godot-autoload-architecture

Expert patterns for Godot AutoLoad (singleton) architecture including global state management.

What this skill does for you

Expert patterns for Godot AutoLoad (singleton) architecture including global state management, scene transitions, signal-based communication, dependency injection, autoload initialization order, and anti-patterns to avoid. Use for game managers, save systems, audio controllers, or cross-scene resources. Trigger keywords: AutoLoad, singleton, GameManager, SceneTransitioner, SaveManager, global_state, autoload_order, signal_bus, dependency_injection.

Quoted from the skill description in the pinned source

Who made it

Publisherthedivergentai

Repositorygd-agentic-skills

Installs359as 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-autoload-architecture 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: sha256:3427cc48667e5d659f87bdc4d85d62025a5c73c6346e123badd69251a3a20f68
Licence: LGPL-3.0