🐙 Guides, papers, lessons, notebooks and resources for prompt engineering, context engineering, RAG, and AI Agents.
By leveraging Python SDK / OpenAI API, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
Clone dair-ai/Prompt-Engineering-Guide from GitHub
Install dependencies with pip install -r requirements.txt (or uv sync)
Copy .env.example to .env and add your API keys
Run the skill server and connect your AI client via stdio or HTTP
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
Generative UI system that translates natural language prompts into live, interactive shadcn/ui components and exportable React code using schema-driven composition.
Starter AI AgentsThe AI Meme Generator Agent is a powerful browser automation tool that creates memes using AI agents. This app combines multi-LLM capabilities with automated browser interactions to generate memes based on text prompts through direct...
Starter AI AgentsAI-powered web scraping using ScrapeGraphAI - extract structured data from websites using natural language prompts. This agent runs locally with the open-source scrapegraphai library.
