Does it require access to my Twitter account?

No, this skill operates as a consultant within Claude Code. It analyzes the text and strategy of your drafts based on the open-source algorithm documentation rather than accessing live account data.

Can this skill help my tweets go viral?

While virality depends on many factors, this skill significantly increases your chances by aligning your content structure with the specific community 'clusters' and engagement metrics the algorithm prioritizes.

What algorithmic signals does this skill focus on?

It focuses on both explicit signals (likes, replies, retweets) and implicit signals (time spent, profile visits) while helping you avoid negative signals like blocks or reports.

How does the Twitter Algorithm Optimizer work?

It analyzes your tweet drafts against Twitter's documented ranking models like Real-graph and SimClusters to suggest edits that trigger high-value engagement signals like replies and retweets.

Twitter Algorithm Optimizer

Name: Twitter Algorithm Optimizer
Author: EricGrill

byEricGrill

•

ソーシャルメディア管理

Optimizes tweets for maximum reach and engagement using insights from Twitter's open-source recommendation algorithm.

The Twitter Algorithm Optimizer is a specialized Claude Code skill designed to boost social media visibility by aligning content with Twitter's core recommendation systems. It analyzes tweet drafts against key ranking models like Real-graph for follower interaction and SimClusters for community resonance, providing data-driven rewrites that maximize high-weight signals such as replies, retweets, and bookmarks. Whether you are launching a product or building a personal brand, this skill helps you understand the technical 'why' behind content performance while providing actionable strategies to build topical authority and mitigate negative algorithmic signals.

主な機能

01Identifies and prevents negative signals that trigger algorithmic penalties

0211 GitHub stars

03Optimizes for high-weight signals including replies, retweets, and bookmarks

04Analyzes tweet drafts against Twitter's open-source ranking models

05Provides detailed explanations for rewrites based on Real-graph mechanics

06Applies SimClusters and TwHIN principles for community-specific reach

ユースケース

01Debugging underperforming content threads to improve algorithmic ranking

02Refining a content strategy to build consistent topical authority and Tweepcred

03Optimizing product launch announcements for maximum community visibility

主な機能

01Identifies and prevents negative signals that trigger algorithmic penalties

0211 GitHub stars

03Optimizes for high-weight signals including replies, retweets, and bookmarks

04Analyzes tweet drafts against Twitter's open-source ranking models

05Provides detailed explanations for rewrites based on Real-graph mechanics

06Applies SimClusters and TwHIN principles for community-specific reach

ユースケース

01Debugging underperforming content threads to improve algorithmic ranking

02Refining a content strategy to build consistent topical authority and Tweepcred

03Optimizing product launch announcements for maximum community visibility