Tweet Composer

Score and optimize tweets based on X's real open-source ranking algorithm. Analyzes draft tweets against the actual ranking code — not generic tips. Use when...

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:

Category	Weight	What to check
Reply potential	25	Questions, opinions, CTAs that drive replies
Media	20	Native image/video attached (not link previews)
Shareability	15	Would someone DM this or copy the link?
Dwell time	15	Length that makes people stop scrolling
Content quality	10	Clear, original, not generic
Format	10	No links in body, no hashtags, good length
Negative signals	5	Risk of not_interested/mute/block

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"