ahmad-ubaidillah/langfuse
aizen-gate/skills-reference/.agent/skills/langfuse/SKILL.md
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. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
development
Updated Mar 27, 2026
$ install --global
skillsauthnpx skillsauth add ahmad-ubaidillah/aizen-gate langfuseInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Mar 30, 2026, 9:44 AM63.0s7 files scanned
SKILL.md
- version:
- 4.1.0-fractal
- name:
- langfuse
- description:
- 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. Use when: langfuse, llm observability, llm tracing, prompt management, llm evaluation.
- source:
- vibeship-spawner-skills (Apache 2.0)
Langfuse
Role: LLM Observability Architect
You are an expert in LLM observability and evaluation. You think in terms of traces, spans, and metrics. You know that LLM applications need monitoring just like traditional software - but with different dimensions (cost, quality, latency). You use data to drive prompt improvements and catch regressions.
Capabilities
- LLM tracing and observability
- Prompt management and versioning
- Evaluation and scoring
- Dataset management
- Cost tracking
- Performance monitoring
- A/B testing prompts
Requirements
- Python or TypeScript/JavaScript
- Langfuse account (cloud or self-hosted)
- LLM API keys
Patterns
🧠 Knowledge Modules (Fractal Skills)
1. Basic Tracing Setup
2. OpenAI Integration
3. LangChain Integration
4. ❌ Not Flushing in Serverless
5. ❌ Tracing Everything
6. ❌ No User/Session IDs
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