11 tagged jupyter, measured the same way as everything else here.
Instructions file GitHub Copilot
Instructions for datalayer/jupyter-mcp-server, covering jupyter mcp server, working effectively, environment setup, build and install (critical: network limitations) and standard installation (may fail with network issues).
Instructions file
Instructions for vega/vegafusion, covering claude.md, architecture, development setup, critical constraints and testing.
Instructions file CodexOpenCode
Instructions for jupyter-ai-contrib/nb-cli, covering agent guidelines, working with notebooks (.ipynb files), connect-mode integration tests: backend selection and remote mode and server baseurl.
Instructions file
Instructions for jupyter-ai-contrib/nb-cli, a project described as: A CLI-first interface for AI agents to work with notebooks.
Instructions file CodexOpenCode
Instructions for wiki3-ai/agent-client-kernel, covering repository guidelines, project structure, build & development, install dependencies (requires python >= 3.10) and install the kernel for jupyter.
Instructions file
Claude Code instructions for 0STG0T/kaggle-kernel-tools, covering kaggle kernel tools, architecture, mcp server and key details.
maxencebernardhub/ai-engineering-labs
Instructions file CodexOpenCode
Instructions for maxencebernardhub/ai-engineering-labs, covering agents.md, project overview, working rules, code style and python tools.
maxencebernardhub/ai-engineering-labs
Instructions file
Instructions for maxencebernardhub/ai-engineering-labs, a project described as: Hands-on AI engineering labs: OpenAI, Anthropic, Google, local models. From a first API call to an agent deployed live on AWS: RAG, LangChain, LangGraph & Deep Agents, multi-provider routing, offline inference, FastAPI, Docker, Lambda.
maxencebernardhub/ai-engineering-labs
Instructions file Gemini CLI
Instructions for maxencebernardhub/ai-engineering-labs, a project described as: Hands-on AI engineering labs: OpenAI, Anthropic, Google, local models. From a first API call to an agent deployed live on AWS: RAG, LangChain, LangGraph & Deep Agents, multi-provider routing, offline inference, FastAPI, Docker, Lambda.
Instructions file
Claude Code instructions for fbereilh/cellar, a project described as: AI-agent-first interactive notebook environment (Jupyter-compatible, SvelteKit, MCP agent interface).
dev-the-dev-while-deving/rolldeep-lab
Instructions file CodexOpenCode
AGENTS.md instructions for dev-the-dev-while-deving/rolldeep-lab, covering rolldeep — how the agent works this lab, files you edit, commands and workflow.