What problem does it solve? Teams using AI-DLC planning need confidence that their Feature, Epic, Task, and Design documents contain enough detail for AI tooling to execute implementation, and they need a controlled way to move approved plans into Jira or Linear without creating incomplete or inconsistent tickets. ## Core Features & Use Cases - Confidence Assessment: Scores documentation across Feature Clarity, Task Completeness, Design Readiness, NFR Coverage, and Dependency Mapping using per-Epic verification subagents, with High/Medium/Low thresholds gating the transfer. - Multi-Backend Support: Reads artifacts from GitLab markdown branches, Linear Initiatives/Projects/Issues, or Confluence page hierarchies, normalizing them into a common verification format. - Sprint Execution Planning: Refines Sprint groupings, detects cross-Sprint dependencies, assigns phases and lanes, identifies the critical path, and propagates rebalancing changes back to source documents. - Jira Transfer: Creates the full Feature → Epic → Sprint → Story/Task hierarchy with labels, Story Points, and dependency links after explicit user approval; Linear backends update Initiative status natively instead. - Use Case: After running design and elaboration for an authentication feature, ask the assistant to verify readiness; it scores each Epic, lists blocking gaps such as missing acceptance criteria, and on approval creates the Jira ticket hierarchy. ## Quick Start Ask the assistant to verify the documentation for your feature branch or Linear Initiative and confirm whether it is ready to transfer to Jira.
