image-generation

The Image Generation skill provides a robust framework for creating visual assets within the DeerFlow environment. Designed for users, creators, and developers, this skill bridges the gap between text-based intent and high-fidelity image output. By utilizing structured JSON-formatted prompt files, the skill ensures that complex requirements regarding subject matter, artistic style, lighting, and composition are communicated clearly to the generative model. It is particularly effective for character design, conceptual scenery, product visualization, and artistic exploration, where granular control over the final output is required.

• Executes automated image generation via dedicated Python scripts in isolated sandbox environments.

• Supports structured prompt engineering, allowing detailed specification of gender, age, clothing, accessories, era, and negative constraints.

• Enables style and composition guidance through the use of reference images, ensuring consistent output across generation tasks.

• Configures technical parameters such as aspect ratios and quality levels to meet specific delivery needs.

• Provides a reproducible workflow by saving prompt definitions in the /mnt/user-data/workspace/ directory.

• To initiate generation, clearly state the visual requirements including the subject, style, mood, and any specific technical aspects like aspect ratio.

• When using reference images, ensure they are accessible to the system to guide the style or character likeness effectively.

• The skill automatically handles the execution of the generate.py script; users should focus on refining the JSON prompt configuration for best results.

• Note that this skill requires access to the workspace and output directories for persistent storage of prompts and generated image files.

• Users should avoid reading the internal Python implementation directly; interaction is exclusively facilitated through the structured prompt file interface.

• The system is designed to work seamlessly within the DeerFlow agent harness, ensuring that generated visual content can be integrated into broader research or creative workflows.