godot-3d-materials

Expert patterns for Godot 3D PBR materials using StandardMaterial3D including albedo.

What this skill does for you

Expert patterns for Godot 3D PBR materials using StandardMaterial3D including albedo, metallic/roughness workflows, normal maps, ORM texture packing, transparency modes, and shader conversion. Use when creating realistic 3D surfaces, PBR workflows, or material optimization. Trigger keywords: StandardMaterial3D, BaseMaterial3D, albedo_texture, metallic, metallic_texture, roughness, roughness_texture, normal_texture, normal_enabled, orm_texture, transparency, alpha_scissor, alpha_hash, cull_mode, ShaderMaterial, shader parameters.

Quoted from the skill description in the pinned source

Who made it

Publisherthedivergentai

Repositorygd-agentic-skills

Installs341as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the godot-3d-materials skill from thedivergentai/gd-agentic-skills.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 4c4d0ff5c4597938cc9257d99d9e35f7692c9c06. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 4c4d0ff5c4597938cc9257d99d9e35f7692c9c06. Raw findings: 1. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 4c4d0ff5c4597938cc9257d99d9e35f7692c9c06. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/thedivergentai/gd-agentic-skills
Pinned skill file: View source at revision
Revision: 4c4d0ff5c4597938cc9257d99d9e35f7692c9c06
Package hash: sha256:f74a192648780ef3c767ed5c48e5de6497eaa41d926889579d46b1f65f90f6f8
Licence: LGPL-3.0