GD-KS: A Spec-Driven Multi-Agent Framework for LLM-Assisted Game Development

  • Murilo Mazzotti Silvestrini UNICAMP
  • Leonardo Tórtoro Pereira UNESP

Resumo


Introduction: LLM-based coding assistants operate mainly at the level of code completion and do not model the process by which a software artifact is produced. This gap is acute in game development, whose pre-production (concept, design, narrative, art, audio) generates documentation whose volume and interdependencies rival the implementation effort — a burden falling disproportionately on indie studios and solo developers. Objective: To design a multi-agent framework for indie and solo developers that applies SpecDriven Development (SDD) to the game development lifecycle and decouples engine-agnostic design from engine-specific implementation. Steps: We designed GD-KS, an open-source four-phase spec-driven pipeline (ideation, design, planning, engine) with up to 32 specialized agents. Its main technical innovation is a plugin-based engine-profile abstraction isolating engine-specific knowledge from design artifacts, currently supporting Unreal Engine 5, Godot 4 and Unity 6, complemented by a single-source-of-truth project state with append-only audit trail. The framework is validated through schema validation, 240 automated tests, and multi-engine installation scenarios. Expected Results: The pipeline enforces documentation discipline that small teams often cannot maintain manually; the engine-profile abstraction lowers the cost of evolving to new engines; the project state supports fragmented sessions typical of solo work. A user study is planned as the next step.

Palavras-chave: game development, large language models, spec-driven development, AI-assisted software engineering

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Publicado
29/09/2026
SILVESTRINI, Murilo Mazzotti; PEREIRA, Leonardo Tórtoro. GD-KS: A Spec-Driven Multi-Agent Framework for LLM-Assisted Game Development. In: SIMPÓSIO BRASILEIRO DE JOGOS E ENTRETENIMENTO DIGITAL (SBGAMES), 25. , 2026, Goiânia/GO. Anais [...]. Porto Alegre: Sociedade Brasileira de Computação, 2026 . p. 954-965. DOI: https://doi.org/10.5753/sbgames.2026.26161.