spellprocessing

Spellprocessing is a term used in academic, gaming, and fan communities to describe the study and engineering of magical spells within fictional or game worlds. It treats spells as structured procedural knowledge, including invocations, ingredients, and intended effects, and aims to model their generation, interpretation, and simulation computationally.

Key components include spell encoding schemes, grammar-based models for spellcasting, ontologies of magical effects, and simulation engines that predict outcomes given inputs and constraints. Researchers use formal grammars, semantic networks, and, increasingly, machine learning to generate new spells and to analyze existing ones. Evaluation typically relies on consistency with the fictional system, playtesting feedback, and expert judgment.

Applications include game design for balancing and scripting, authoring tools for world-building and interactive fiction, and scholarly analysis of fantasy texts. Data sources range from in-universe spellbooks and game manuals to fan wikis and fan fiction, which pose challenges for licensing and standardization.

Challenges include diverse and inconsistent magic systems, ambiguous or subjective effects, and difficulty measuring correctness or usefulness across contexts. Ethical considerations concern the portrayal of violence and power, and the risk of reinforcing stereotypes. The field remains largely informal, with formalization most common in game-engine contexts or experimental linguistics.