Skill: Grafana Tempo & TraceQL
by Grafana Labs
Grafana's official Tempo skill: stand up a tracing backend that needs nothing but object storage, then write TraceQL that finds the slow span instead of scrolling for it.
Grafana's official Alloy skill: write one collector config that carries metrics, logs, traces and profiles, validate it locally, and prove samples are actually leaving the box.
Add this skill to your favorite AI agent in a few steps.
Grafana Alloy is a single OpenTelemetry-compatible binary that replaces Grafana Agent and, for most stacks, a separate OTel Collector — one process collecting metrics, logs, traces and profiles and shipping them to Grafana Cloud, Prometheus, Loki, Tempo and Pyroscope. This is Grafana Labs' official skill for writing and debugging its configuration.
The config language is the part people get wrong, because Alloy components reference each other by name rather than sitting in a YAML pipeline list. The skill covers blocks, attributes and expressions, sys.env for secrets, and the component-reference syntax that connects prometheus.scrape to prometheus.remote_write.cloud.receiver. Complete, runnable configs are given for the three pipelines that cover most deployments: Prometheus scrape to remote write, loki.source.file through loki.process to loki.write, and an OTLP receiver forwarding to a Tempo exporter with otelcol.auth.basic.
What sets it apart is that each workflow ends with verification rather than a claim of success. alloy fmt and alloy validate catch syntax before a run; a jq filter against the component API on port 12345 lists any component that is not healthy and why; and prometheus_remote_storage_samples_total plus enqueue_retries_total confirm data is genuinely flowing rather than queueing. The log and trace pipelines get equivalent checks through loki.source.file targets and otelcol_receiver_accepted_spans.
Wider ground covered includes Kubernetes, Docker and EC2 service discovery with relabeling, modules via import.file / import.git / import.http, clustering, and Fleet Management through remotecfg. The troubleshooting section maps the failures that actually happen — "component not found" from an outdated binary, unhealthy components in the UI, dropped remote-write samples, and refused spans on the OTLP receiver — to the specific metric or page that identifies the cause.
Apache-2.0, part of the grafana/skills repository, installable via npx skills add grafana/skills or the Claude Code plugin marketplace. A companion reference carries the full component catalogue and end-to-end pipelines for all four signals.
by Grafana Labs
Grafana's official Tempo skill: stand up a tracing backend that needs nothing but object storage, then write TraceQL that finds the slow span instead of scrolling for it.
by Grafana Labs
Grafana's official Loki skill: write LogQL that returns rows instead of timeouts, ship logs through Alloy, and reason about a store that indexes labels rather than log text.
by Grafana Labs
Grafana's official PromQL skill: write, validate, and optimise Prometheus queries, and hunt down the label that blew up your cardinality.
by Datadog
Install, instrument and analyse Datadog APM from an agent — Kubernetes and Linux Single-Step Instrumentation, service remapping, trace search and service maps.