Honeycomb is the observability platform that enables engineering teams to find and solve problems they couldn't before.
Honeycomb's skills equip AI agents to instrument applications with OpenTelemetry, including GenAI and LLM calls, and to migrate legacy Beeline code to OTel. They also guide agents through querying trace, log, event and metrics datasets, investigating production issues to a root cause, and building dashboards and reviewing SLO and trigger status. The set stands out for covering the full observability loop, from instrumentation through investigation to alerting.
Agent Skill
11 skills · 28 stars · MIT
Beeline Migration Migrating from Honeycomb Beelines (End of Life) to OpenTelemetry.
Create Honeycomb Board Design and create a Honeycomb board (dashboard) with queries and SLOs.
Metrics Queries Querying OpenTelemetry metrics datasets in Honeycomb, whose rules differ from trace/event dataset…
Observability Fundamentals First principles of observability: wide events, high cardinality, the core analysis loop, events…
Otel Genai Instrumentation Instrumenting GenAI/LLM applications with OpenTelemetry for Honeycomb, including content capture…
Otel Instrumentation OpenTelemetry SDK setup, custom instrumentation, and sending data to Honeycomb.
Otel Migration Retrofitting OpenTelemetry into an existing, uninstrumented application.
Production Investigation Workflows for investigating production issues in Honeycomb: context priming, broad query, BubbleU…
Query Patterns Constructing and interpreting Honeycomb queries on trace, log and event datasets: operation selec…
Slos And Triggers Interpreting Honeycomb SLO compliance, burn rates and trigger status, and what to do about them:…
Verify Recent Trace Find a recent trace in Honeycomb, to see what happened in a recent test.