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muse

Generate second-by-second video blueprints with dynamic format selection and retention engineering.

3|Updated Mar 14, 2026
Search Tags:#content strategy#production#AI#video#scripting#retention
One-click install
npx skills add https://github.com/GunjanGrunge/rrq --skill muse-gunjangrunge
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: muse
Source: https://github.com/GunjanGrunge/rrq/tree/main/skills/muse
Command: npx skills add https://github.com/GunjanGrunge/rrq --skill muse-gunjangrunge

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill ensures videos are structurally sound, engaging, and retain viewer attention by architecting the video's format, pacing, and visual direction based on dynamic data and proven retention principles.

Core Features & Use Cases

  • Dynamic Format Selection: Selects the optimal video format from a live library based on topic signals and performance data.
  • Blueprint Generation: Creates a detailed second-by-second blueprint including structural beats, tension devices, visual instructions, and retention checkpoints.
  • Retention Engineering: Implements strategies to overcome key viewer drop-off points (0:30, 1:00, Midpoint, 2 mins before end).
  • Visual Direction: Defines visual types, cut timing rules, and script-visual pairing.
  • Character Brief Generation: Creates detailed presenter profiles for avatar generation.
  • Use Case: When creating a new video on a complex topic, MUSE analyzes the topic, selects the best format (e.g., Explainer, Deep Dive), and generates a blueprint that maps out every beat, visual cue, and retention strategy to maximize audience engagement.

Quick Start

Use the muse skill to generate a video blueprint for a video about the future of AI.

Frequently Asked Questions about muse

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

FAQPage Schema
How do I create a video structure that maximizes viewer retention?▼

Video retention engineering applies proven strategies to overcome key drop-off points at 0:30, 1:00, midpoints, and 2 minutes before the end by mapping structural beats, tension devices, and retention checkpoints into a second-by-second blueprint.

What is the best way to select an optimal video format for a complex topic?▼

Selecting an optimal video format uses a multi-signal selection algorithm to analyze topic signals and performance data dynamically from a live library to choose the best structure, such as an Explainer or Deep Dive format.

How do I script visual direction and cut timing for video production?▼

Script visual direction by defining visual types, cut timing rules, and script-visual pairing within a detailed blueprint, ensuring every second of the video has mapped visual instructions and cues.

Can I generate presenter avatar profiles for AI video production?▼

You can generate presenter avatars by creating detailed character briefs that define presenter profiles, ensuring the AI avatar matches the visual direction and structural pacing of the video blueprint.

Does this video blueprinting approach work for any content strategy pipeline?▼

This blueprinting approach applies to any content creation pipeline for video production, analyzing topics and engineering retention walls to ensure complex subjects are structurally sound and engaging.

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