Loading...
Loading...
Found 472 Skills
Expert-level Grafana dashboards, visualization, data sources, alerting, and production operations
Hermes-native AIOps agent for evidence-driven incident response, approval-gated remediation, and runbook learning
Troubleshoot Coval OpenTelemetry trace ingestion, missing trace UI, sparse traces, bad simulation or conversation correlation, auth/org errors, oversized payloads, duplicate spans, and production debugging with Trace Search.
Every PostHog resource in one CLI — with offline search, agent-native output, and cross-resource analytics no... Trigger phrases: `check my PostHog feature flags`, `query PostHog events`, `show experiment results in PostHog`, `what errors are spiking in PostHog`, `LLM costs in PostHog`, `is it safe to ramp this flag`, `use posthog`.
Use when one Python service must send each agent's, tenant's, team's, or request's spans to its correct Arize space and project using application metadata. Covers dynamic OpenTelemetry routing for custom agent builders and multi-tenant applications, including register_with_routing, set_routing_context, multi-space tracing, and custom span routing.
CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD, GitOps, monitoring.
Sets up TraceKit APM in Next.js applications with multi-runtime support, error boundaries, and distributed tracing. Covers both App Router and Pages Router architectures.
Logz.io integration. Manage data, records, and automate workflows. Use when the user wants to interact with Logz.io data.
General OpenTelemetry onboarding style for Superlog managed agents: native APIs, signal quality, env vars, LLM metrics, and smoke checks.
Analyze production Agentforce agent behavior using session traces and Data Cloud. TRIGGER when: user queries STDM session data or Data Cloud trace records; investigates production agent failures, regressions, or performance issues; asks about session traces, conversation logs, or agent metrics; wants to reproduce a reported production issue in preview; runs findSessions or trace analysis queries. DO NOT TRIGGER when: user creates, modifies, or debugs .agent files during development (use developing-agentforce); writes or runs test specs (use testing-agentforce); uses sf agent preview for local development iteration; deploys or publishes agents.
Generates a self-contained Python experiment client that uses the ddtrace.llmobs SDK. Emits either a runnable .py script or a Jupyter .ipynb notebook matching the canonical DataDog reference notebook style. Use when the user says "generate Python experiment", "write an SDK experiment", "create a ddtrace experiment", "Python notebook experiment", "use the LLM Obs SDK", or has `ddtrace` installed and wants idiomatic SDK code.
Design structured logging systems with context propagation. Use to ensure Python applications are observable and logs are machine-readable.