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GunjanGrunge
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rrq-retro

Automate post-publish video performance analysis over a 7-day cycle.

3|Updated Mar 14, 2026
Search Tags:#content strategy#knowledge management#performance review#video analysis#ai synthesis#post-publish analysis
One-click install
npx skills add https://github.com/GunjanGrunge/rrq --skill rrq-retro
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: rrq-retro
Source: https://github.com/GunjanGrunge/rrq/tree/main/skills/rrq-retro
Command: npx skills add https://github.com/GunjanGrunge/rrq --skill rrq-retro

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the analysis of video performance after publication, extracting lessons to improve future content strategy and avoid repeating mistakes.

Core Features & Use Cases

  • Automated Performance Monitoring: Tracks key metrics like CTR, retention, and geo performance for 7 days post-publish.
  • AI-Driven Synthesis: Uses advanced AI (Claude Opus 4) to synthesize agent reviews into actionable lessons.
  • Knowledge Archiving: Stores lessons in a searchable index for future reference.
  • Use Case: After a video is published, this Skill automatically monitors its performance, identifies what worked and what didn't, and writes a permanent lesson into a knowledge base, ensuring the team continuously learns and improves.

Quick Start

Initiate the rrq-retro skill to analyze the performance of video ID '12345'.

Frequently Asked Questions about rrq-retro

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

FAQPage Schema
How do I automate post-publish video performance analysis?▼

Automated post-publish video performance analysis tracks metrics like CTR, retention, and geo-performance over a 7-day cycle, then synthesizes the data into actionable lessons for your knowledge index.

What is AI synthesis for video content strategy?▼

AI synthesis for video content strategy uses a large language model to process agent reviews and performance data, generating actionable lessons that are archived to prevent repeating past content mistakes.

Do I need YouTube analytics integration to track video retention factors?▼

Yes, you need YouTube analytics integration to track video retention factors. The system requires YouTube analytics and geo-signal APIs to monitor 7-day post-publish performance and identify geographic trends.

Can I extract geo-performance trends from video content automatically?▼

You can extract geo-performance trends from video content automatically by utilizing geo-signal APIs. The system monitors geographic performance data over a 7-day cycle to identify regional audience trends.

How do I store content strategy lessons in a knowledge management index?▼

You store content strategy lessons in a knowledge management index by archiving the AI-synthesized reviews and performance data into a searchable repository for continuous future reference and improvement.

What are the limitations of automating video performance reviews?▼

Automating video performance reviews is limited to a 7-day post-publish cycle and requires external API integrations for YouTube analytics and geo-signals, alongside a large language model for data synthesis.

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