🎬 Generate research-backed blog articles from news with OpenAI, Tavily and Google Docs

⚑ 48 views · 🎬 Content Creation & Video

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Description

How it works

This workflow automatically generates full-length, research-backed blog articles from online news sources. It collects headlines from selected URLs, extracts topic ideas, creates an outline, writes well-structured sections with citations, compiles the article, and finally exports the completed piece to Google Docs. The workflow supports SEO outputs such as title, slug, and meta description, making the article ready for publication.


Key Features


Step-by-Step Workflow

1️⃣ News Extraction

The workflow begins by fetching content from the configured URLs using the Extract node. The scraped page content is processed to pull out headlines and article references.

2️⃣ Topic Identification

The AI Agent analyzes the extracted headlines and converts them into meaningful blog topic suggestions.

3️⃣ Topic Looping

Each topic is processed individually using a loop, ensuring one full article is generated per topic.

4️⃣ Table of Contents Generation

The Table of Contents Agent creates a structured outline for the article:

5️⃣ Section Writing

For each section in the outline:

6️⃣ Article Assembly

All generated sections are merged and refined into a complete article:

7️⃣ SEO Enhancements

The workflow automatically generates:

8️⃣ Google Docs Export

The workflow:


API & Services Required

(Optional) You may add additional sources, categories, or CMS publishing integrations.

πŸ”— Nodes Used

Google Docs, AI Agent, OpenAI Chat Model, Call n8n Workflow Tool, OpenAI

πŸ“₯ Import

Download workflow.json and import into n8n: Workflow menu β†’ Import from File

πŸ“– Importing guide Β· πŸ”‘ Credential setup