verify-recent-trace

Migrating from Honeycomb Beelines (End of Life) to OpenTelemetry. Trigger phrases: "migrate from Beelines", "upgrade from Beeline to OpenTelemetry", "migrate to OTel", "replace Beelines", "Beeline end of life", "Beeline EOL", "switch from Beeline to OTel", "migrate Go/Python/Node/Java/Ruby Beeline", "W3C trace headers", "W3C propagation", "incremental migration to OpenTelemetry".

Design and create a Honeycomb board (dashboard) with queries and SLOs. Trigger phrases: "make a board", "build a dashboard", "create a Honeycomb board", "make a dashboard in Honeycomb", "set up a board", "dashboard for my service", "visualize service health", "golden signals dashboard", "set up monitoring board".

Querying OpenTelemetry metrics datasets in Honeycomb, whose rules differ from trace/event datasets: bare COUNT, RATE_SUM, RATE_AVG, RATE_MAX and CONCURRENCY are forbidden, temporal aggregation is automatic, and each metric has its own attributes. Use for gauges, counters, histograms and sums; temporal aggregation (RATE, INCREASE, SUMMARIZE, LAST); finding the metrics dataset, metric names and attributes; unexpected metrics results; infrastructure metrics (CPU, memory, disk I/O, network). Not for instrumenting metrics (use otel-instrumentation), event datasets with "metrics" in their name, or conceptual questions (use observability-fundamentals).

First principles of observability: wide events, high cardinality, the core analysis loop, events vs metrics vs logs, and how instrumentation connects to debugging. Trigger phrases: "what is observability", "why observability", "why Honeycomb", "events vs metrics vs logs", "why wide events", "what is high cardinality", "core analysis loop", "observability vs monitoring", "what is dimensionality", "explain observability".

Instrumenting GenAI/LLM applications with OpenTelemetry for Honeycomb, including content capture and agent failure detection. Trigger phrases: "instrument my GenAI app", "add tracing to LLM calls", "trace AI agent", "instrument OpenAI", "instrument Anthropic", "GenAI observability", "trace tool calling", "LLM token usage", "instrument embeddings", "trace MCP", "GenAI metrics", "instrument LangChain", "add GenAI spans", "capture prompts", "capture LLM responses", "enable GenAI content capture", "streaming tracing", "trace streaming responses".

OpenTelemetry SDK setup, custom instrumentation, and sending data to Honeycomb. Trigger phrases: "instrument my app", "add tracing", "set up OpenTelemetry", "configure OTel", "add custom spans", "add attributes to spans", "send traces to Honeycomb", "set up OTLP", "configure sampling", "add span events", "add span links", "set up tracing for [any language]", "configure the OTel Collector".

Retrofitting OpenTelemetry into an existing, uninstrumented application. Trigger phrases: "migrate existing app to OTel", "add OpenTelemetry to existing project", "retrofit OTel into my codebase", "thread context through my code", "context propagation", "bridge Prometheus metrics to OTel", "logging bridge", "migrate logging to OTel", "slog bridge", "logback bridge", "verify my instrumentation", "traces are disconnected", "orphaned spans", "migrate to OpenTelemetry", "OTel migration plan", "how do I sequence an OTel migration", "add tracing to existing code", "refactor for context propagation", "Fiber context gotcha", "keep existing logging working with OTel", "add OTel without breaking Prometheus", "bridge existing metrics", "coexist with existing monitoring". For greenfield instrumentation use otel-instrumentation; for Beelines use beeline-migration.

Workflows for investigating production issues in Honeycomb: context priming, broad query, BubbleUp, trace analysis, verification, and chaining results between steps to a root cause. Trigger phrases: "investigate production issue", "debug latency spike", "find root cause", "use BubbleUp", "analyze traces", "debug an outage", "why is my API slow", "errors are increasing", "health check", "SLO burning".

Configure this repo for the engineering skills: set up its issue tracker, triage label vocabulary, and domain doc layout. Run once before first use of the other engineering skills.

Teach the user a new skill or concept, within this workspace.

Ask which skill or flow fits your situation. A router over the skills in this repo.

Plan a huge chunk of work (more than one agent session can hold) as a shared map of decision tickets on your issue tracker, and resolve them one at a time until the way to the destination is clear.

Hand the current conversation off to a fresh background agent that picks up the work immediately.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

Use when starting any conversation - establishes how to find and use skills, requiring skill invocation before ANY response including clarifying questions

Use when executing implementation plans with independent tasks in the current session