An AI coding agent skill that systematically generates structured, high-fidelity prompt frameworks for multi-character ensemble posters from any book, game, or television series.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install ensemble-poster-prompt
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 ensemble-poster-prompt 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 Ensemble Poster Prompt Generator?
The Ensemble Poster Prompt Generator is an advanced prompt engineering skill designed for AI coding environments. It converts user-provided titles of films, literature, anime, or video games into production-ready, highly detailed image generation prompts tailored for group character posters. By evaluating historical eras, tonal parameters, and character interrelations, it translates abstract narratives into cohesive visual blueprints.
Built to function flawlessly within the Openclaw Skills ecosystem, it enforces precise structural design over the output. It maps genres to optimized aesthetic configurations while utilizing a objective, line-sketch character description methodology to guarantee authentic, high-quality, and structurally sound generation prompts.
Ensemble Poster Prompt Generator Use Cases
- Transforming a media title into a production-grade multi-character generation prompt.
- Extracting canonical clothing styles, facial features, and character dynamics from text reference files.
- Generating structured compositional maps for complex graphics design configurations and midjourney inputs.
- Instantly standardizing image generation formats across various media categories.
How Ensemble Poster Prompt Generator Works
- The skill captures the input arguments containing the title or scenario description from the environment variable.
- It analyzes the name, media type origin, historical timeline, thematic tone, and core relational networks of the characters.
- It maps the project to an optimized visual style dictionary matrix spanning from traditional ink wash to futuristic cyberpunk aesthetics.
- It isolates 3 to 6 key characters and drafts objective line-sketch summaries defining their canonical appearances and geometric placements.
- It defines structural layouts, including layer spacing, spatial ratios, and background components.
- It appends text banners wrapped in double quotes alongside lighting, resolution, and strict quality guardrails for structural safety.
Ensemble Poster Prompt Generator Setup
System Integration
To load this tool into your workspace environment, reference the skill profile inside your configuration manifest:
# Example syntax to register the skill within your agent configuration
openclaw skills add ensemble-poster-prompt
Ensure that the core executable environment has read access to the local template structure and can access the pipeline arguments via $ARGUMENTS variables.
Ensemble Poster Prompt Generator Data Schema & Taxonomy
Output Format Configuration
The prompt generator processes attributes into a structured output framework. The resulting block is partitioned according to the following template schema:
| Section Border | Key Data Fields | Formatting Strategy |
|---|---|---|
| Header Parameters | Title, Art Style, Dimension Aspect Ratios | Text-based metadata configurations |
| Character Elements | 3-6 Core Characters, Identity Labels, Attributes | Objective, line-sketch summaries (3-5 sentences each) |
| Composition Plan | Layer distribution, sizing balance, shapes | Hierarchical background and foreground arrangement |
| Text Layering | Primary Header text, Theme sub-headers | Text explicitly isolated using double quotes ("Text") |
| Quality Controls | Color grading, illumination bounds, avoidance rules | Strict performance limits to avoid facial and limb artifacts |
Ensemble Poster Prompt Generator Advanced Features
- Context-Aware Mapping Engine: Automatically switches layout paradigms based on whether input is flagged as historical fiction, high fantasy, or futuristic sci-fi.
- Strict Line-Sketch Validation: Enforces a descriptive rule that prevents the LLM from adding subjective prose, ensuring only visible physical features are detailed.
- Double-Quote Text Isolation: Decouples textual elements from visual descriptions to prevent text generation leaks from corrupting background rendering engines.
SKILL.md
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