langfuse-trace
Analyze Langfuse trace JSON exports using jq queries. Use when user provides a Langfuse trace file (.json) for analysis, debugging agent behavior, checking token usage, or investigating tool calls. Triggers on...
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Analyze Langfuse trace JSON exports using jq queries. Use when user provides a Langfuse trace file (.json) for analysis, debugging agent behavior, checking token usage, or investigating tool calls. Triggers on...
Expert prompt engineering for Claude 4.x models (Sonnet 4.5, Opus 4.5, Haiku 4.5). Use when creating system prompts, optimizing existing prompts, designing agentic workflows, or improving prompt effectiveness....
AI 에이전트를 위한 고품질 프롬프트를 생성하는 스킬. 스킬/에이전트/MCP 서버/일반 코딩 작업을 위한 프롬프트를 한국어로 생성. 사용자가 "프롬프트 만들어줘", "프롬프트 생성", "프롬프팅 해줘", "~를 위한 프롬프트", "~...
LLM이 잘 설계된 도구를 통해 외부 서비스와 상호작용할 수 있게 하는 고품질 MCP(Model Context Protocol) 서버 생성 가이드. Python(FastMCP)이나 Node/TypeScript(MCP SDK)로 외부 API나 서비스를 통합하는 MCP 서버를 구축...
효과적인 스킬 생성 가이드. 사용자가 Claude의 기능을 전문 지식, 워크플로우, 도구 통합으로 확장하는 새 스킬을 만들거나 기존 스킬을 업데이트하려 할 때 사용한다.
Claude Code용 커스텀 서브에이전트 생성. .claude/agents 또는 ~/.claude/agents에 새 에이전트를 생성, 추가, 구성하려 할 때 사용한다. "에이전트 만들어줘", "에이전트 생성", "서브에이전트 추가", "~를 위한 에이전트 만...
This skill should be used when the user asks to "use the oracle" or "ask the oracle" for deep research, analysis, or architectural questions. The oracle excels at multi-source research combining codebase explor...
This skill should be used when the user asks to "use delphi", "ask delphi", or wants multiple parallel oracle investigations of the same question to discover divergent insights. Delphi launches multiple oracle...
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
Chain Vibery commands, skills, and agents into repeatable automated workflows. Outputs: Executable workflow files, hook configurations, CI/CD integration. Use when user has repetitive multi-step processes to au...
Build AI agents with Google's Agent Development Kit (ADK) Python - an open-source toolkit for building, evaluating, and deploying AI agents. Features LlmAgent, workflow agents (sequential, parallel, loop), tool...
Manage Model Context Protocol (MCP) servers - discover, analyze, and execute tools/prompts/resources from configured MCP servers. Use when working with MCP integrations, need to discover available MCP capabilit...
Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn/ui). Use for complex artifacts requiring state management, rou...
Replace with description of the skill and when Claude should use it.
Master context engineering for AI agents - token optimization, degradation patterns, compression, memory systems, multi-agent coordination, evaluation. Use when designing agents, debugging context failures, or...
Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or...
Transform conversations and ideas into structured technical specifications. Outputs: User stories, acceptance criteria, technical requirements, edge cases. Use when user wants to document requirements before co...
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hour...
A set of resources to help me write all kinds of internal communications, using the formats that my company likes to use. Claude should use this skill whenever asked to write some sort of internal communication...
API authentication patterns, SDK installation scripts, environment variable management, and connection testing for ElevenLabs. Use when setting up ElevenLabs authentication, installing ElevenLabs SDK, configuri...
Production deployment patterns for ElevenLabs API including rate limiting, error handling, monitoring, and testing. Use when deploying to production, implementing rate limiting, setting up monitoring, handling...
Agent-to-Agent (A2A) protocol implementation patterns for Google ADK - exposing agents via A2A, consuming external agents, multi-agent communication, and protocol configuration. Use when building multi-agent sy...
Memory layer integration patterns for FastAPI with Mem0 including client setup, memory service patterns, user tracking, conversation persistence, and background task integration. Use when implementing AI memory...
Templates and patterns for common ML training scenarios including text classification, text generation, fine-tuning, and PEFT/LoRA. Provides ready-to-use training configurations, dataset preparation scripts, an...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库,同一仓库的多个技能可能共享相同数值;它反映仓库关注度,不代表单个技能的安装量或质量评分。