Content Performance Analysis

This breaks down Xiaohongshu post performance into three dimensions: engagement, growth, and viral metrics. You get formulas for engagement rate, save rate, and a "viral score" (views divided by followers, where >10 means you broke out beyond your audience). The workflow is straightforward: pull data from Creator Center or Qiangua, calculate KPIs, sort by performance, then extract patterns from your top 5 posts. What makes content succeed or tank, which formats convert, what timing works. It includes benchmarks (8-12% engagement is good, 3-5% save rate) and a content performance matrix to decide which formats deserve your attention. Honest take: this is pattern recognition work that most creators skip, but the structured approach here saves you from guessing why posts flop.

skills.sh installs: 338
GitHub stars: 539
last updated: Aug 21, 2026

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Install

$ npx -y skills add vivy-yi/xiaohongshu-skills --skill content-performance-analysis --agent claude-code

Installs into .claude/skills of the current project.

Files

Content Performance Analysis (内容效果分析)

Overview

Content performance analysis is the systematic evaluation of individual posts and overall content portfolio to identify success patterns, understand what resonates with the audience, and make data-driven decisions about content strategy.

When to Use

Use when:

Post performance is inconsistent or unpredictable
Need to understand why certain content went viral
Identifying patterns in top-performing content
Recognizing underperforming content that needs improvement
Comparing different content formats (carousel vs video vs single image)
Deciding which content types to focus on
Planning content optimization based on past performance

Do NOT use when:

Account has fewer than 5 published posts (insufficient data)
Looking for real-time performance during first hours (wait 3-7 days)
Analyzing paid advertising performance (use ad analytics tools)

Core Pattern

Before (guessing what works):

❌ "This post should do well, I worked hard on it"
❌ "I don't know why this post went viral, lucky I guess"
❌ "All my content is pretty similar, performance is random"

SKILL.md on GitHub