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From grafana-app-sdk
Provides PromQL reference, alerting setup, recording rules, and Grafana Cloud Metrics integration patterns for Prometheus monitoring.
npx claudepluginhub grafana/skills --plugin grafana-coreHow this skill is triggered — by the user, by Claude, or both
Slash command
/grafana-app-sdk:prometheusThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Prometheus is an open-source monitoring and alerting toolkit for cloud-native environments. Combined with
Prometheus instrumentation discipline: right metric type, right name, right labels. Invoke whenever task involves any interaction with Prometheus metrics — instrumenting application code, writing PromQL queries, defining alerting or recording rules, choosing metric types, managing label cardinality, building exporters, or reviewing monitoring configuration.
Write, validate, and optimise PromQL queries for Prometheus and Grafana Cloud Metrics. Covers rates, aggregations, histogram quantiles, recording rules, and query debugging.
Generates PromQL queries, alerting/recording rules, and Prometheus dashboards via interactive workflow clarifying goals, metrics, and use cases like Grafana viz or troubleshooting.
Share bugs, ideas, or general feedback.
Prometheus is an open-source monitoring and alerting toolkit for cloud-native environments. Combined with Grafana Cloud Metrics (powered by Grafana Mimir), it provides a fully managed Prometheus-compatible service with long-term storage, global query performance, and enterprise scalability.
Key Differentiators: Pull-based model, dimensional data model with labels, PromQL, automatic service discovery, scales to billions of active series.
# By metric name
http_requests_total
# Label filter
http_requests_total{job="api-server"}
# Multiple labels (AND)
http_requests_total{job="api-server", method="GET"}
# Regex
http_requests_total{job=~"api.*", status=~"5.."}
# Negative
http_requests_total{status!="200"}
# Per-second rate over 5 minutes
rate(http_requests_total[5m])
# Increase over interval
increase(http_requests_total[1h])
# Instant rate (last two samples)
irate(http_requests_total[5m])
# Offset (5 minutes ago)
rate(http_requests_total[5m] offset 5m)
# Sum by label
sum by (job) (rate(http_requests_total[5m]))
# Average
avg by (instance) (node_cpu_seconds_total)
# Top-K
topk(5, rate(http_requests_total[5m]))
# Histogram quantiles
histogram_quantile(0.99, rate(http_request_duration_seconds_bucket[5m]))
# Count distinct
count(up{job="api"})
# Error rate percentage
sum(rate(http_requests_total{status=~"5.."}[5m]))
/ sum(rate(http_requests_total[5m])) * 100
# Saturation (CPU usage %)
100 - (avg by(instance) (irate(node_cpu_seconds_total{mode="idle"}[5m])) * 100)
# Memory usage
node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes
# Predict disk full (linear extrapolation)
predict_linear(node_filesystem_free_bytes[6h], 24*3600) < 0
Queryless Prometheus metrics exploration (preinstalled in Grafana 12+):
Route, group, silence, and deduplicate alerts. Multi-destination routing (PagerDuty, Slack, Email, webhooks).
Unified alerting across all data sources. Supports multi-dimensional alerts, notification policies, and contact points.
Pre-compute expensive PromQL queries for dashboard performance:
groups:
- name: api_rules
rules:
- record: job:http_requests:rate5m
expr: sum by (job) (rate(http_requests_total[5m]))