x-research_skill

Overview

This skill researches high-performing X/Twitter content from tracked accounts using Apify's Tweet Scraper V2 and downstream analytics. It identifies outlier tweets, trending topics, and repeatable content patterns to inform content strategy. The output includes outlier lists, topic summaries, engagement-pattern breakdowns, and an optional AI-driven video hook analysis.

How this skill works

The skill fetches tweets from configured accounts over a specified time window, then calculates an engagement score and detects outliers using statistical thresholds. It extracts top hashtags, mentions, keywords, and content-format patterns (media, thread, questions, lists). If outliers include videos and a video-analysis API key is available, it optionally analyzes openings, hooks, and repeatable formulas.

When to use it

• Find trending tweets or content in a niche
• Analyze what’s performing on X/Twitter for competitors
• Identify high-performing tweet patterns to replicate
• Generate content ideas from trending topics and hooks
• Run recurring X/Twitter research to inform posting strategy

Best practices

• Ensure APIFY_TOKEN is set and accounts list is up to date before running
• Use a 30-day window and at least 50 tweets per query to stabilize statistics
• Adjust outlier threshold (e.g., 2.0) to control sensitivity of results
• Combine content-pattern outputs with audience data before changing strategy
• Run video analysis only when outliers include video posts and Gemini API key is available

Example use cases

• Competitor analysis: identify which tweets drive amplification and why
• Content ideation: derive replicable hooks and thread formulas from top outliers
• Trend spotting: surface rising hashtags and keywords across tracked accounts
• Format testing: discover whether short text, lists, media, or threads perform best
• Quarterly audit: generate a report of top-performing posts and actionable takeaways