Explain Orkid math types and their usage in code.
npx skills add https://github.com/tweakoz/orkid --skill orkcore-math
Please help me install this Agent Skill. Skill: orkcore-math Source: https://github.com/tweakoz/orkid/tree/main/.claude/skills/orkcore-math Command: npx skills add https://github.com/tweakoz/orkid --skill orkcore-math
Orkid developers often need a quick, authoritative reference for math types and their usage across the codebase. This Skill provides a centralized description of fvec2/3/4, fmtx3/4, fquat, DecompTransform, TransformNode, MultiCurve1D, color utilities, and Klein integration to speed up learning and implementation.
Ask for details on a specific math type (e.g., fvec3 or fmtx4) to get concise API guidance.
High-intent search queries and answers about installing and using this skill.
You can use fvec3 for 3D vector operations and fmtx4 for 4x4 matrix transformations in ork.core. Ask for details on a specific math type to get concise API guidance, including header mappings, constructors, and common operations to accelerate development and debugging.
Ork.core provides fquat for quaternions, alongside TransformNode and DecompTransform for handling transformations. The reference covers these types comprehensively, including their constructors and common operations for implementation and debugging tasks.
Klein integration is supported alongside ork.core math types like vectors, matrices, and quaternions. The reference explains how these types interact with Klein integration to support development and debugging tasks, providing authoritative API guidance for implementation.
Yes, the ork.core math reference includes color utilities and MultiCurve1D helpers. These are covered alongside the primary math types like fvec2/3/4, fmtx3/4, and fquat to provide a centralized description for quick lookup during development and debugging.
The best way to look up constructors and header mappings is to query the ork.core math reference directly. It provides quick lookup for header and file mappings, constructors, and common operations to speed up learning and implementation across the codebase.
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