A 'Claude Code skill' designed to enforce a specific problem-scoping methodology, based on Peter Naur's 'Programming as Theory Building,' by requiring an AI agent to create a 'problem-theory artifact' before generating code.

This submission represents a meta-level tool within the AI development ecosystem. It addresses a critical pain point in AI-driven code generation: the quality of problem definition. By forcing the AI agent to construct a 'problem-theory artifact' based on Peter Naur's methodology, it aims to improve the foundational understanding before coding, potentially reducing errors and increasing the relevance of generated solutions. This indicates a maturing AI development landscape where the focus shifts from raw code generation to structured, theoretically grounded problem-solving. For B2B SaaS, this highlights the emerging market for AI orchestration and methodology enforcement tools, ensuring AI outputs align with established engineering principles. It is not a direct SaaS product but a component or methodology for integration into larger AI development platforms.