Multiple things to think about here:

1. For summarizing, in my experience GPT-3 still has some ways to go. It gets it right a lot of the times, but when it misses, it misses bad.

2. Assuming that after scraping we feed all the scrapped data as a prompt from which GPT-3 generates bullet points, that will be a very big prompt. Since prompts are also counted as tokens, it might end up costing 10cents minimum to generate one summary.

3. I think the core USP from the process the OP has detailed is in steps 1,2 and 3. Step 4 is a good hook to get people to try this out, but have to test it properly and check the costs also.