testland/langfuse-tracing
Wires Langfuse tracing into LLM apps for production observability, monitoring, telemetry, and offline eval - instruments via `@observe` (Python) / `startActiveObservation` (TS) decorators that auto-capture inputs / outputs / timings / errors per generation; exposes `langfuse.update_current_span()` for metadata + cost / latency annotation; supports trace-bound scoring for eval datasets and prompt-as-code management. Use when the user needs to monitor, log, trace, or debug LLM API calls in production beyond pre-deploy eval, wants to add LLM observability tooling to an existing app, or wants to ship traces from production to an eval dataset for offline regression testing.
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tile.json
{
"name": "testland/langfuse-tracing",
"version": "1.3.6",
"summary": "Wires Langfuse tracing into LLM apps for production observability, monitoring, telemetry, and offline eval - instruments via `@observe` (Python) / `startActiveObservation` (TS) decorators that auto-capture inputs / outputs / timings / errors per generation; exposes `langfuse.update_current_span()` for metadata + cost / latency annotation; supports trace-bound scoring for eval datasets and prompt-as-code management. Use when the user needs to monitor, log, trace, or debug LLM API calls in production beyond pre-deploy eval, wants to add LLM observability tooling to an existing app, or wants to ship traces from production to an eval dataset for offline regression testing.",
"private": false,
"skills": {
"langfuse-tracing": {
"path": "SKILL.md"
}
}
}