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Reveal · Skill Anatomy Engine

Reveal · Skill Anatomy Engine

Turn Skill architecture into a shareable 4:3 infographic

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13
CategoryImage
FromYouMind

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Description

Dissect any Skill’s architecture and examples into a single 4:3 infographic. After reading the target Skill, it extracts seven dimensions—identity, workflow, variables, boundaries, and more—then lets users choose the example source and a dual-axis visual style (mood × technique, with 8 curated combinations expandable to the full library). It generates a single image with the architecture and example layers presented together, ready to share externally. Built-in permission branching, strict word-count limits, honest labeling, and word-for-word text verification help ensure accuracy.

Editor's Recommendation
D

Recommended by

Dancang

Why we love this skill

Compresses a complex Skill's identity, process, variables, boundaries, and real cases into a shareable 4:3 infographic. Its uniqueness lies in three-step confirmation, case source grading, and strict auditing, balancing structural fidelity, information honesty, and visual readability.

Instructions

Related Skills

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9D Visual Deconstruction

Break down one or more infographics, data visualizations, flowcharts, timelines, maps, knowledge graphs, and organizational charts into reusable visual and information structures. Understand precisely why an image is organized the way it is and reconstruct a similar communicative effect. The skill examines spatial composition, dimensionality and materials, color hierarchy, typography and layout, and module relationships, while also identifying chart encodings, reading paths, visual-symbol metaphors, and geographic or network relationships—so the analysis goes beyond simply describing what the style resembles. You will receive a parameterized visual deconstruction covering the canvas and compositional logic, visual hierarchy, text density, module topology, ways of expressing data and relationships, and the narrative flow within the image. For statistical charts, maps, and relationship networks, the output focuses on how data is mapped to visual variables such as color, position, size, connecting lines, and nodes. For complex subject-specific visuals, it further organizes the coordinated relationships among graphics, text, and metaphor systems. Based on this analysis, the skill generates detailed, clearly structured English image-generation prompts suitable for infographic recreation, visual research, design reference, brand content exploration, and concept development. Whether you provide an existing image or an idea for a theme and visual direction, you will receive prompts aimed at reproducing the underlying structure—not just a vague description of the style.

知
53k
Image

Essential Photography Layouts

Ideal for creators exploring photo style directions, creating visual exercises, and making content illustrations. Provide a text theme or readable photos with usage rights, along with the subject to keep, color scheme, and aspect ratio; the default is a 3:4 vertical diptych. The upper frame features natural photography, while the lower frame keeps the same subject as a base, organizing seven numbered detail experiment cards: 01 fine stripes, 02 grayscale paper texture, 03 ink line sketch, 04 cyan-red offset, 05 pixel blocks, 06 iridescence, and 07 two-tone halftone. The cards zoom in on visible details of the subject for easy comparison of different visual directions; these are not same-coordinate filters on a base image, nor seven independent standalone images. The Skill lists the close-up and effect for each card, actually calls image tools to generate the output, verifies the seven numbers, visual differences, subject, and layout, and then revises based on specific issues. It delivers an actual layout image, an effect checklist, and inspection notes, with prompts included when needed. Without image tools, image generation remains incomplete. Four final display pieces are fictional AI cases regenerated locally on November 12, 2026, using the revised Skill: headphone woman, white cat, vase, and arcade; these are not real photos, client work, or algorithmic processing results. Initial requirements for same-coordinate alignment were not met, so failure records were kept and changed to explicit detail cards before running four cases. Each final image shows seven cards from 01 to 07 with distinct effects, but card details, flower shapes, compositions, and upper-lower subject sizes vary without guaranteeing exact identity or structural consistency. The avatar reference was independently generated from the initial white cat case as a conceptual demonstration, not a fifth standalone case or strict seven-window validation image. Effects are visually simulated by image models without claiming to execute seven real filter algorithms, quantifiable parameters, lossless processing, or layered editable files. Text planning recommends GPT, and image creation relies on available image generation or editing tools. Local usage uses the built-in image_gen, and tools do not return specific model IDs, so no binding to Image2 is claimed. Photo editing and YouMind operations have not been practically tested, so identity, product structure, text, or cross-image consistency cannot be guaranteed. Image generation is explicitly marked incomplete if no image tools are available. The 299 credits cover the Skill installation price and do not include platform model or third-party service fees; PSD or vector source files are not delivered, and automatic publishing or purchasing is not included.

若
0299

Text to 3D Infographic

Transform a single sentence, paragraph, or abstract concept into a clear and readable 3D stereoscopic infographic, making complex content ideal for presentations, article illustrations, study notes, course explanations, and technical descriptions. The Skill extracts the core points from the original text, presenting them with brief labels and concise descriptions on 3D nodes, cards, or floating panels while preserving the original meaning to avoid lengthy text walls, and matches the language and image ratio to the content. It matches 3D graphic structures such as processes, timelines, hierarchical structures, radial layouts, comparison layouts, and more based on parallel, progressive, circular, hierarchical, comparative, causal, or temporal relationships between key points, clearly linking each text node to its corresponding visual unit. It also selects appropriate 3D styles, materials, color palettes, and lighting for business, technology, education, or process explanation scenarios, placing text on flat front surfaces to enhance text-image readability. After generating the image, it provides the graphic structure, visual style and lighting material strategy, text list on the image, content coverage and compression notes, and the actual image ratio used, making it easy to verify information completeness and use directly for business presentations, science explanations, process walkthroughs, or daily content organization.

李
050

Information

Version
v3
Last updated
Runtime credits
Usage-based
Models
Auto

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Reveal · Skill Anatomy Engine