Block 1 - Start Curriculum Planning
- Type / Role
- n8n-nodes-base.manualTrigger - manualTrigger
- Config choices
- Version 1
How It Works This workflow automates end to end curriculum planning using a multi agent AI architecture in n8n. Designed for educators, instructional designers, and academic institutions, it elimin...
n8n-nodes-base.manualtrigger, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, @n8n/n8n-nodes-langchain.agenttool, @n8n/n8n-nodes-langchain.toolserpapi, n8n-nodes-base.perplexitytool, @n8n/n8n-nodes-langchain.toolwikipedia
This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Cheng Siong Chin.
Original n8n.io sourceThis workflow automates end-to-end curriculum planning using a multi-agent AI architecture in n8n. Designed for educators, instructional designers, and academic institutions, it eliminates the manual effort of researching, structuring, and assessing curriculum content. A Curriculum Supervisor Agent orchestrates three specialised sub-agents: a Research Agent (using Google Search, Perplexity, and Wikipedia), a Content Creation Agent (using GPT for drafting), and an Assessment Agent (using a calculator and code tools). Planning memory persists context across agent interactions. Once all agents complete their tasks, the Prepare Curriculum Data node formats the output, which is then stored in Google Sheets. This pipeline ensures coherent, research-backed, assessment-ready curriculum plans are generated and stored automatically with minimal human intervention.
This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.
Showing the first 24 of 26 workflow blocks. Download the JSON for the full node graph.
| Workflow | Generate research-backed curriculum plans with GPT-4o, Perplexity and Google Sheets |
|---|---|
| Complexity | advanced |
| Nodes | 26 |
| Categories | Document Extraction, AI Chatbot |
| Author | Cheng Siong Chin |
| Published | 11 Mar 2026 |
Use the JSON export at /data/workflows/13995/13995.json as the source template for this automation.
Open n8n, import the downloaded JSON, and review each node before activating the workflow.
Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.
Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.
Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.
How It Works This workflow automates end to end curriculum planning using a multi agent AI architecture in n8n. Designed for educators, instructional designers, and academic institutions, it elimin...
Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.
Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Document Extraction, AI Chatbot use case.