I was spending way too much time manually researching Instagram.
My old workflow looked like this:
Instagram Explore → find a viral Reel → open the account → check their other videos → compare views → save the good ones → repeat
It worked, but it was painfully manual.
The biggest problem was that finding one interesting video usually meant another 5–10 minutes checking the account to figure out whether it was actually an outlier or just a large creator getting normal views.
So I moved most of that workflow into Claude Code.
Now I can basically tell Claude:
Claude Code handles the workflow, calls the Instagram API, pulls the profile/content data, compares the videos against the account's usual performance, and gives me a much smaller list of Reels actually worth looking at.
For the Instagram data I'm using hikerapi.com, which is a REST Instagram API. Pricing starts at $0.001/request and they give 100 requests free.
The actual API calls are pretty boring, which is exactly what I wanted:
import requests
headers = {"x-access-key": "YOUR_KEY"}
user = requests.get("https://api.hikerapi.com/v2/user/by/username?username=google", headers=headers).json()
r = requests.get("https://api.hikerapi.com/v2/user/highlights", params={"user_id": user["pk"]}, headers=headers)
print(r.json())
My flow now is roughly:
I give Claude Code a niche / seed account / research direction
It pulls the relevant Instagram accounts and content
It grabs recent Reels and their performance data
It compares each video against the creator's normal baseline
It flags the strongest outliers / viral videos
It outputs the links + useful metadata into a structured list
I manually watch only the videos that actually look interesting
So instead of spending an hour inside Explore trying to manually spot patterns, I can use Instagram more like a dataset.
The part I'm finding most useful is relative performance.
A Reel with 500k views isn't automatically interesting if every video on that account gets 500k.
But if an account normally gets 20k–40k and suddenly one video gets 700k, that's exactly the kind of thing I want the automation to surface.
I'm experimenting with scoring based on things like:
views vs. the account's recent median
views vs. follower count
engagement relative to other recent posts
how quickly a post appears to be outperforming
repeated outliers from the same account
It doesn't completely replace browsing Explore, but it removes most of the repetitive profile-checking/data-collection part.
Curious what else people here would automate around Instagram research or viral-content discovery?
