style-locks

Generate multi-scene video stories with consistent characters and synchronized narration.

34|7|Updated Nov 29, 2025

Search Tags:#consistency #visual-design #character-lock #negative-lock #style-lock

Ready to run

npx skills add https://github.com/jkitchin/skillz --skill style-locks

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: style-locks
Source: https://github.com/jkitchin/skillz/tree/main/skills/creative/video-storytelling/references/style-locks.md
Command: npx skills add https://github.com/jkitchin/skillz --skill style-locks

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Defines global and per-character visual constraints to prevent drift in multi-scene video storytelling.

Core Features & Use Cases

STYLE_LOCK: global visual guidelines (aspect, camera, lighting, color palette, materials, background, style, post).
CHARACTER_LOCK: per-character appearance consistency (colors, features, outfits).
NEGATIVE_LOCK: anti-patterns to avoid (no watermarks, no text errors, consistent lighting).

Quick Start

Create a STYLE_LOCK and a CHARACTER_LOCK for a main character to ensure consistency across scenes.

Frequently Asked Questions about style-locks

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

FAQPage Schema

How do I maintain visual consistency across multiple scenes in AI-generated video stories?▼

Visual consistency across scenes uses STYLE_LOCK to define global guidelines—aspect ratio, camera angle, lighting, color palette, materials, background, and post-processing style—applied uniformly. CHARACTER_LOCK ensures individual characters retain consistent colors, features, and outfits. NEGATIVE_LOCK prevents anti-patterns like watermarks or lighting errors, keeping the entire narrative visually coherent.

Can I keep AI-generated characters looking the same throughout a multi-scene video?▼

CHARACTER_LOCK maintains per-character appearance consistency by locking colors, distinguishing features, and outfit details across all scenes. Combined with global STYLE_LOCK guidelines, characters remain recognizable and visually unified even when AI regenerates images for different scenes.

What's the best way to prevent visual drift when generating video stories with AI images?▼

Define a STYLE_LOCK with precise visual constraints—lighting conditions, color palette, camera framing, and material properties—before generating scenes. Apply CHARACTER_LOCK for each character and NEGATIVE_LOCK to exclude unwanted elements. This constraint system prevents the AI from drifting toward inconsistent aesthetics across your 1 title scene plus 5 story scenes.

Does this work with narrated video assembly and voice mapping?▼

Yes. The Skill generates coherent multi-scene videos with AI images, narrated audio via ElevenLabs voice mapping, and automated assembly using ffmpeg into 1080×1080 MP4 format at 30fps with H.264 video and AAC audio, ensuring narration synchronizes with visual consistency locks.

What types of video stories benefit from style and character locks?▼

Style locks suit educational content, children's stories, social media videos, and character-driven narratives where visual consistency builds recognition and trust. Any multi-scene story requiring persistent character appearance and unified visual tone benefits from STYLE_LOCK, CHARACTER_LOCK, and NEGATIVE_LOCK enforcement.

Why do I need negative locks alongside style and character locks?▼

NEGATIVE_LOCK prevents common AI generation errors—watermarks, text inconsistencies, unwanted lighting shifts—that break immersion. Combined with STYLE_LOCK and CHARACTER_LOCK, negative constraints create a complete safety net ensuring the final video maintains professional quality and narrative coherence.