What problem does it solve? Ending a coding session cleanly requires several bookkeeping steps: confirming all work is committed, archiving finished tasks, and logging what was accomplished. This Skill automates that wrap-up sequence so nothing is forgotten and the project history stays consistent. ## Core Features & Use Cases - Dirty-tree classification: Inspects git status output, separates current-task changes from unrelated parallel work, and blocks the wrap-up if uncommitted task code remains. - Task archiving: Archives the active task (plus any other completed tasks the user confirms) via task.py archive, producing automatic chore(task): archive commits. - Session journaling: Records a session entry with title, commit hashes, and summary through add_session.py, producing a chore: record journal commit. - Use Case: After finishing a feature and committing the code in your workflow's commit phase, run this Skill to archive the task and log the session so the next session starts from a clean, documented state. ## Quick Start Ask the AI to finish the work session by archiving the current task and recording a session journal with the recent commit hashes.