user-story-splitting
Break large stories and epics into smaller, independently deliverable increments using eight systematic splitting patterns.
- Provides eight splitting patterns: workflow steps, business rule variations, data variations, acceptance criteria complexity, major effort, external dependencies, DevOps steps, and Tiny Acts of Discovery for unpacking unknowns
- Emphasizes vertical slicing (each split delivers complete user value) rather than horizontal task decomposition or arbitrary chopping
- Includes validation checks to ensure splits are independent, testable, sprint-sized, and collectively equal the original story
- Covers common pitfalls: horizontal slicing, over-splitting, meaningless splits, hard dependencies, and ignoring user outcomes
Purpose
Break down large user stories, epics, or features into smaller, independently deliverable stories using systematic splitting patterns. Use this to make work more manageable, reduce risk, enable faster feedback cycles, and maintain flow in agile development. This skill applies to user stories, epics, and any work that's too large to complete in a single sprint.
This is not arbitrary slicing—it's strategic decomposition that preserves user value while reducing complexity.
Key Concepts
The Story Splitting Framework
Based on Richard Lawrence and Peter Green's "Humanizing Work Guide to Splitting User Stories," the framework provides 8 systematic patterns for splitting work:
- Workflow steps: Split along sequential steps in a user's journey
- Business rule variations: Split by different rule scenarios (permissions, calculations, etc.)
- Data variations: Split by different data types or inputs
- Acceptance criteria complexity: Split when multiple "When" or "Then" statements exist
- Major effort: Split by technical milestones or implementation phases
- External dependencies: Split along dependency boundaries (APIs, third parties, etc.)
- DevOps steps: Split by deployment or infrastructure requirements
- Tiny Acts of Discovery (TADs): When none of the above apply, use small experiments to unpack unknowns
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