Automates Instagram content research by pulling posts and reels from tracked accounts via Apify, identifying statistical outliers based on engagement rates, then using AI to analyze the top 5 videos for hook formulas and content structure. You configure accounts in a markdown file, run three scripts (fetch, analyze, AI breakdown), and get a report with replicable hook patterns and trending topics. Useful when you need to reverse engineer what's actually working in a niche rather than guessing. Requires both Apify and Gemini API keys, so there's a cost consideration, but the outlier detection math (mean plus standard deviation threshold) and the focus on extractable formulas makes this more systematic than manually scrolling Instagram for inspiration.

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13
skills.sh installs
1.5K
GitHub stars
309
last updated
Aug 21, 2026

Install

$ npx -y skills add bradautomates/head-of-content --skill instagram-research --agent claude-code

Installs into .claude/skills of the current project.

Files

Instagram Research

Research high-performing Instagram posts and reels, identify outliers, and analyze top video content for hooks and structure.

Prerequisites

  • APIFY_TOKEN environment variable or in .env
  • GEMINI_API_KEY environment variable or in .env
  • apify-client and google-genai Python packages
  • Accounts configured in .claude/context/instagram-accounts.md

Verify setup:

python3 -c "
import os
try:
    from dotenv import load_dotenv
    load_dotenv()
except ImportError:
    pass
from apify_client import ApifyClient
from google import genai
assert os.environ.get('APIFY_TOKEN'), 'APIFY_TOKEN not set'
assert os.environ.get('GEMINI_API_KEY'), 'GEMINI_API_KEY not set'
" && echo "Prerequisites OK"

Workflow

1. Create Run Folder

RUN_FOLDER="instagram-research/$(date +%Y-%m-%d_%H%M%S)" && mkdir -p "$RUN_FOLDER" && echo "$RUN_FOLDER"

2. Fetch Content

python3 .claude/skills/instagram-research/scripts/fetch_instagram.py \
  --type reels \
  --days 30 \
  --limit 50 \
  --output {RUN_FOLDER}/raw.json

Sponsors

Details

Repository
github.com/bradautomates/head-of-content
Categories
Frontend Development, Data Science & ML
First seen
May 16, 2026

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