Templates / Weekly competitor content digest with Gemini & OpenAI, Google Sheets, and Firecrawl

Weekly competitor content digest with Gemini & OpenAI, Google Sheets, and Firecrawl

Ready for 3.0

by Michael Yang · 1,024 views · created 2025-07-29 · Market Research, AI Summarization

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 16 nodes and runs on a schedule (cron 0 0 5 * * SUN). Along the way it connects Google Gemini Chat Model, Google Sheets, OpenAI Chat Model and Gmail. It also calls api.firecrawl.dev over HTTP.

How it runs

Trigger: On a schedule (cron 0 0 5 * * SUN).

  1. Input Links (Google Sheets): uses Google Sheets
  2. Firecrawl_Links (HTTP Request): calls api.firecrawl.dev (POST)
  3. Agent: Identify URLs to Crawl (AI Agent): runs an AI agent, with model: OpenAI o4-mini; 1 tool (Read_Url_Summary_Tool); output parser: Structured Output Parser
  4. Split Out: splits a list into separate items
  5. Firecrawl_Markdown (HTTP Request): calls api.firecrawl.dev (POST)
  6. Agent: Summarize Each URL (AI Agent): runs an AI agent, with model: Gemini 2.5 Flash: Temp; output parser: Structured Output Parser
  7. Append row in sheet (Google Sheets): append
  8. Get row(s) in sheet (Google Sheets): uses Google Sheets
  9. Code: runs custom JavaScript code
  10. Send a message (Gmail): uses Gmail

Services it uses

Google Gemini Chat ModelGoogle SheetsOpenAI Chat ModelGmail

HTTP calls to: api.firecrawl.dev

Uses Firecrawl. New users get 10% off with our link.

Before you upgrade to n8n 3.0

Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.

Nodes used (11)

From the author

Who is this template for? This workflow is perfect for competitive‑intel analysts, product managers, content marketers, and anyone who tracks multiple company blogs or news sources. If you need a weekly snapshot of fresh, on‑topic articles—without wading…

Excerpt from Michael Yang's description on n8n.io.

View the original on n8n.io → Check your own copy

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