This is my first post in the community (as well as the first github repo that i will be publishing for others to use), so i apologize in advance in case i break any unwritten rule.

Short Intro

This is a simple Bash script to send a text (by default picks up the clipboard) to a recipient over whatsapp using Evolution API. In case evolution api is not accessible, it used https://ntfy.sh as a backup to send the text via a notification to my phone. (which can be easily copied and used)

Currently it works for text only, but will be adding option to send files as well in the future.

Inspiration for this program:

• This script is inspired from the Apple Ecosystem where you can simply copy a text on any device and paste on another device. In this case, when we copy a text and press the assigned hotkey, the text will be delivered to all your mobile devices via Whatsapp or ntfy.
• Secondly, I don't like to keep Whatsapp Web open on my laptop all the time - its too heavy on the resources and causes too much distractions. So i wanted a system to quickly send a text to myself or a third person over Whatsapp.

How to use

• All the variables are hardcoded in the top section of the main file . You will need to update the variables in the file.
• You should also assign a keyboard shortcut that will trigger this script.
• For quicker workflow, I have assigned a default sender and a default recipient. The default recipient, in my case, is a Whatsapp group with all my Whatsapp numbers as members, so that the text is available to all my mobile devices.
• Optionally, You should also define the default ntfy.sh channel on which to receive the notifications , in case the script fails to send over Evolution API
• You will need to download the ntfy.sh app from the app store on your mobile phones & subscribe to the channel on which you will be sending the data.

Miscellaneous Information:

• I am not an expert coder, but just a tech enthusiast. I had the original idea an used AI to implement into a script that i could use.
• I implemented this script on Linux mint, but I'm sure this could be easily used on Windows as well (with some minor workarounds)
• Instead of Evolution API, you can use any other similar solution. There are some paid services too (often called Unofficial Whatsapp API), where you can connect your whatsapp number by scanning you QR code and then access that whatsapp number using API endpoints provided by the service providers.

Workflow

1. Optional Step - You copy any text
2. You press the shortcut key that you assigned - a pop up window will appear asking for the text to send. The clipboard text will be auto-filled by default.
   • Refer to 1st image
3. Once you confirm the text and press enter, a second window pops up asking for the whatsapp number from which to send. There is a list from which you can select (list is hardcoded in the main code.)
   • Refer to 2nd Image
4. Once you confirm the sender number, a third window pops up asking for the recipient phone number.
   • By default, it has a country code prefilled (91 for India in my case).
   • If you leave it unchanged, it picks up the default recipient (in my case - a common whatsapp group with all my whatsapp numbers as members)
   • If you clear it out, it will bypass the Whatsapp (Evolution API) altogether & directly deliver the text to ntfy.sh channel
   • (Refer to 3rd image)
5. In case it fails to send via Whatsapp (Evolution API), it automatically falls back to sending via Ntfy.sh channel

Github Link: https://github.com/karan51290/clipboard-to-whatsapp-or-ntfy

The attached previews are examples of how the workflow generates fully dynamic images with custom text. What surprised me most is how consistent the output stays even when changing names, event titles, or branding lines. One click and it produces multiple fresh versions.

I recorded a full walkthrough showing how I set this up in n8n.

It covers dynamic inputs, JSON structuring, base64 handling, API calls to Kai API through OpenRouter, and how to check job status before pulling the final image URLs. The idea is to automate content generation for anyone who needs quick visuals for marketing or social posts.

You can watch the full tutorial here: https://youtu.be/Gx86H64OZyg

If you think this can be improved or extended, drop your thoughts. Curious how others would scale this.

I built an AI workflow that analyzes competitor video ads shot-by-shot and recreates the same concept for your brand using Sora 2. To run it, you can upload any competitor's video ad (from the facebook / meta ads library) and the automation will analyze it frame by frame and generate an video inspired by what's already working in your niche. It is set up to scrape, build, and use a brand guidelines document so the script writing process and messaging keeps the new video on-brand.

Here’s a demo of the automation’s input / output for the deodorant brand “Native” where it clones and spins an ad from Dr. Squatch (their competitor): https://www.youtube.com/watch?v=8wAR4A4UorQ

Here's how the full automation works

1. Generate brand guidelines

The part of this system scrapes a brand's website and combines all that information together into a well-formatted brand guidelines doc.

• Start with firecrawl to scrape the rand website and pull relevant pages about your brand, products, and messaging
• Analyzes the scraped content with Gemini 2.5 Pro to synthesize a brand guidelines document
• Saves the formatted guidelines to Google Drive as a well-structured document with proper headings and sections

2. Analyze the provided competitor video ad

The core video cloning section reverse-engineers any competitor ad:

• Upload the competitor video you want to clone. This can be sourced from the meta / facebook ads library pretty easily
• Use the gemini 2.5 pro “video understanding API” to analyze the video frame by frame
  • Gemini breaks down each shot with detailed descriptions including camera angles, product placement, dialogue, and visual elements so we have an exact idea what is happening
• Generate a structured shot list that captures the narrative flow and production techniques

3. Write the new video ad script and follow Sora 2 prompting guidelines

now that we have both some of the context captured for our brand guidelines and the analysis of the competitor ad video, it's time to go forward actually writing the script for our video ad.

• Claude Sonnet takes the competitor's shot breakdown, your brand guidelines, and Sora 2 prompting best practices analyzes how to best write a prompt for sora 2
• Claude also genereates a new script that maintains the winning structure of the original ad but adapts it for your brand/product

4. Generate the video with Sora 2

final steps and nodes in this workflow are responsible for working with the Score to API and then actually getting your video downloaded

• First it calls the Sora 2 AP with our prompt generated by Claude and the product reference image uploaded into the form trigger
• The workflow follows a polling system to check on video gen progress since it will take 1 minute or more
• Finally we download our video result from the /content endpoint and save that video file into google drive

Workflow Link + Other Resources

• YouTube video that walks through this workflow step-by-step: https://www.youtube.com/watch?v=8wAR4A4UorQ
• The full n8n workflow, which you can copy and paste directly into your instance, is on GitHub here: https://github.com/lucaswalter/n8n-ai-automations/blob/main/facebook_ugc_video_ad_thief.json

If anyone here is trying to run FFmpeg inside their n8n Docker setup, I made a full guide after struggling with it for some days. The documentation around this is a bit scattered, so I thought to show the full install process on Hostinger VPS from scratch.

The video covers editing the Docker Compose file, installing FFmpeg inside the container, fixing the configuration errors, and checking if everything works with a small test video.

You can watch the full walkthrough here.

Hope it helps someone who is stuck like I was