langfuse
Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.
Product ManagementAI & AutomationSecurity
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.
Procedure
- Inspect the dependency lock and existing instrumentation. Do not mix old
langfuse.trace(),langfuse.decoratorsorlangfuse.callbackexamples with the current SDK without checking its migration guide. - Choose one integration layer: direct SDK spans, a framework callback or OpenTelemetry instrumentation. Avoid tracing the same call twice through ov
Subscribers only
The full skill, its 1 bundled files and every download is included with every paid Complete AI plan.
Details
| Source | vibeship-spawner-skills (Apache 2.0) |
|---|---|
| License | — |
| Risk label | critical ("critical" means the skill may run commands or touch files — read before use) |
| Files | SKILL.md |
| Added | 2026-02-27 |
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