What problem does it solve?
This skill solves the pain point of users who have finished articles but lack design expertise to select and create appropriate matching images, eliminating the need for users to make complex design decisions on their own.
Core Features & Use Cases
- Intelligent illustration candidate scanning: Automatically scans the full article to identify high-value cover and inline illustration candidates based on reader understanding gain, with no minimum frequency threshold for candidate selection.
- Guided alignment workflow: Provides a 3-step user interaction process to select illustration schemes, confirm a unified visual style for the entire batch of images, and refine composition and in-image text strategy for each individual illustration.
- Standardized prompt generation: Produces compliant .prompt files with visual thesis, style anchors, and structured composition prompts that meet mainstream image generation model requirements, with built-in quality checklists to ensure output consistency and narrative alignment.
- Use case: For a technical blog post about distributed system consensus algorithms, use this skill to automatically generate a cover concept diagram and inline flowcharts that match the article's narrative, ready for direct use with image generation tools.
Quick Start
Provide your article (as a local file, URL, pasted text, or existing conversation context) to the article-image-prompt skill to automatically generate all required illustration prompts after confirming the scheme and style.
