brainstorm

To break down a vague feature request into actionable scrum tasks, engage an AI scrum master to challenge assumptions, uncover hidden constraints, and decompose high-level ideas into technically sound stories ready for backlog commitment.

Backlog refinement is the process of pressure-testing epics and user stories for scope and technical feasibility. An AI scrum master facilitates this by providing critical feedback and vetting proposed features before board commitment within the JengaAgent framework.

Yes, you can use this skill to pressure-test project scope and uncover edge cases. It engages an inquisitive scrum-master agent role to deliver frank feedback that identifies hidden constraints and prevents scope creep during planning.

To define technical requirements for a new module before backlog commitment, invoke the brainstorm skill to vet the proposed features for scope, constraints, and technical feasibility, ensuring all tasks are fully decomposed.

Yes, this backlog refinement skill maintains session context for agile planning. It requires the scrum-master agent role to preserve ongoing conversation state and provide continuous critical feedback on development tasks.

The main limitation is that the AI agent operates strictly within the JengaAgent framework, meaning it requires the scrum-master agent role to be active to maintain session context and properly challenge assumptions during the planning session.