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Found 275 Skills
View Langfuse trace details. Use when checking specific trace input/output, debugging LLM calls, or analyzing costs.
Exclusive skill set for the GoFrame development framework. Provides comprehensive framework usage guidelines for Go language developers, covering best practices for core components such as command-line management, configuration management, logging components, error handling, data validation, type conversion, cache management, template engines, database ORM, and I18n internationalization. Includes project engineering structure specifications, development mode guidelines, common problem solutions, and rich practical code examples. Suitable for building various Go projects such as RESTful APIs, gRPC microservices, web applications, and CLI tools, helping developers quickly master GoFrame framework features, improve development efficiency and code quality.
Debug AI traces, find exceptions, analyze sessions, and manage prompts via Langfuse MCP. Also handles MCP setup and configuration.
Create, update, and manage Slot deployments for Katana and Torii services.
Use when deploying Docker Compose applications to production including security hardening, resource management, health checks, logging, monitoring, and high-availability patterns.
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
AI 도입 전략, Build vs Buy, 우선순위 설정, 거버넌스/보안, 6개월 확장 로드맵을 다루는 모듈.
Expert-level Grafana dashboards, visualization, data sources, alerting, and production operations
Fetch, organize, and analyze LangSmith traces for debugging and evaluation. Use when you need to: query traces/runs by project, metadata, status, or time window; download traces to JSON; organize outcomes into passed/failed/error buckets; analyze token/message/tool-call patterns; compare passed vs failed behavior; or investigate benchmark and production failures.
Internal skill. Use cc10x-router for all development tasks.
Asynchronous event-based communication to decouple producers/consumers for scalability and resilience. Triggers: event-driven, message queue, pub/sub, asynchronous, decoupling Use when: real-time workloads or multiple subsystems react to same events DO NOT use when: selecting paradigms (use architecture-paradigms first), simple request-response.
Consult this skill when designing data pipelines or transformation workflows. Use when data flows through fixed sequence of transformations, stages can be independently developed and tested, parallel processing of stages is beneficial. Do not use when selecting from multiple paradigms - use architecture-paradigms first. DO NOT use when: data flow is not sequential or predictable. DO NOT use when: complex branching/merging logic dominates.