Observe by Snowflake

alert-investigation

Investigate alerts using systematic SRE methodology to understand issues, assess impact, test hypotheses, and identify root causes with evidence-based analysis. Use when: (1) User asks to investigate or analyze an alert (2) User mentions a specific alert or monitor that is firing

debug-k8s-collection

Troubleshoot and debug Observe Agent data collection on Kubernetes. Use this skill whenever the user reports any K8s-side problem with Observe — pods crashing, stuck Pending, ImagePullBackOff, "no data in Observe", missing datastreams, suspected token/secret issues, endpoint reac

debug-linux-host-collection

Troubleshoot and debug Observe Agent data collection on Linux hosts. Use this skill whenever the user reports any host-side problem with Observe — the agent failing to start, `observe-agent status` reporting errors, `init-config` failing with unknown flags, "no data in Observe" f

deploy-k8s-explorer

End-to-end onboarding of a Kubernetes cluster to Observe — creates the backend datastreams + content via the Observe CLI and deploys the observe/agent helm chart. Use for ANY request to install or set up the Observe Agent on Kubernetes, onboard a K8s cluster to Observe, or send K

deploy-linux-host-explorer

End-to-end Host Explorer deployment for Observe — creates backend resources (datastreams, content, ingest token) via the Observe CLI and installs the observe-agent on a Linux host. Use this skill whenever the user mentions setting up Observe on a Linux machine, onboarding a host

generate-opal

Contains dataset kind selection, column selection rules, core syntax, and the skill index. NEVER generate OPAL, and NEVER invoke an opal-* reference, without first loading this skill.

observe-cli

Use the Observe CLI (`observe`) to investigate production systems and pull telemetry. Reach for this skill whenever the user wants to: search or tail logs; query metrics (CPU, memory, latency, error rate, request volume, custom app metrics); explore traces and spans; correlate ev

opentelemetry-auto-instrumentation

Installs and configures OpenTelemetry auto-instrumentation for applications written in Java, .NET, Node.js, Python, Ruby. Use when instrumenting applications with opentelemetry auto-instrumentation, auditing existing auto-instrumentation implementations, migrating from vendor lo

opentelemetry-manual-instrumentation

Add, change, or debug OpenTelemetry (OTel) instrumentation in code: custom spans, metrics, logs, attributes, context propagation, and resource attributes. Use when writing, changing, reviewing, or debugging manual instrumentation, including OTel SDK setup.

opentelemetry-validation

Canned queries for various APM features in Observe. Use to validate auto-instrumentation, or when validating or troubleshooting OpenTelemetry instrumentation for a service sending telemetry to Observe.

outlier-detection-analysis

Identify which field values correlate with bad behavior (slowness, errors, anomalies, unusual values) using phi-coefficient correlation analysis over OPAL. Works on any time-series data — metrics, structured logs, span/trace data, or any dataset where rows can be split into a 'ba

query-card-visualization

How to fill in a query card's `visualizationTemplate` (the JSON object that renders a chart). Load this whenever the user asks for a chart, graph, plot, trend, "show me over time", ranking, single number/KPI, scatter, waterfall, or map. Acts as the directory for the per-chart JSO