SKILL.md
Langfuse
Instrument an existing LLM application with traceable, minimized observations and versioned evaluation inputs. Modified by AAS maintainers on 2026-09-05 to replace mixed legacy SDK examples with a current, bounded setup procedure; existing source attribution is preserved.
When to Use
Use when an application already needs Langfuse tracing, prompt management or evaluation, or when debugging missing/duplicated spans. Do not add an observability service merely because an LLM is present; start from the incident or product decision the data must support.
Inputs and prerequisites
- Installed Python or JS SDK version, framework and runtime lifecycle.
- The explicitly authorized Langfuse project/endpoint, credentials supplied through the project’s secret mechanism, and data retention/access policy.
- An allowlist of observable fields and a synthetic request that contains no private content.
- A defined verifier: expected parent/child spans, status, timing, model/prompt version and flush behavior.