x-algo-engagement

Analyze X engagement signals and PhoenixScores to predict post performance.

11|2|Updated Jan 20, 2026
One-click install
npx skills add https://github.com/CloudAI-X/x-algo-skills --skill x-algo-engagement
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: x-algo-engagement
Source: https://github.com/CloudAI-X/x-algo-skills/tree/main/x-algo-engagement
Command: npx skills add https://github.com/CloudAI-X/x-algo-skills --skill x-algo-engagement

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The X engagement skill provides a clear reference for understanding the 18 engagement action types tracked by the X algorithm and how the Phoenix model uses these signals to predict post visibility and performance.

Core Features & Use Cases

  • Understand Positive Engagement signals (Favorite, Reply, Retweet, Quote) and other categories, and how they contribute to scores.
  • Inspect the PhoenixScores struct fields and their mapping to action probabilities to diagnose ranking behavior.
  • Use as a cross-skill reference with /x-algo-scoring and /x-algo-ml to explain how probabilities translate into rankings and decisions.

Quick Start

List the 18 engagement signals and their PhoenixScores for a sample post to interpret predicted engagement.

Frequently Asked Questions about x-algo-engagement

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

FAQPage Schema
How does the X algorithm use engagement signals to rank posts?

The X algorithm ranks posts by tracking 18 engagement action types, applying specific weightings across positive, sharing, and negative categories to predict visibility. These signals feed the Phoenix scorer pipeline to calculate post reach.

What are the 18 engagement action types tracked by the X ranking system?

The 18 engagement action types include positive signals like Favorite, Reply, Retweet, and Quote, alongside sharing and negative signals. Each action carries specific weightings used by the Phoenix model to calculate overall post performance.

How do I diagnose why my X post lost reach using engagement signals?

Diagnose lost reach by inspecting the PhoenixScores struct fields and their mapping to action probabilities. Analyzing negative engagement signals alongside positive interactions reveals why the Phoenix scorer pipeline reduced your post visibility.

How do PhoenixScores predict post performance on X?

PhoenixScores predict post performance by mapping 18 engagement action types to action probabilities within a specific struct. These scores feed the Phoenix scorer pipeline to interpret ranking behavior and estimate overall visibility.

Can I evaluate content ideas using X engagement signals before posting?

Evaluate content ideas by referencing the 18 engagement action types and their PhoenixScores to interpret predicted engagement. Understanding positive signal weightings helps anticipate how the Phoenix model will score your planned content.

How do I cross-reference PhoenixScores with other X algorithm scoring skills?

Cross-reference PhoenixScores by using this skill alongside x-algo-scoring and x-algo-ml skills. Together they explain how engagement probabilities translate into final rankings and algorithmic decisions within the Phoenix scorer pipeline.