twitter-algorithm-optimizer

Name: twitter-algorithm-optimizer
Availability: InStock
Author: sangrokjung

Analyze and rewrite tweets using Twitter's Real-graph, SimClusters, and TwHIN ranking factors.

1|Updated Feb 7, 2026

Search Tags:#social media #algorithm #engagement #twitter #content optimization #reach

Ready to run

npx skills add https://github.com/sangrokjung/claude-code-config-public --skill twitter-algorithm-optimizer-sangrokjung

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: twitter-algorithm-optimizer
Source: https://github.com/sangrokjung/claude-code-config-public/tree/main/commands/twitter-algorithm-optimizer
Command: npx skills add https://github.com/sangrokjung/claude-code-config-public --skill twitter-algorithm-optimizer-sangrokjung

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps users optimize their tweets for maximum reach and engagement by analyzing them against Twitter's known recommendation algorithms, rewriting content to improve visibility.

Core Features & Use Cases

Algorithmic Analysis: Understand how your tweets align with Twitter's Real-graph, SimClusters, and TwHIN models.
Content Rewriting: Edit tweets to better resonate with specific communities and engagement signals.
Use Case: You've drafted a tweet but it's not getting much traction. Use this skill to rewrite it, focusing on clearer calls to action and community-specific language to increase its chances of being seen and interacted with.

Quick Start

Optimize the following tweet draft for maximum reach: "I think AI is changing the world."

Frequently Asked Questions about twitter-algorithm-optimizer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I optimize my tweets for the Twitter algorithm to increase reach?▼

To optimize tweets for the Twitter algorithm, this Skill analyzes your drafts against ranking factors like Real-graph, SimClusters, and TwHIN, then rewrites the content to maximize visibility and engagement signals.

How does the Twitter recommendation system rank tweets?▼

The Twitter recommendation system ranks tweets using models like Real-graph, SimClusters, and TwHIN to evaluate explicit and implicit engagement signals. This Skill aligns your content with these specific ranking factors to boost visibility.

Why does my tweet get low engagement and how can I fix it?▼

Low tweet engagement often stems from missing algorithmic signals or triggering negative indicators. This Skill rewrites your drafts to focus on clearer calls to action and community-specific language, improving interaction rates.

Can I rewrite an existing tweet draft to target specific Twitter communities?▼

Yes, you can rewrite tweet drafts to target specific communities. This Skill analyzes your text against SimClusters and TwHIN embeddings, adjusting the language to better resonate with targeted audience segments.

What is the best way to improve content visibility on social media using algorithm insights?▼

The best way to improve social media visibility is by leveraging open-source algorithm documentation. This Skill applies those documented ranking factors directly to your text, avoiding negative indicators while maximizing recommendation system scores.

Are there limitations to optimizing tweets for algorithmic engagement?▼

A limitation of algorithmic tweet optimization is that it relies on known recommendation system models like Real-graph and SimClusters. While it maximizes ranking signals, actual reach can still fluctuate based on real-time platform updates.