qcsd-refinement-swarm

Automating sprint refinement requires orchestrating a multi-agent swarm to evaluate user stories using SFDIPOT analysis and generate BDD scenarios for validation. This skill coordinates core and conditional agents to perform requirements validation, contract testing, and impact analysis to ensure stories are ready for development.

SFDIPOT analysis is a framework of product factors used to comprehensively evaluate user stories during sprint refinement. It helps assess stories across multiple dimensions to ensure requirements are fully validated and prepared for development readiness decisions.

Generating BDD scenarios from acceptance criteria is automated by orchestrating multi-agent swarms that parse user story inputs. The agents apply SFDIPOT analysis to validate requirements and automatically produce BDD scenarios to guide development and testing.

Multi-agent coordination can be used for requirements validation by deploying a swarm of core and conditional agents with specific domains. These agents handle distinct functionalities like contract testing and impact analysis to provide a comprehensive readiness decision for user stories.

Before running sprint refinement with agent coordination, you need user story content and a specified output folder. These inputs activate the swarm orchestration to process stories through SFDIPOT analysis, BDD generation, and multi-agent validation workflows.

Multi-agent swarms for sprint refinement are best used when you need to efficiently process user stories through comprehensive SFDIPOT analysis, automated BDD scenario generation, and parallel validation tasks like contract testing and impact analysis that manual review cannot scale to handle.