Model Prompt Generator for Openclaw

Converts Chinese clothing descriptions into professional, highly detailed English fashion photography prompts for AI image generators.

openlark
v1.0.0
Jun 8, 2026
0
487
0

Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install model-prompt-generator

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install model-prompt-generator 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 Model Prompt Generator?

The Model Prompt Generator is an advanced AI agent capability designed to streamline the workflow of fashion brands, e-commerce retailers, and digital marketers. By translating and expanding brief Chinese descriptive inputs into granular, professional English prompts, this tool ensures high-fidelity image outputs from standard AI art generation platforms. It bridges the gap between basic product listings and editorial-grade visual assets.

Integrating this tool within your Openclaw Skills ecosystem ensures that every prompt systematically covers critical photographic dimensions. It eliminates guesswork and prompt engineering fatigue, delivering consistent and diverse visual configurations that elevate e-commerce product listings and lookbooks.

Model Prompt Generator Use Cases

  • Automatically generate model prompts based on basic raw product specifications for high-quality marketing assets.
  • Craft a detailed clothing shoot prompt for specific styling lookbooks and seasonal product drops.
  • Streamline the creative pipeline by generating an explicit model image prompt for swift prototyping and catalog design.

How Model Prompt Generator Works

  1. Parse Clothing Description: The skill extracts core attributes from the input text, analyzing factors like apparel type, color, material, style, season, and optional user constraints like model ethnicity or specific poses.
  2. Dimension Building: It constructs an optimized prompt string containing information across four essential axes: Model Appearance, Overall Coordination, Scene & Lighting, and Photography Style.
  3. Refinement & Output: Filters out any conversational filler or localized explanations to return a single, optimized, professional-grade English prompt limited to 700 characters.

Model Prompt Generator Setup

To deploy and configure this capability within your Openclaw Skills architecture, add the skill to your project configuration:

openclaw skill install model-prompt-generator

Ensure your local environment configuration or agent instructions point to this module when processing apparel metadata pipelines.

Model Prompt Generator Data Schema & Taxonomy

The skill expects structured or unstructured textual product data and outputs a sanitized string format:

Attribute Description Output Type
Input Content Text describing clothing details, styling goals, and model specifications String (Chinese/English)
Output Prompt Single, condensed English prompt block (≤700 chars) String (Plain English Text)

Output Constraints

  • Strict character budget: ≤700 characters.
  • Zero conversational formatting or markdown block wrappers outside the direct prompt asset.

Model Prompt Generator Advanced Features

  • Diverse Representation Filters: Built-in logic prioritizes global, multi-ethnic, and inclusive representation when no specific model details are declared.
  • Cohesive Accessory Layering: Automated contextual look matching that automatically attaches complementary, seasonally-appropriate accessories, bags, footwear, and jewelry to the prompt.
  • User Preference Override: Fully dynamic schema parsing ensures that if a user's unique styling request overrides conventional fashion rules, the prompt builder favors user specification over standard styling benchmarks.

SKILL.md


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