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langfuse-docs

Skill Documents & Content Early

🪢 Langfuse documentation -- Langfuse is the open source LLM Engineering Platform. Observability, evals, prompt management, playground and metrics to debug and improve LLM apps

187 starsMIT (commercial OK)FreeQuick setup
New Find — Recently discovered. Looks promising but has limited community feedback so far. We added it early so you can evaluate it before the crowd finds it.

Makes Langfuse's full documentation available as a skill, giving AI agents instant access to LLM observability, evaluation, and prompt management guidance. Speeds up integration and debugging of AI pipelines.

ML engineers and AI teams building production LLM applications who need quick access to Langfuse observability and evaluation guidance.

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https://github.com/langfuse/langfuse-docs

By langfuse

How to Get It

Option 1: Claude Desktop App (Code Mode)Click the + button next to the prompt box → PluginsAdd plugin. Search and click Install. Skills work in Claude Code only.
Option 2: Paste into Claude CodeCopy the command below and paste it into your conversation. Claude will install it.
Command
claude plugins install langfuse/langfuse-docs

Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.

CostFree

Trust Signals Auto-scanned

Stars187Last updated2026-04-16T12:44:31ZLicenseMIT (OK for commercial use)Known CVEsNone foundSources: GitHub Advisory Database + OSV.dev · Scanned 2026-04-16 · scanner v1

Community Pulse Active

Discussed on Hacker News, Reddit

14 mentions across 2 sources

Reviewer notes

Auto-scanned review. These are observations, not a security certification.

Scored from trust signals (evidence-eval-v1): 187 GitHub stars; contributors unknown; last commit 34d ago; license MIT.

How to evaluate tools before deploying →

Data shown here comes from public APIs and automated scanning. Reviewer notes reflect one person's experience. This is not a security certification or legal recommendation. Always evaluate tools according to your own organization's policies.

Evaluation

Ease of Use
3/5
Versatility
3/5
Reliability
3/5
Security
3/5
Overall score3.00 / 5.00 EarlyEvaluatedMay 2026
Scored from trust signals (evidence-eval-v1): 187 GitHub stars; contributors unknown; last commit 34d ago; license MIT.

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