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Install and configure Langfuse SDK authentication for LLM observability.
Passed 22 of 22 test cases with the skill, and 10 of 22 without it.
and 20 more in the full report
12 fixed10 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 12 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are using the modern modular JS SDK setup for LLM tracing. Which npm package provides the drop-in wrapper for OpenAI calls, and what function is exported by it?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies @langfuse/openai as the npm package | Missed | Passed |
| Identifies observeOpenAI as the exported wrapper function | Missed | Passed |
The instructions your model reads when the skill loads.
Install the Langfuse SDK and configure authentication for LLM observability. Covers both the legacy langfuse package (v3) and the modern modular SDK (v4+/v5) built on OpenTelemetry.
pk-lf-...) and Secret Key (sk-lf-...) from project settingsTypeScript/JavaScript (v4+ modular SDK -- recommended):
set -euo pipefail
# Core client for prompt management, datasets, scores
npm install @langfuse/client
# Tracing (observe, startActiveObservation)
npm install @langfuse/tracing @langfuse/otel @opentelemetry/sdk-node
# OpenAI integration (drop-in wrapper)
npm install @langfuse/openai
# LangChain integration
npm install @langfuse/langchain
TypeScript/JavaScript (v3 legacy -- single package):
npm install langfuse
test cases passed, vs 10 / 22 without
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