Surfaces and applies proven frameworks from domain experts before building or evaluating AI skills and agents.
Methodology Curator is a strategic meta-skill designed to ground AI development in established best practices and expert frameworks. By surfacing methodologies from domain masters—such as TDD principles for testing or instructional design patterns for tutorials—before the brainstorming or coding phase, it prevents 'reinventing the wheel' and ensures that created skills, hooks, and agents are built upon proven logic rather than ad-hoc assumptions. It functions as a pre-flight check that provides high-level guidance for developers seeking to embed deep domain expertise into their automated workflows.
Key Features
01Standardized methodology briefs to guide subsequent skill creation
02Domain-specific framework surfacing for instruction, testing, and debugging
03Methodology gap analysis for auditing existing AI tools and skills
04Strategic workflow integration for both creation and evaluation cycles
05Curated database of industry 'Masters' and their core principles
06123 GitHub stars
Use Cases
01Performing a methodology audit on an existing code review tool to identify missing feedback patterns
02Grounding a new coding assistant skill in established instructional design frameworks
03Selecting the optimal debugging framework before building a complex troubleshooting agent
