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publish-retro

Analyze YouTube analytics data to generate retrospective episode performance reports.

Updated Apr 26, 2026
Search Tags:#analytics#retrospective#performance review#video analysis#production improvement
One-click install
npx skills add https://github.com/fy538/project-parallax --skill publish-retro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: publish-retro
Source: https://github.com/fy538/project-parallax/tree/main/skills/publish-retro
Command: npx skills add https://github.com/fy538/project-parallax --skill publish-retro

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of analyzing YouTube episode performance, extracting key metrics, and generating comprehensive retrospective reports to inform production improvements.

Core Features & Use Cases

  • Analytics Extraction: Parses manual YouTube Studio screenshots or structured data like CSV/JSON to gather viewership metrics, retention, traffic sources, and comments.
  • Performance Analysis: Compares observed metrics against predictive artifacts and benchmark standards, identifying strengths and weaknesses.
  • Reporting & Recommendations: Generates detailed reports with insights on visual effectiveness, persona engagement, and forecast accuracy, providing hypotheses for next episode optimization.

Quick Start

Input the episode's YouTube analytics data in pasted text or structured format, then specify the episode details to receive a performance review and improvement suggestions.

Frequently Asked Questions about publish-retro

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

FAQPage Schema
Can I use pasted text or screenshots for YouTube retrospective analysis?▼

A YouTube retrospective analyzes viewership metrics, retention, and comments to evaluate episode success. It compares observed data against predictive artifacts and benchmark standards, generating a report with hypotheses for future production improvements.

What is the best way to compare YouTube episode metrics against forecast accuracy?▼

To analyze YouTube episode performance, input your analytics data in pasted text, screenshots, or structured formats like CSV and JSON. The system flexibly handles these inputs to parse viewership metrics, traffic sources, and comments for evaluation.

How do I get production improvement recommendations from YouTube analytics?▼

The best way to compare episode metrics against forecast accuracy is to input your observed YouTube analytics alongside predictive artifacts. The system analyzes these comparisons to identify strengths, weaknesses, and optimization hypotheses for future episodes.

Can I use pasted text or screenshots for YouTube retrospective analysis?▼

To get production improvement recommendations, provide your episode's YouTube analytics data to the system. It evaluates visual effectiveness, persona engagement, and forecast accuracy, generating a detailed report with hypotheses for next episode optimization.

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