langfuse-extraction
Extracts traces, observations, and metrics from Langfuse Cloud (EU) API for debugging, telemetry analysis, and regulatory audit trails. Generates ALCOA+ compliant reports, exports to pandas DataFrame, and supports time-range/user/session filtering. Use when investigating production issues, generating compliance documentation, or analyzing LLM costs and performance. MUST BE USED for pharmaceutical audit trail generation requiring GAMP-5 traceability.
npx skills add majiayu000/claude-skill-registry --skill langfuse-extraction --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Langfuse Extraction Skill **Purpose**: Extract observability data from Langfuse Cloud API for analysis, debugging, and compliance reporting. --- ## When to Use This Skill ✅ **Use when**: - Investigating production workflow failures or performance issues - Generating ALCOA+ compliant audit trails for regulatory review - Analyzing LLM token usage and costs across sessions - Exporting trace data to pandas for statistical analysis - Creating compliance reports for GAMP-5 validation - Debugging specific user sessions or workflows ❌ **Do NOT use when**: - Adding instrumentation to code (use `langfuse-integration` skill) - Interacting with Langfuse dashboard UI (use `langfuse-dashboard` skill) --- ## Prerequisites 1. **Langfuse API Keys** configured in environment 2. **langfuse** Python package installed 3. Traces already exist in Langfuse Cloud from instrumented workflows --- ## Workflow Phases ### Phase 1: Extract Recent Traces (Time-Range Query) **Use case**: Get last 24 hours of traces for monitoring/debugging. ```python # scripts/extract_traces.py --hours 24 --output recent_traces.json from langfuse import Langfuse from datetime import datetime, timedelta import json langfuse = Lan
- When to Use This Skill
- Prerequisites
- Workflow Phases
- Phase 1: Extract Recent Traces (Time-Range Query)
- Phase 2: Extract Detailed Observations (Span Analysis)
- Phase 3: Generate ALCOA+ Audit Trail
- Phase 4: Export to Pandas DataFrame
- Success Criteria
- Reference Materials
What does the langfuse-extraction skill do?
Extracts traces, observations, and metrics from Langfuse Cloud (EU) API for debugging, telemetry analysis, and regulatory audit trails. Generates ALCOA+ compliant reports, exports to pandas DataFrame, and supports time-range/user/session filtering. Use when investigating production issues, generating compliance documentation, or analyzing LLM costs and performance. MUST BE USED for pharmaceutical audit trail generation requiring GAMP-5 traceability.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langfuse-extraction --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.