X Algorithm Skills for AI Coding Agents

AI-powered skills that help you understand and leverage the X (Twitter) recommendation algorithm. Add these to your coding agent (Claude Code, Cursor, etc.) to analyze posts, understand ranking, and optimize your X presence.

What You Can Do

Ask your AI assistant questions like:

• "Why did my post get low engagement?"
• "What engagement signals does X track?"
• "How does the X algorithm rank posts?"
• "Why was my post filtered from the feed?"
• "Analyze this post for X algorithm optimization"

Skills Included

| Skill | Command | Use Case | | -------------- | -------------------- | --------------------------------------------- | | Engagement | /x-algo-engagement | Understand the 18 engagement signals X tracks | | Scoring | /x-algo-scoring | Learn how posts are scored and weighted | | Filters | /x-algo-filters | Know why posts get filtered out | | Pipeline | /x-algo-pipeline | Full overview of the recommendation system | | ML Model | /x-algo-ml | Deep dive into the Phoenix transformer model |

Installation

Claude Code

Copy skills to your project or global skills directory:

# Project-scoped (recommended)
cp -r x-algo-* /path/to/your/project/.claude/skills/

# Or global
cp -r x-algo-* ~/.claude/skills/

Cursor / Other Agents

Add the skill files to your agent's context or skills directory. Each skill is a standalone SKILL.md file with YAML frontmatter.

Example Interactions

Analyze a Post

You: Analyze this post for X algorithm optimization:
"Just shipped a new feature! Check it out at [link]"

AI: Based on the X algorithm scoring system:
- Low predicted engagement signals (no question, no visual)
- Link posts typically get lower reach due to X preferring native content
- Suggestions: Add an image, ask a question, remove external link...

Understand Filtering

You: Why might my post not appear in followers' feeds?

AI: The X algorithm has 12 filters. Your post could be filtered by:
- AgeFilter: Post is too old (>24-48h typically)
- DedupConversationFilter: Another post in the thread scored higher
- VFFilter: Safety/spam detection triggered
- ...

Learn the Algorithm

You: How does X decide which posts to show me?

AI: X uses an 8-stage pipeline:
1. Query Hydration - Load your preferences
2. Sources - Thunder (following) + Phoenix (For You)
3. Candidate Hydration - Fetch post data
4. Pre-Score Filtering - Remove ineligible posts
5. Scoring - ML predictions → weighted scores
6. Selection - Top K by score
7. Post-Score Filtering - Dedup, seen posts
8. Side Effects - Logging

Key Insights from the Algorithm

Engagement Weights

The algorithm predicts probability of 18 actions and combines them:

Positive signals (increase score):

• Favorite (like)
• Reply
• Retweet
• Quote tweet
• Follow author
• Share (DM, copy link)
• Video quality view
• Dwell time

Negative signals (decrease score):

• Not interested
• Block author
• Mute author
• Report

What Gets Filtered

Posts are removed if they:

• Are too old (Snowflake ID age check)
• Were already seen (Bloom filter)
• Are from blocked/muted accounts
• Contain muted keywords
• Fail safety checks
• Are duplicates or from same conversation

Source

These skills are based on the open-source X recommendation algorithm and internal documentation, adapted for practical use with AI coding agents.

Contributing

PRs welcome! Areas to improve:

• Add more example queries
• Update weights if X publishes changes
• Add skills for specific use cases (video optimization, thread strategy)

License

MIT