43-node n8n workflow using Anthropic, Qdrant, Brave Search, and Google Sheets style libraries for RAG-powered scriptwriting.
A focused 43-node workflow that combines document-ingestion RAG with AI scriptwriting and a distinctive approach to consistent voice: Google Sheets as style libraries. Rather than hoping an AI model maintains a consistent tone across scripts, this workflow feeds the agent structured libraries of hooks, linking phrases, and narrative progression patterns pulled directly from spreadsheets. The result is an AI scriptwriter that writes like a specific creator, not a generic chatbot.
| Nodes | Category | Complexity | Key Integrations |
|---|---|---|---|
| 43 | Content Creation & AI | Intermediate | Google Drive, Qdrant, Cohere, Anthropic, OpenAI, Brave Search, Redis Memory |
45-60 minutes including Qdrant setup, Redis configuration, style library spreadsheet creation, reference document ingestion, and credential wiring.
The workflow operates in two modes. The first mode is document ingestion: reference documents (PDFs, articles, notes) are pulled from Google Drive, processed through Mistral OCR via HTTP Request for text extraction, chunked, embedded using Cohere, and stored in the Qdrant vector store. This builds the knowledge base that the AI agent draws from when writing scripts. You run this mode whenever you have new reference material to add.
The second mode is script generation. You provide a topic, and the AI Agent -- powered by Anthropic Claude -- retrieves relevant context from Qdrant, searches the web via Brave Search for current information, and then writes the script. What makes this workflow distinctive is how it handles writing style. Three Google Sheets serve as AI "style libraries": a Hook Library containing proven opening patterns, a Linking Phrases sheet with transition language that matches the creator's voice, and a Narrative Progression sheet defining how the creator typically structures arguments and stories.
The AI Agent accesses these sheets as tools during generation. Rather than relying on vague prompt instructions like "write in a conversational tone," the agent has concrete examples of the creator's actual language patterns. Redis Memory maintains context across the writing session, allowing the agent to reference earlier sections of the script as it writes later ones. The finished script is output to Google Sheets with section markers and timing estimates.
Triggers
AI & Language Models
Data & Integrations
Tip: Key Techniques Used in This Workflow
- Google Sheets as AI tools -- Providing Google Sheets as callable tools to an AI Agent is a powerful pattern for injecting structured, editable knowledge into AI workflows. The creator can update their style libraries at any time, immediately changing how the AI writes.
- Document ingestion pipeline -- The Google Drive to Mistral OCR to Cohere to Qdrant pipeline is a reusable pattern for building RAG-ready knowledge bases from document collections.
- Brave Search integration -- Adding real-time web search to a RAG-equipped agent gives it both deep (vector store) and fresh (web) context.
- Redis session memory -- Maintaining context across a multi-section writing task ensures coherent long-form output where later sections build on earlier ones.
- Dual-mode workflows -- Separating ingestion from generation within a single workflow file keeps related logic together while allowing independent execution of each mode.
The workflow.json file in this folder can be imported directly into your n8n instance via Settings > Import Workflow.
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