Tweet Composer

Score and optimize tweets using rules derived from X's open-source ranking algorithm.

How It Works

X's "For You" feed is ranked by a Grok-based transformer (Phoenix) that predicts 19 engagement

actions for every candidate tweet. The final score is a weighted sum of these predictions.

This skill encodes the structural rules from that pipeline into a scoring system.

For the full algorithm breakdown, read references/algorithm-rules.md.

Scoring a Draft Tweet

When a user asks to score or optimize a tweet draft:

1. Read references/algorithm-rules.md for the complete rules engine
2. Analyze the draft against all rules
3. Output the score card in this format:

🐦 Tweet Composer — Score: XX/100

[Category scores with ✅ ⚠️ ❌ indicators]

📊 Predicted Action Boost:
├─ P(reply): [assessment]
├─ P(favorite): [assessment]  
├─ P(share): [assessment]
├─ P(dwell): [assessment]
└─ P(not_interested): [assessment]

💡 Suggestions:
→ [actionable improvements]

✏️ Optimized version:
"[rewritten tweet]"

Scoring Rubric (Quick Reference)

Score 0-100 based on weighted categories:

Thread Optimization

When composing threads:

• First tweet = strongest hook (DedupConversationFilter keeps only the best per conversation)
• 3-6 tweets max (short threads > mega-threads)
• Each tweet self-contained (many see only the first)
• Media on tweet 1 or 2 for photo_expand boost
• CTA in last tweet

Quick Rules (No Reference File Needed)

• Links: Always in reply, never in body (learned penalty from lower engagement)
• Hashtags: Zero. The model learns they reduce engagement
• Length: 100-200 chars sweet spot for single tweets
• Media: Native image/video = separate P(photo_expand) and P(video_quality_view) predictions
• Video: Must exceed minimum duration threshold for VQV weight to apply
• Timing: Post when your audience is active — engagement velocity in first 30 min is critical
• Frequency: AuthorDiversityScorer penalizes exponentially: 2nd post ~55% score, 3rd ~33%. Max 3-4 strong tweets/day
• Quote tweets: P(quote) has dedicated weight — QTs with added value outperform plain retweets
• Engagement bait: Questions/polls drive P(reply). "What would you add?" > "Like if you agree"