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Research high-performing Instagram content (posts and reels) from tracked accounts using Apify's Instagram Scraper. Identifies outlier content, analyzes top 5 videos with AI, and generates reports with actionable hook formulas. Use when asked to: - Find trending Instagram content in a niche - Research what's performing on Instagram - Identify high-performing reel patterns - Analyze competitors' Instagram content - Generate content ideas from Instagram trends - Run Instagram research - Find viral reels - Analyze hooks and content structure Triggers: "instagram research", "ig research", "find trending reels", "analyze instagram accounts", "what's working on instagram", "content research instagram", "reel analysis", "instagram trends"
npx skill4agent add bradautomates/head-of-content instagram-researchAPIFY_TOKEN.envGEMINI_API_KEY.envapify-clientgoogle-genai.claude/context/instagram-accounts.mdpython3 -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"RUN_FOLDER="instagram-research/$(date +%Y-%m-%d_%H%M%S)" && mkdir -p "$RUN_FOLDER" && echo "$RUN_FOLDER"python3 .claude/skills/instagram-research/scripts/fetch_instagram.py \
--type reels \
--days 30 \
--limit 50 \
--output {RUN_FOLDER}/raw.json--type--days--limitpython3 .claude/skills/instagram-research/scripts/analyze_posts.py \
--input {RUN_FOLDER}/raw.json \
--output {RUN_FOLDER}/outliers.json \
--threshold 2.0total_postsoutlier_counttopicsaccountsoutlierspython3 .claude/skills/video-content-analyzer/scripts/analyze_videos.py \
--input {RUN_FOLDER}/outliers.json \
--output {RUN_FOLDER}/video-analysis.json \
--platform instagram \
--max-videos 5video-content-analyzer{RUN_FOLDER}/outliers.json{RUN_FOLDER}/video-analysis.json{RUN_FOLDER}/report.md# Instagram Research Report
Generated: {date}
## Top Performing Hooks
Ranked by engagement. Use these formulas for your content.
### Hook 1: {technique} - @{username}
- **Opening**: "{opening_line}"
- **Why it works**: {attention_grab}
- **Replicable Formula**: {replicable_formula}
- **Engagement**: {likes} likes, {comments} comments, {views} views
- [Watch Video]({url})
[Repeat for each analyzed video]
## Content Structure Patterns
| Video | Format | Pacing | Key Retention Techniques |
|-------|--------|--------|--------------------------|
| @username | {format} | {pacing} | {techniques} |
## CTA Strategies
| Video | CTA Type | CTA Text | Placement |
|-------|----------|----------|-----------|
| @username | {type} | "{cta_text}" | {placement} |
## All Outliers
| Rank | Username | Likes | Comments | Views | Engagement Rate |
|------|----------|-------|----------|-------|-----------------|
[List all outliers with metrics and links]
## Trending Topics
### Top Hashtags
[From outliers.json topics.hashtags]
### Top Keywords
[From outliers.json topics.keywords]
## Actionable Takeaways
[Synthesize patterns into 4-6 specific recommendations]
## Accounts Analyzed
[List accounts]RUN_FOLDER="instagram-research/$(date +%Y-%m-%d_%H%M%S)" && mkdir -p "$RUN_FOLDER" && \
python3 .claude/skills/instagram-research/scripts/fetch_instagram.py --type reels -o "$RUN_FOLDER/raw.json" && \
python3 .claude/skills/instagram-research/scripts/analyze_posts.py -i "$RUN_FOLDER/raw.json" -o "$RUN_FOLDER/outliers.json" && \
python3 .claude/skills/video-content-analyzer/scripts/analyze_videos.py -i "$RUN_FOLDER/outliers.json" -o "$RUN_FOLDER/video-analysis.json" -p instagramlikes + (3 × comments) + (0.1 × views)