Total 57,164 skills, AI & Machine Learning has 9510 skills
Showing 12 of 9510 skills
Install the Vercel AI SDK with AI Elements components. Build a streaming chat interface with the useChat hook.
Core trading insights learned from Agent Arena competition. Use when making any trading decision to apply institutional knowledge.
This skill should be used when the user asks about "plugin settings", "store plugin configuration", "user-configurable plugin", ".local.md files", "plugin state files", "read YAML frontmatter", "per-project plugin settings", or wants to make plugin behavior configurable. Documents the .claude/plugin-name.local.md pattern for storing plugin-specific configuration with YAML frontmatter and markdown content.
This skill provides comprehensive guidance for using OpenCode, the open-source AI coding agent. Use this skill when working with OpenCode CLI commands, keyboard shortcuts, agents (build/plan), slash commands, tools, skills, MCP servers, or configuration. Automatically triggered when OpenCode-specific questions or tasks are detected.
Interact with the Langfuse API. Use when user wants to query traces, fetch prompts, create datasets, manage scores, or do anything else via the Langfuse REST API.
LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications
AI가 생성한 한국어 텍스트의 특징적인 패턴을 감지하고 자연스러운 인간의 글쓰기로 변환합니다. 과학적 언어학 연구(KatFishNet 논문, 94.88% AUC 정확도)에 기반합니다. 쉼표 과다, 띄어쓰기 경직성, 품사 다양성, AI 어휘 과용, 대명사 과다, 복수형 과다, 구조적 단조로움 등 24가지 패턴을 분석합니다. ChatGPT/Claude/Gemini가 생성한 한국어 텍스트를 자연스럽게 만들거나 LLM 출력에서 AI 흔적을 제거할 때 사용하세요.
Curated collection of high-quality prompts for various use cases. Includes role-based prompts, task-specific templates, and prompt refinement techniques. Use when user needs prompt templates, role-play prompts, or ready-to-use prompt examples for coding, writing, analysis, or creative tasks.
Caching strategies for LLM prompts including Anthropic prompt caching, response caching, and CAG (Cache Augmented Generation) Use when: prompt caching, cache prompt, response cache, cag, cache augmented.
Design effective Claude Code skills with optimal descriptions, progressive disclosure, and error prevention patterns. Covers freedom levels, token efficiency, and quality standards. Use when: creating new skills, improving skill descriptions, optimizing token usage, structuring skill content, or debugging why skills aren't being discovered.
Design and build custom Claude Code agents with effective descriptions, tool access patterns, and self-documenting prompts. Covers Task tool delegation, model selection, memory limits, and declarative instruction design. Use when: creating custom agents, designing agent descriptions for auto-delegation, troubleshooting agent memory issues, or building agent pipelines.
Pattern for progressively refining context retrieval to solve the subagent context problem