EdgePrompt: Engineering Guardrail Techniques for Offline LLMs in K-12 Educational Settings

EdgePrompt is a prompt engineering framework that implements pragmatic guardrails for Large Language Models (LLMs) in the K-12 educational settings through structured prompting inspired by neural-symbolic principles.The system addresses educational disparities in Indonesia's Frontier, Outermost, Underdeveloped (3T) regions by enabling offline-capable content safety controls.It combines: (1) content generation with structured constraint templates, (2) assessment processing with layered validation, and (3) lightweight storage for content and result management.The framework implements a multi-stage verification workflow that maintains safety boundaries while preserving model capabilities in connectivity-constrained environments.Initial deployment targets Grade 5 language instruction, demonstrating effective guardrails through structured prompt engineering without formal symbolic reasoning components.