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132,413 skills indexed with the new KISS metadata standard.
Techniques for generating clear, accurate, visually compelling infographic panels and data visualizations using AI image generation. Covers chart types, visual hierarchy, Nano Banana prompting for data-heavy images, and mixed-media approaches.
- Research queries requiring Gemini's knowledge and source citations
Generate panel images for investigations using Gemini in the browser via Chrome MCP extension. Uses the **multi-tab fire-and-harvest** approach for throughput with reliable single-tab download accuracy.
The GatorSquare editorial voice — institutional weight with vivid investigative storytelling. Not pop science. Not academic. The register that gets read at Harvard and shared by economists.
The eight-stage investigation framework every GatorSquare article follows. This is the editorial backbone — the equivalent of Porter's Five Forces for systems analysis.
Four hook formulas from elite publications, adapted for GatorSquare's visual investigation format. Plus the engagement loop that keeps readers clicking.
Every panel after panel-01 receives the previous panel's actual generated pixels. The prompt describes ONLY what changed. The chain carries visual identity forward.
Professional film techniques — shot types, camera movements, lighting setups, composition rules, and the 180-degree rule — translated into AI image generation prompt language. Think like a DP (Director of Photography), not an illustrator.
The animator's vocabulary for describing body positions in text prompts. How to make a character look like they're DOING something — not posed for a photograph. Covers line of action, weight, foreshortening, toddler-specific mechanics, and the Pixar posing principles.
Package investigation projects into self-contained, deployable ZIP files. Each zip works standalone (open index.html) AND is the upload format for the GatorSquare platform.
Every visual element in a scene is a layer. Each layer is an entity in `objects/`. The generation model composites them — you provide the ingredients.
> The agent is the editor. Each project gets a personalized reading experience. Zero config from the user.
When directing scenes sequentially, detect spatial/temporal gaps between the current panel and the next story beat, and insert bridge frames on the fly.
The Writer writes what happens. The Director visualises HOW it's shot — camera position, what's in frame, how objects move, what grows and shrinks as the camera-person moves through space.
Extract MAXIMUM structured intelligence from ALL project source files — not just knowledge.json, but the raw production files that contain data the knowledge tagging step may have missed or compressed. This skill governs the TypeScript extraction module (`knowledge-extractor.ts`) that feeds the Gato
The art of understanding what a person MEANS, not what they SAY. The client has a perfect image in their head — a scene so vivid they can feel it. But translating that internal vision to words is like describing color to a deaf person. Words come out in fragments, half-sentences, corrections mid-tho
- Deep research queries requiring ChatGPT's reasoning
Attach reference images (character sheets, previous panels, style references) to browser-based AI image prompts (Gemini, ChatGPT) for visual consistency across panels.
Before writing any prompt, mentally construct the scene in a 3D application like Blender. Place the camera, the subjects, the lights, the environment — then describe what the camera SEES, not what you KNOW about the scene.
A comprehensive reference for applying professional animation and comic techniques to frame-by-frame AI image generation. Makes sequential still images feel like motion.
> Check this before ANY task. Spawn agent to read relevant skills.
display_name: "xpost"
display_name: "Zine Deck Maker"
Agent skill for codex-debugging