The problem

Vague app ideas often lead to scope creep or development stalls because core data structures and user flows aren't defined. Moving straight from a concept to a builder tool without a specification results in messy schemas and wasted hours refactoring logic.

What it does

• Generates 10-12 numbered core function components with specific builder actions.
• Maps out primary user flows and identifies critical edge case failure scenarios.
• Defines a complete data model including entities, field types, and relationships.
• Creates a structured user role matrix with granular CRUD permissions and auth methods.
• Produces an assumptions log that flags unstated decisions rather than guessing.

Frameworks & tools

Optimized for Airtable, Webflow, FlutterFlow, Make, and various AI app builders.

Why this beats prompting it yourself

Standard LLM prompts often hallucinate missing details or ignore platform constraints. This skill enforces a rigorous architectural framework that translates business logic into platform-specific terminology, ensuring your data model and logic are actually buildable in your chosen stack.

Use cases

• Convert a napkin sketch into a structured Airtable base schema and automation plan.
• Draft buildable FlutterFlow widget requirements and navigation logic from a one-liner.
• Define the MVP scope fence and future roadmap for a client discovery session.
• Generate technical handoff documentation for no-code developers or AI agents.

Known limitations

Not intended for production security policies or deep technical infrastructure design. Low-context prompts will result in lower confidence scores and more items in the assumptions log.