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 - Resear

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: Workflow 1. Create Run Folder 2. Fetch Content Parameters: type : "posts", "reels", or "stories" days : Days back to search (default: 30) limit : Max items per account (default: 50) 3. Identify Outliers Output JSON contains: total posts : Number of posts analyzed outlier count : Number of outliers found topics : Top hashtags and keywords accounts : List of accounts analyzed outliers : Array of outlier posts with engagement metrics 4. Analyze Top Videos with AI Extracts from each video: Hook technique and replicable formula Content structure and sections Retention techniques CTA strategy See the video content analyzer skill for full output schema and hook/format types. 5. Generate Report Read {RUN FOLDER}/outliers.json and {RUN FOLDER}/video analysis.json , then generate {RUN FOLDER}/report.md . Report Structure: Focus on actionable insights. The "Top Performing Hooks" section with replicable formulas should be prominent. Quick Reference Full pipeline: Then read both JSON files and generate the report. Engagement Metrics Engagement Score : likes + (3 × comments) + (0.1 × views) Outlier Detection : Posts with engagement rate mean + (threshold × std dev) Engagement Rate : (score / followers) × 100

instagram-research