A systematic workflow for maintaining character consistency and preventing appearance drift in multi-shot AI video generation.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install character-consistency-workflow
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install character-consistency-workflow using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Character Consistency Workflow?
The Character Consistency Workflow is a professional framework designed to solve the problem of character drift in AI-generated short films and videos. It addresses visual instabilities where faces, clothing, or expressions change unexpectedly between shots. By implementing this skill within the Openclaw Skills ecosystem, creators can ensure their AI-generated protagonists maintain a rock-solid identity across complex narrative sequences.
This methodology categorizes consistency into three distinct levels: Appearance, Costume, and Emotion. It leverages advanced technical backgrounds from tools like Seedance 2.0 and Nano Banana 2 to provide a reliable path for high-fidelity video production, ensuring that skin tones, facial proportions, and hair styles remain uniform throughout the entire creative lifecycle.
Character Consistency Workflow Use Cases
- Maintaining visual identity across multi-shot AI video sequences.
- Preventing character face-changing or outfit-switching between different scenes.
- Standardizing character assets for collaborative AI film production teams.
- Automating consistency checks for high-volume video content generation workflows.
- Synchronizing character traits across different AI models and generation platforms.
How Character Consistency Workflow Works
- Perform a Character Drift Diagnosis to identify stability requirements for appearance, costume, and emotional continuity.
- Execute Asset Preparation by capturing standardized reference shots (front, side, and 3/4 views) and expression sheets.
- Implement the Consistency Token System by generating a fixed descriptive formula for physical traits and scene-specific clothing.
- Apply Cross-Shot Consistency Rules by embedding complete token blocks and reference image paths into every generation prompt.
- Conduct a five-point Quality Check to verify face shape, hair color, skin tone, proportions, and lighting across all generated shots.
Character Consistency Workflow Setup
To integrate this workflow into your Openclaw Skills environment, organize your local asset directory as follows:
# Create character directory structure
mkdir -p characters/protagonist/{expressions,costume_detail}
# Initialize your consistency tokens
touch characters/protagonist/tokens.md
Ensure that your generation prompts are configured to include the reference path syntax: Style Reference: ./characters/protagonist/ref_front.jpg. This allows the AI agent to maintain the identity lock during the rendering process.
Character Consistency Workflow Data Schema & Taxonomy
The workflow organizes character data using a hierarchical metadata structure to ensure the AI agent can retrieve specific physical attributes reliably:
| Folder/File | Purpose | Metadata Scope |
|---|---|---|
ref_front.jpg |
Base Identity | Locked facial features and skin tone |
expressions/ |
Emotion Map | 6-8 reference shots for emotional overlay |
tokens.md |
Logic Layer | BASE_IDENTITY, PHYSICAL, and HAIR formulas |
costume_detail/ |
Detail Lock | Textures, accessories, and fabric patterns |
Character Consistency Workflow Advanced Features
- Emotion Overlay Stacking: Allows for dynamic expression changes without breaking the underlying facial structure.
- Cross-Platform Parameter Mapping: Optimized instructions for Seedance 2.0, Nano Banana 2, LibLib, and Jimeng models.
- Hex-Color Code Locking: Prevents color drift by specifying exact hex values (e.g., #1B2838) for hair and clothing within the Openclaw Skills prompt logic.
- Negative Token Automation: Pre-configured negative prompts to prevent common AI artifacts like deformed hands or extra limbs during consistent character generation.
SKILL.md
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