rag-implementation
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Discover reusable agent skills, browse implementation details, and find the right skill for your workflow.
210 skills found
Build production-grade RAG systems using vector databases, semantic search, and LangGraph to ground LLMs in external knowledge.
Search, discover, and refine AI prompts using the prompts.chat library. Access thousands of community-curated prompts for ChatGPT, Claude, and other AI models.
Execute implementation plans in separate sessions with review checkpoints, ensuring task-by-task verification and robust code quality.
Generates a random lucky number between 0 and 9999 for games, decision-making, or entertainment.
Generate AGENTS.md and AI configuration files (Cursor, Claude, Gemini, Copilot) for your project to streamline your vibe-coding workflow and maintain context across sessions.
Research technical documentation and automatically generate ready-to-use software agent skills in markdown format.
Epsimo AI platform SDK and CLI for building agents with persistent state, Virtual Database, streaming conversations, and a React UI kit.
Unified API for LLM function calling and tool use across OpenAI, Anthropic, Google, and Ollama with standardized schema definitions and execution patterns.
Analyzes OpenAPI specifications to generate TypeScript interfaces, API service patterns, and implementation guidance for backend-integrated frontend development.
Language-agnostic backend architectural patterns covering API design, authentication, security protocols, and database modeling.
Unified AI gateway for building full-stack apps and automating tasks. Access 100+ AI models for content generation, web scraping, app deployment, and Stripe payments with a single API key.
Expert guidance for designing and implementing high-quality tool schemas and descriptions for Julia's agent systems, ensuring reliable tool execution and reducing model hallucinations.