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grafana

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.

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BuilderIO/agent-native
Última actividad en el origen
20 de septiembre de 2026 a las 21:55
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SKILL.md
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name
grafana
description
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.
# Grafana Integration ## Connection - **Base URL**: `$GRAFANA_URL` (e.g. `https://your-org.grafana.net`) - **Auth**: `Authorization: Bearer $GRAFANA_API_TOKEN` (service account token) - **Credentials**: `GRAFANA_URL`, `GRAFANA_API_TOKEN` from Settings → Data sources - **Caching**: 10-minute cache for metadata; query results are NOT cached (time-sensitive) - **Key datasource**: Prometheus UID `grafanacloud-prom` ## Server Lib & API Routes - **File**: `server/lib/grafana.ts` ### Exported Functions | 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` | ### API Routes | 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.) | ### Agent Action 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 | ### Dashboard - `/adhoc/engineering` — Engineering dashboard (mirrors a Grafana dashboard by UID) ## Grafana Response Frame Format ``` { results: { [refId]: { frames: [{ schema: { fields }, data: { values } }] } } } ``` - `values[0]` = timestamps (epoch ms), `values[1+]` = metric values - Series labels from `schema.fields[i].labels` (e.g. `{ model: "claude-3.5" }`) - Transform to Recharts: `{ time: number, [seriesName]: number }[]` ## Template Variables - `$CodegenMode` → default `quality-v4` - `$AIModel` → regex pattern, default `.*` (all) - `$environment` → `cloud` or `cloud-v2`, default `cloud` - Variables interpolated via string replace before querying ## Key Prometheus Metrics - **Codegen**: `vcpcodegen_completion_total`, `vcpcodegen_completion_latency_bucket`, `vcpcodegen_feedback_total`, `vcpcodegen_error_total` - **LLM**: `llm_completion_cost_total`, `llm_input_tokens_total`, `llm_output_tokens_total`, `llm_latency_bucket`, `llm_failures_total`, `llm_completions_total` - **Projects**: `projects_proposed_config_total`, `projects_status_total`, `projects_remote_machine_*`, `projects_start_duration_bucket` - **API/Runtime**: `api_request_total`, `with_span_duration_bucket`, `memory_heap_usage_percent_bucket` - **Fly.io**: `fly_endpoint_total`, `fly_machine_*` - **GitHub**: `builderbot_pr_created_total`, `builderbot_pr_closed_total` ## Key Patterns & Gotchas - `queryDatasource` constructs body with datasource UID in each query target; timestamps as string ms - `getAlertRules` flattens nested rule groups from unified alerting API - `getAlertInstances` handles both array and wrapped object response shapes - POST helper caches by default (fine for idempotent endpoints) but `queryDatasource` skips cache - Heatmap panels render as multi-series line/area (Recharts has no native heatmap; PromQL `histogram_quantile()` computes quantiles) ## Incident Investigation Pattern For production issues, query Grafana/Prometheus FIRST: 1. LLM latency by model (`llm_latency_bucket`) 2. Request rates (`api_request_total`) 3. Error rates (`llm_failures_total`) 4. Instance counts (via Cloud Monitoring) 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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