cd-foundations

Computational Design Foundations

This skill auto-activates whenever a computational design context is detected. It provides the foundational knowledge layer, paradigm classification, tool routing, and anti-pattern awareness that underpins every other skill in the Computational Design Skills Plugin.

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1. Computational Design Paradigm Overview

Computational design is not a single methodology but a spectrum of interrelated paradigms. Each paradigm carries distinct assumptions about the relationship between the designer, the algorithm, and the artifact. Understanding which paradigm applies to a given problem is the first critical decision in any computational design workflow.

1.1 Parametric Design

Definition: Parametric design establishes explicit relationships between design elements through variable parameters and constraints, enabling the exploration of a continuous design space by adjusting input values. The geometry is not drawn; it is described as a system of dependencies.

Key Characteristics:

• Associative relationships between geometry elements (change one parameter, downstream geometry updates)
• Design intent is encoded as a graph of operations, not a static drawing
• Enables rapid iteration and variant generation from a single model definition
• Parameters can be numeric (dimensions), geometric (reference curves), or categorical (material type)

When to Use: When the design problem has well-defined variables and the goal is to explore a constrained solution space — e.g., facade panel optimization, structural member sizing, massing studies with fixed programmatic requirements, and any scenario where rapid iteration across known parameters is valuable.

1.2 Generative Design

Definition: Generative design delegates part of the design ideation to algorithmic processes that produce novel solutions based on goals, constraints, and evaluation criteria. The designer defines the problem space and fitness criteria; the algorithm proposes solutions the designer may not have conceived.