u/Ok_Steak_4182

Been meaning to solve my own content problem, so I built this in n8n over the weekend. Sharing the setup in case it's useful to anyone.

What it does: every Monday it pulls the most-viewed YouTube videos in my niche, has an AI model break down why each one worked (hook type, emotional trigger, format), then generates 7 original content ideas — each with a hook line, format, structure, and caption starter — and drops them as clean rows into a Google Sheet. Also pings me on Telegram when it's done.

The pipeline:

Schedule Trigger (weekly)

YouTube Data API → most-viewed videos in-niche (free, official API)

Code node → rank + prep the top 10

OpenAI (gpt-4o-mini) → analyze the viral patterns

OpenAI → generate 7 structured ideas as JSON

Code node → split JSON into one row per idea

Google Sheets (append) + Telegram (notify)

Stuff I learned the hard way:

Started with Reddit as the source but n8n Cloud's shared IPs get 403'd on anonymous requests — switched to the YouTube Data API and it's honestly better data (real view counts = a cleaner viral signal).

Ask the AI for JSON, not a markdown table — a table dumps into one ugly cell; JSON split into rows gives you clean columns.

gpt-4o-mini is more than enough for this and keeps the cost basically nothing.

Runs completely hands-off now. Happy to share more detail on any node if anyone wants to build their own.

Wanted to share a workflow I built for cleaning up messy PDFs (scanned notes, rough drafts, unformatted text dumps) sent via Telegram.

How it works:

1. Send a PDF to my Telegram bot

2. n8n extracts the raw text from the PDF

3. A "Cleaner Agent" (GPT-4o-mini) strips out OCR noise, fixes broken sentences, normalizes spacing

4. A "Structurer Agent" re-organizes the cleaned text into logical sections using a content schema parser

5. A "Summary Agent" generates a short summary alongside the full cleaned doc

6. Everything gets built into a properly formatted Google Doc (headings, bullet points, etc. — not just a wall of text)

7. Exported as PDF, then both the cleaned PDF and a summary message are sent back to me on Telegram

Stack: n8n + OpenAI (gpt-4o-mini) + Google Docs API + Telegram Bot API

Biggest technical hurdle: pdf-lib doesn't work on n8n Cloud, so I had to route through Google Docs batchUpdate → Drive export → PDF as a workaround instead of manipulating PDFs directly.

Happy to answer questions about the node setup or the agent prompts if anyone's building something similar. Also open to feedback if anyone sees ways to simplify the chain.

Wanted to share a workflow I put together for handling inbound leads automatically.

The problem: most small businesses lose deals simply because they reply too slowly, and someone has to manually sort "serious buyer" from "just browsing."

What this does, start to finish, with zero manual work:

Captures the lead through a webhook (works with any form)

Scores it with AI — GPT evaluates lead quality and returns a structured score

Logs everything to a Google Sheet for tracking

Routes by score — hot leads take a priority path, everyone else gets the standard flow

Sends a personalized auto-reply — hot leads get one message, standard leads get another

Pings Discord with a real-time alert for hot leads

The AI scoring + branching is what makes it smarter than a basic autoresponder — you're not blasting the same generic reply to everyone.

Happy to answer questions if anyone wants to build something similar.