Manage TypeScript data types, Zustand state, and d3-force-3d graph layouts.
npx skills add https://github.com/KJ-devs/portfolio --skill data-architect-kj-devs
Please help me install this Agent Skill. Skill: data-architect Source: https://github.com/KJ-devs/portfolio/tree/main/.claude/skills/data-architect Command: npx skills add https://github.com/KJ-devs/portfolio --skill data-architect-kj-devs
This Skill manages the complex data structures, state, and layout logic for the Neural Portfolio project, ensuring precise typing and efficient data handling.
Use the data-architect skill to define the types for a new project neuron.
High-intent search queries and answers about installing and using this skill.
TypeScript data modeling for a 3D neural network portfolio involves defining strict types for neurons, connections, and projects. This establishes a precise data architecture that ensures efficient data handling and reliable interactive visualization.
Zustand state management handles interactive graph selection by maintaining global application state for selected neurons, search queries, and panel visibility. This enables dynamic state updates for seamless interactive filtering and visualization control.
Implementing a 3D force-directed graph layout for data visualization is best achieved using d3-force-3d. This library provides 3D graph simulation specifically designed to calculate spatial positions for complex network structures like a neural portfolio.
Yes, strict TypeScript typing works with dynamic d3-force-3d simulations by defining static data definitions for portfolio elements alongside dynamic state updates. This integration ensures type safety while maintaining interactive 3D graph simulation capabilities.
Zustand is needed for global state to manage runtime interactions like search queries and panel visibility, complementing your TypeScript data models. While types define static structure, Zustand handles dynamic state updates required for interactive portfolio visualization.
Using d3-force-3d for a neural network provides specialized 3D force-directed graph simulation capabilities. Unlike standard 2D alternatives, it calculates spatial layouts in three dimensions, accurately modeling complex connections between skills, projects, and experiences.
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