What problem does it solve? Turning a feature specification and implementation plan into an actionable, ordered task list is tedious and error-prone. This Skill automates the creation of a tasks.md file that organizes work by user story so each increment is independently implementable and testable. ## Core Features & Use Cases - Story-Organized Task Generation: Reads spec.md, plan.md, data-model.md, contracts/, and research.md to produce tasks grouped by user story priority (P1, P2, P3). - Strict Checklist Format: Every task follows a validated format with checkbox, sequential task ID, parallelization marker, story label, and exact file path. - Dependency & Parallelism Analysis: Produces a dependency graph, parallel execution examples per story, and an MVP-first implementation strategy. - Extension Hooks: Supports optional and mandatory pre/post hooks declared in .specify/extensions.yml. - Use Case: After writing a spec and plan for a new feature with GitHub Spec Kit, run this Skill to instantly get a complete tasks.md ready for LLM-driven implementation. ## Quick Start Ask the AI to generate the tasks.md for the current feature based on the spec and plan in the specs directory.