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Found 25 Skills
Instrument LLM applications with Langfuse tracing. Use when setting up Langfuse, adding observability to LLM calls, or auditing existing instrumentation.
Comprehensive backend development guide for Langfuse's Next.js 14/tRPC/Express/TypeScript monorepo. Use when creating tRPC routers, public API endpoints, BullMQ queue processors, services, or working with tRPC procedures, Next.js API routes, Prisma database access, ClickHouse analytics queries, Redis queues, OpenTelemetry instrumentation, Zod v4 validation, env.mjs configuration, tenant isolation patterns, or async patterns. Covers layered architecture (tRPC procedures → services, queue processors → services), dual database system (PostgreSQL + ClickHouse), projectId filtering for multi-tenant isolation, traceException error handling, observability patterns, and testing strategies (Jest for web, vitest for worker).
Create or update Langfuse prompt with development label. Use when creating new prompts, updating existing prompts, or improving prompt content.
LLM observability platform for tracing, evaluation, prompt management, and cost tracking. Use when setting up Langfuse, monitoring LLM costs, tracking token usage, or implementing prompt versioning.
Add new LLM model pricing entries to Langfuse's default-model-prices.json. Use when adding model prices, updating model pricing, creating model entries, adding Claude/OpenAI/Anthropic/Google/Gemini/AWS Bedrock/Azure/Vertex AI model pricing, working with matchPattern regex, pricingTiers, or model cost configuration. Covers model price JSON structure, regex patterns for multi-provider matching, tiered pricing with conditions, cache pricing, and validation rules.
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.
Set up Langfuse local development workflow with hot reload and debugging. Use when developing LLM applications locally, debugging traces, or setting up a fast iteration loop with Langfuse. Trigger with phrases like "langfuse local dev", "langfuse development", "debug langfuse traces", "langfuse hot reload", "langfuse dev workflow".
Query Langfuse traces for debugging LLM calls, analyzing token usage, and investigating workflow executions. Use when debugging AI/LLM behavior, checking trace data, or analyzing observability metrics.
LLM cost tracking with Langfuse for cached responses. Use when monitoring cache effectiveness, tracking cost savings, or attributing costs to agents in multi-agent systems.
Monitoring and observability patterns for Prometheus metrics, Grafana dashboards, Langfuse LLM tracing, and drift detection. Use when adding logging, metrics, distributed tracing, LLM cost tracking, or quality drift monitoring.
Discovers, tests, and manages remote SSH infrastructure hosts and Docker services across 5 hosts (infra.local, deus, homeassistant, pi4-motor, armitage). Use when checking infrastructure status, verifying service connectivity, managing Docker containers, troubleshooting remote services, or before using remote resources (MongoDB, Langfuse, OTLP, Neo4j). Triggers on "check infrastructure", "connect to infra/deus/ha", "test MongoDB on infra", "view Docker services", "verify connectivity", "troubleshoot remote service", "what services are running", or when remote connections fail.
Adds new users to Cloudflare Access authentication by updating ACCESS_ALLOWED_EMAIL in .env and syncing policies to all protected services. Use when you need to grant access to a new user, add someone to the network, share service access, or update allowed emails. Triggers on "add user to access", "grant access to [email]", "add [email] to cloudflare", "share access with", "allow [email] to authenticate", or "update access users". Works with .env, update-access-emails.sh, and Cloudflare Access policies for pihole, jaeger, langfuse, sprinkler, ha, and temet.ai services.