ai-observability-langfuse

# Langfuse Observability Patterns > **Quick Guide:** Use the Langfuse TypeScript SDK (built on OpenTelemetry) to add observability to LLM applications. Install `@langfuse/tracing`, `@langfuse/otel`, and `@opentelemetry/sdk-node` for core tracing. Use `startActiveObservation()` for automatic context propagation or `observe()` to wrap functions. Use `@langfuse/openai` with `observeOpenAI()` for zero-config OpenAI tracing. Use `LangfuseClient` from `@langfuse/client` for prompt management, scores, and datasets. Always call `forceFlush()` or `sdk.shutdown()` in short-lived processes. --- <critical_requirements> ## CRITICAL: Before Using This Skill > **All code must follow project conventions in CLAUDE.md** (kebab-case, named exports, import ordering, `import type`, named constants) **(You MUST import and register `instrumentation.ts` at the top of your entry point BEFORE any other imports -- OpenTelemetry must instrument modules before they are loaded)** **(You MUST call `forceFlush()` or `sdk.shutdown()` in short-lived processes (serverless, scripts, CLI tools) -- events are batched and will be lost without explicit flushing)** **(You MUST use `@langfuse/openai` with `observeOpenAI()` for OpenAI SDK tracing -- do NOT manually create generation observations for OpenAI calls when the wrapper handles it automatically)** **(You MUST set `LANGFUSE_SECRET_KEY`, `LANGFUSE_PUBLIC_KEY`, and `LANGFUSE_BASE_URL` via environment variables -- never hardcode credentials)** **(You MU...