postmortem

Analyzes underperforming YouTube videos using metrics from the YouTube Analytics API.

161|6|Updated Mar 22, 2026

Search Tags:#postmortem #video analysis #video optimization #performance diagnosis #YouTube analytics

Ready to run

npx skills add https://github.com/daiki-beppu/youtube-automation --skill postmortem-daiki-beppu

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: postmortem
Source: https://github.com/daiki-beppu/youtube-automation/tree/main/.claude/skills/postmortem
Command: npx skills add https://github.com/daiki-beppu/youtube-automation --skill postmortem-daiki-beppu

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires youtube_analytics, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill analyzes the performance of videos that did not meet expectations, diagnosing the reasons and providing steps for further investigation.

Core Features & Use Cases

Analytics Review: Compares CTR, average viewing time, and impressions of failed videos with benchmarks and channel averages.
Hypothesis Generation: Formulates hypotheses based on symptoms and suggests validation steps.
Skill Recommendations: Recommends existing skills for further analysis, such as thumbnail comparison or comment analysis.

Quick Start

Run the postmortem skill with the video ID to analyze its performance and potential causes.

Frequently Asked Questions about postmortem

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

FAQPage Schema

How do I analyze why a YouTube video failed to meet performance expectations?▼

Yes, you can diagnose underperforming YouTube videos by quantifying symptoms like low CTR and short viewing time. The analysis benchmarks these metrics against channel averages to formulate hypotheses and suggest further investigation steps.

Do I need the YouTube Analytics API to diagnose video performance issues?▼

Yes, diagnosing video performance issues requires YouTube Analytics API access. This dependency is necessary to retrieve video analytics data, benchmark metrics, and generate hypotheses for why a video did not meet expectations.

What is the best way to find the causes of low YouTube video retention and CTR?▼

After identifying performance symptoms, the next step is to validate the generated hypotheses. The diagnosis recommends further analysis skills, such as thumbnail comparison or comment analysis, to verify the root causes of video underperformance.

Can YouTube analytics benchmarking help generate hypotheses for video optimization?▼

Yes, YouTube analytics benchmarking compares failed video metrics against channel averages to generate hypotheses. This process quantifies symptoms like low impressions and suggests targeted steps for further video optimization investigation.