Workshop Export

Export learning workshops to standalone projects with all necessary artifacts for maximum AI-assisted learning

Workshop Export Skill

Purpose

Export any learning workshop to a standalone project with all necessary artifacts for maximum AI-assisted learning.

Artifacts Generated

Artifact	Purpose
`.cursorrules`	Project-level AI rules and context
`.cursor/rules/<lang>.md`	Technology-specific coding rules
`.cursor/knowledge/*.json`	Relevant knowledge files
`.cursor/WORKSHOP_CONTEXT.md`	AI assistant guidance for workshop phases
`README.md`	Workshop overview, exercises, objectives
`package.json` / `requirements.txt`	Dependencies
`src/exercises/`	Starter code for exercises
`.solutions/`	Hidden solutions (gitignored)
`.gitignore`	Clean repository patterns

Usage

Via Python Script

bash

# From factory root
python scripts/workshops/export_workshop.py <workshop_id> <target_directory>

# Examples
python scripts/workshops/export_workshop.py L1_ethereum_fundamentals {TARGET_DIR}
python scripts/workshops/export_workshop.py L7_langchain_fundamentals {TARGET_DIR}
python scripts/workshops/export_workshop.py L5_crewai_multiagent {TARGET_DIR}

Via Agent Request

When user asks to start a workshop:

•
Identify the workshop from available options:
- •Blockchain: L1 (Ethereum), L2 (Bitcoin), L4 (Solana)
- •AI: L3 (LangGraph), L5 (CrewAI), L6 (HuggingFace), L7 (LangChain), L8 (RAG), L16-L18
- •Web: L9 (React), L10 (Next.js), L11 (FastAPI)
- •Cloud: L12 (Kubernetes), L13 (Docker)
- •ML: L14 (PyTorch), L15 (Fine-tuning)
•
Ask for target directory if not specified

•

Run the export script:

bash

python scripts/workshops/export_workshop.py {workshop_id} {target_dir}

•
Guide user to open the new project in Cursor

bash

# From factory root
python scripts/workshops/export_workshop.py <workshop_id> <target_directory>

# Examples
python scripts/workshops/export_workshop.py L1_ethereum_fundamentals {TARGET_DIR}
python scripts/workshops/export_workshop.py L7_langchain_fundamentals {TARGET_DIR}
python scripts/workshops/export_workshop.py L5_crewai_multiagent {TARGET_DIR}

bash

python scripts/workshops/export_workshop.py {workshop_id} {target_dir}

Available Workshops

ID	Name	Category
L1_ethereum_fundamentals	Ethereum Smart Contracts	Blockchain
L2_bitcoin_lightning	Bitcoin & Lightning	Blockchain
L3_langgraph_workflows	LangGraph Workflows	AI
L4_solana_fundamentals	Solana Development	Blockchain
L5_crewai_multiagent	CrewAI Multi-Agent	AI
L6_huggingface_transformers	HuggingFace Transformers	AI
L7_langchain_fundamentals	LangChain Agents	AI
L8_rag_systems	RAG Systems	AI
L9_react_modern	Modern React	Web
L10_nextjs_fullstack	Next.js Fullstack	Web
L11_fastapi_production	FastAPI Production	Web
L12_kubernetes_production	Kubernetes	Cloud
L13_docker_containerization	Docker	Cloud
L14_pytorch_deeplearning	PyTorch Deep Learning	ML
L15_llm_finetuning	LLM Fine-Tuning	ML
L16_langsmith_observability	LangSmith Observability	AI
L17_anthropic_tool_agents	Anthropic Tool Agents	AI
L18_deep_research_agents	Deep Research Agents	AI

Post-Export Steps

After export, guide the user:

•Open the project in a new Cursor window
•
Install dependencies:
- •npm: npm install
- •pip: pip install -r requirements.txt
•Read README.md for workshop overview
•Follow the phases: Concept → Demo → Exercise → Challenge → Reflection

Customization

The export script uses stack configurations to customize output:

•Blockchain projects: Hardhat config, Solidity rules, contract templates
•Python AI projects: pytest config, type hints, async patterns
•Web projects: Framework-specific configs and patterns
•Cloud projects: YAML configs, deployment templates

Integration with Workshop Facilitator

The exported project is designed to work with the @workshop-facilitator agent:

code

@workshop-facilitator Guide me through the L1 Ethereum workshop

The facilitator uses:

•WORKSHOP_CONTEXT.md for phase-specific guidance
•Knowledge files for accurate information
•Exercise hints for progressive assistance

code

@workshop-facilitator Guide me through the L1 Ethereum workshop

Example Workflow

code

User: I want to learn LangChain

Agent: I'll set up the LangChain workshop for you.

1. Runs: python scripts/workshops/export_workshop.py L7_langchain_fundamentals {TARGET_DIR}
2. Project created with:
   - .cursorrules with LangChain context
   - .cursor/rules/python.md with Python best practices
   - Knowledge files for LangChain patterns
   - Exercise starter code
   - Comprehensive README

3. Guide user to open project and begin learning

code

User: I want to learn LangChain

Agent: I'll set up the LangChain workshop for you.

1. Runs: python scripts/workshops/export_workshop.py L7_langchain_fundamentals {TARGET_DIR}
2. Project created with:
   - .cursorrules with LangChain context
   - .cursor/rules/python.md with Python best practices
   - Knowledge files for LangChain patterns
   - Exercise starter code
   - Comprehensive README

3. Guide user to open project and begin learning

Troubleshooting

Issue	Solution
Workshop not found	Check workshop ID matches pattern in `patterns/workshops/`
Permission denied	Run with appropriate permissions or choose different target
Dependencies fail	Use `--legacy-peer-deps` for npm or update pip

Best Practices

•Validate workshop ID before export - confirm the workshop exists and matches user's learning goals to avoid wasted time
•Ensure target directory is clean or doesn't exist - prevent accidental overwrites by checking directory state first
•Include comprehensive README.md in exports - learners need clear guidance on objectives, phases, and how to use the workshop
•Structure exercises progressively - start with concepts, move to demos, then exercises, building complexity gradually
•Keep solutions hidden but accessible - use .solutions/ directory with .gitignore so learners can check answers without temptation
•Test exported projects before delivery - verify dependencies install correctly and starter code runs on clean environments

Part of the Cursor Agent Factory Learning System

Prerequisites

[!IMPORTANT] Requirements: