What problem does it solve? Initial AI-generated drafts, plans, and decisions often contain unexamined assumptions and weak spots. This Skill provides a structured refinement checkpoint that pushes the LLM to reconsider and improve its most recent output using proven critique methods like socratic questioning, first principles, pre-mortem, and red teaming. ## Core Features & Use Cases - Method Catalog Serving: A Python script serves a CSV catalog of elicitation methods by category, name, or random draw, keeping the full catalog out of context until needed. - Interactive Refinement Menu: Presents five curated methods per round with options to reshuffle, list all methods, or proceed, applying chosen methods iteratively so refinements compound. - Customizable Workflow: Supports team and personal TOML overrides for preferences and additional custom methods that merge into the catalog as first-class entries. - Use Case: After drafting a product launch plan, invoke this Skill to run a pre-mortem and red team analysis on the plan, revealing risks and gaps before finalizing it. ## Quick Start Ask the AI to run advanced elicitation on the plan it just drafted and apply a pre-mortem method to it.
