AIDraw-batch-img2img for Openclaw

An automation tool for batch processing reference-to-image tasks on the Tencent Hunyuan AI platform.

chottomattekimkim-droid
v1.0.0
Apr 9, 2026
0
740
0

Install & Download

1. ClawHub CLI

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

npx clawhub@latest install aidraw-batch-img2img

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 aidraw-batch-img2img 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 AIDraw-batch-img2img?

AIDraw-batch-img2img is a powerful automation skill designed specifically for users of the Tencent Hunyuan AI platform (timiai.woa.com). This tool simplifies the complex process of reference-based image generation by automating the repetitive tasks of uploading source files, applying prompts, and downloading generated variations. By leveraging Openclaw Skills, developers and designers can process entire directories of images without manual intervention, ensuring a consistent and efficient creative pipeline.

The skill handles the end-to-end lifecycle of image generation, from setting the correct aspect ratios and 2K resolution to managing browser sessions via Playwright. It is particularly useful for enterprise users or artists who need to generate high volumes of stylistic variations based on existing assets while maintaining structured local storage.

AIDraw-batch-img2img Use Cases

  • Processing large batches of reference images to generate AI-enhanced versions.
  • Creating multiple stylistic variations (e.g., 2 variations per source) for comparison.
  • Automating the download and organization of AI assets into local project folders.
  • Implementing standardized design styles across a collection of images using custom prompt templates.

How AIDraw-batch-img2img Works

  1. The user configures the source directory, generation keywords, and the desired number of variations per image.
  2. The script initiates a browser instance and navigates to the Tencent Hunyuan AI interface, utilizing saved login states.
  3. It automatically switches the platform to Reference Generation mode and clears previous image data.
  4. For every image in the source folder, the skill uploads the file, enters the prompt keywords, and sets resolution parameters to 2K high-definition.
  5. The tool monitors the generation progress, waiting for the AI to finish processing (typically 30-180 seconds).
  6. Once complete, it triggers a download, renames the output based on the original filename, and validates the file integrity before moving to the next task.

AIDraw-batch-img2img Setup

To use this skill within the Openclaw Skills ecosystem, ensure you have Python 3.8+ and the necessary automation drivers installed.

Install dependencies via CLI:

pip install playwright requests
playwright install chromium

Initial Configuration:

  1. Manually log in to timiai.woa.com in your browser to save the session state.
  2. Run the main automation script:
python scripts/batch_img2img.py
  1. Follow the prompts to provide the source folder path and generation parameters.

AIDraw-batch-img2img Data Schema & Taxonomy

The skill follows a strict file organization and metadata structure to ensure data traceability:

Component Details
Source Path Local directory containing the reference images.
Output Directory Automatically named using the format: SourceFolderName_Date_AI.
Filename Schema Output files are saved as OriginalName_SequenceNumber.png.
Templates Prompt styles are managed via references/keyword-templates.md.
Verification Includes file size checks and automated retry logs for failed generations.

AIDraw-batch-img2img Advanced Features

  • Intelligent retry mechanism that automatically handles network timeouts or platform errors.
  • Automated image validation to ensure downloaded files are not corrupted and meet size requirements.
  • Support for adaptive aspect ratio detection based on the source reference image.
  • Integration-ready architecture for multi-agent workflows using Openclaw Skills to chain image generation with other design tasks.

SKILL.md


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