm_completion_cost_total, llm_input_tokens_total, llm_output_tokens_total, llm_latency_bucket, llm_failures_total, llm_completions_totalprojects_proposed_config_total, projects_status_total, projects_remote_machine_*, projects_start_duration_bucketapi_request_total, with_span_duration_bucket, memory_heap_usage_percent_bucketfly_endpoint_total, fly_machine_*builderbot_pr_created_total, builderbot_pr_closed_totalqueryDatasource constructs body with datasource UID in each query target; timestamps as string msgetAlertRules flattens nested rule groups from unified alerting APIgetAlertInstances handles both array and wrapped object response shapesqueryDatasource skips cachehistogram_quantile() computes quantiles)For production issues, query Grafana/Prometheus FIRST:
llm_latency_bucket)api_request_total)llm_failures_total)Then check Agent-Native Analytics Monitoring -> Errors for captured application issues, external Sentry when connected, and Cloud Logging for raw logs.
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