What problem does it solve? Ambiguous or incomplete acceptance criteria cause defects to be discovered only after implementation. This Skill runs a pre-sprint QA refinement pass over a batch of backlog Stories, surfacing ambiguities, gaps, and edge cases before sprint planning so PO and Dev can fix requirements instead of production code. ## Core Features & Use Cases - Batch backlog triage: Resolves candidate Stories from explicit IDs or a JQL query, rejects non-Story types, applies veto rules and a risk score, and presents a ranked candidate table for user approval. - Structured AC refinement: Reuses sprint-testing's acceptance-test-planning phases to produce refined Given/When/Then scenarios, outline-only test design with coverage estimates, and PO/Dev question lists, all marked NEEDS PO/DEV CONFIRMATION where inferred. - Jira handoff automation: Writes refined ACs to the acceptance_criteria field, populates the acceptance_test_plan field, posts a handoff comment, adds shift-left-reviewed labels, transitions Stories to Estimation, and closes a [QA] Shift-Left Review tracking subtask. - Use Case: Paste a list like UPEX-100,101,102 sitting in Backlog and ask to groom them; the Skill triages, refines each Story sequentially, publishes results to Jira, and produces a batch report for sprint planning. ## Quick Start Ask the assistant to run shift-left refinement on a comma-separated list of backlog Story IDs such as UPEX-100, UPEX-101, and UPEX-102.