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Found 69 Skills
Set up orq.ai observability for LLM applications. Use when setting up tracing, adding the AI Router proxy, integrating OpenTelemetry, auditing existing instrumentation, or enriching traces with metadata.
Implement OpenTelemetry (OTEL) observability - Collector configuration, Kubernetes deployment, traces/metrics/logs pipelines, instrumentation, and troubleshooting. Use when working with OTEL Collector, telemetry pipelines, observability infrastructure, or Kubernetes monitoring.
Create professional engineering diagrams using drawio XML format with industry-standard symbols. Best for electrical schematics, P&ID (Piping & Instrumentation), rack diagrams, fault tree analysis, PLC ladder logic, and logic gate diagrams. Built on drawio with engineering-specific stencils. NOT for simple flowcharts (use mermaid) or network topology (use network skill).
Set up Kafka-based event-driven microservices with Platformatic Watt. Use when users ask about: - "kafka", "event-driven", "messaging" - "kafka hooks", "kafka webhooks" - "kafka producer", "kafka consumer" - "dead letter queue", "DLQ" - "request response pattern" with Kafka - "migrate from kafkajs", "kafkajs migration", "replace kafkajs" Covers @platformatic/kafka, @platformatic/kafka-hooks, consumer lag monitoring, and OpenTelemetry instrumentation.
Guides research engineering and science on LLM tokens—hypotheses about context use, tokenization, compression, and inference efficiency; rigorous benchmarks (tokens per task, quality–cost Pareto); ablation design; instrumentation and reproducible logs; and research memos that inform product decisions. Use when designing token-efficiency experiments, measuring context utilization, comparing compression or routing methods, analyzing tokenizer effects, or writing technical reports on token/cost trade-offs—not for phased cost roadmaps and owners (ai-token-improvement-plan-engineer), production context pipeline implementation (ai-context-engineer), single-prompt edits (prompt-engineer), general non-token AI research (ai-researcher), or shipping features (ai-engineer).
Product analytics instrumentation and strategy covering event taxonomy design, tracking plans, user behavior analysis, activation/retention metrics, and marketing attribution. PostHog-first with multi-platform support (Pendo, Amplitude, Mixpanel, Heap).
Implements comprehensive observability with OpenTelemetry tracing, Prometheus metrics, and structured logging. Includes instrumentation plans, sample dashboards, and alert candidates. Use for "observability", "monitoring", "tracing", or "metrics".
OpenTelemetry observability - use for distributed tracing, metrics, instrumentation, Sentry integration, and monitoring
Use this skill first whenever the user asks about SigNoz instrumentation, OpenTelemetry setup, querying, dashboards, alerts, troubleshooting, self-hosted deployment, API endpoints, auth headers, or where to find anything in SigNoz docs.
Designs and reviews WebMCP instrumentation for existing web apps, especially SPAs. Use when adding agent-accessible tools, route maps, prompts, or WebMCP workflows to a React, Vue, Angular, or vanilla browser app, or when deciding whether WebMCP is the right fit.
Observability and monitoring for data pipelines using OpenTelemetry (traces) and Prometheus (metrics). Covers instrumentation, dashboards, and alerting.
OpenTelemetry with Grafana stack. Covers OTel SDK instrumentation for Go/Java/Python/Node.js/.NET, OTLP protocol and endpoint configuration, sending telemetry to Grafana Cloud via OTLP endpoint, Grafana Alloy as OTel collector, sampling strategies, Kubernetes OTel Operator, and migration from other observability tools. Use when instrumenting apps with OTel, configuring OTLP endpoints, setting up collectors, or migrating to OpenTelemetry.