langfuse-cost-tuning
Monitor and optimize LLM costs using Langfuse analytics and dashboards. Use when tracking LLM spending, identifying cost anomalies, or implementing cost controls for AI applications. Trigger with phrases like "langfuse costs", "LLM spending", "track AI costs", "langfuse token usage", "optimize LLM budget".
npx skills add majiayu000/claude-skill-registry --skill langfuse-cost-tuning --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 Cost Tuning ## Overview Track, analyze, and optimize LLM costs using Langfuse observability data. ## Prerequisites - Langfuse tracing with token usage - Understanding of LLM pricing models - Access to Langfuse analytics dashboard ## LLM Cost Reference | Model | Input (per 1M) | Output (per 1M) | |-------|----------------|-----------------| | GPT-4 Turbo | $10.00 | $30.00 | | GPT-4o | $5.00 | $15.00 | | GPT-4o-mini | $0.15 | $0.60 | | GPT-3.5 Turbo | $0.50 | $1.50 | | Claude 3 Opus | $15.00 | $75.00 | | Claude 3 Sonnet | $3.00 | $15.00 | | Claude 3 Haiku | $0.25 | $1.25 | ## Instructions ### Step 1: Track Token Usage in Generations ```typescript import { Langfuse } from "langfuse"; const langfuse = new Langfuse(); // Model pricing configuration const MODEL_PRICING: Record< string, { input: number; output: number } > = { "gpt-4-turbo": { input: 10.0, output: 30.0 }, "gpt-4o": { input: 5.0, output: 15.0 }, "gpt-4o-mini": { input: 0.15, output: 0.6 }, "gpt-3.5-turbo": { input: 0.5, output: 1.5 }, "claude-3-opus": { input: 15.0, output: 75.0 }, "claude-3-sonnet": { input: 3.0, output: 15.0 }, "claude-3-haiku": { input: 0.25, output: 1.25 }, }; function calculateCost( model: s
- Overview
- Prerequisites
- LLM Cost Reference
- Instructions
- Step 1: Track Token Usage in Generations
- Step 2: Create Cost Dashboard Queries
- Step 3: Implement Cost Alerts
- Step 4: Implement Cost Optimization Strategies
- Step 5: Generate Cost Reports
- Output
- Cost Optimization Strategies
- Error Handling
- Resources
- Next Steps
What does the langfuse-cost-tuning skill do?
Monitor and optimize LLM costs using Langfuse analytics and dashboards. Use when tracking LLM spending, identifying cost anomalies, or implementing cost controls for AI applications. Trigger with phrases like "langfuse costs", "LLM spending", "track AI costs", "langfuse token usage", "optimize LLM budget".
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill langfuse-cost-tuning --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.