analyze-performancelisted

# Analyze Content Performance Identify patterns in high-performing posts to inform future content strategy. ## Process 1. Run `./scripts/print-published.sh linkedin-post` to read all published LinkedIn posts 2. Extract posts that have engagement data (engagement.reactions, engagement.views, etc.) 3. Analyze patterns across high-performing vs low-performing posts ## Analysis Dimensions ### Hook Analysis - What hook styles correlate with higher engagement? - Personal anecdote vs company experience vs surprising data vs news hook? - First 210 characters (LinkedIn cutoff) - what patterns work? ### Content Characteristics - Word count vs engagement correlation - Use of concrete examples vs abstract concepts - Presence of frameworks or mental models - Use of lists/structure vs flowing narrative ### Topic Analysis - Which tags correlate with higher engagement? - Which themes resonate most? - Timing patterns (if publishedDate available) ### Structural Patterns - Opening style (question, statement, story) - Closing style (call-to-action, reflection, question) - Paragraph length and density ## Performance Tiers Categorize posts by reaction count: - **High performers**: 100+ reactions - **Medium performers**: 30-99 reactions - **Lower performers**: <30 reactions ## Output Format Provide: 1. **Summary statistics** - Total posts analyzed, average engagement by tier 2. **Top performers** - List highest-engagement posts with their key characteristics 3. **Pattern insights** - Wh