What problem does it solve? Ending a coding session involves several easy-to-forget bookkeeping steps: confirming the quality gate passed, ensuring all work is committed, archiving finished tasks, and writing a session journal entry. This Skill standardizes that wrap-up so project history stays consistent and no completed task is left unarchived. ## Core Features & Use Cases - State survey: Runs get_context.py in record mode to list active tasks, git status, and recent commits, surfacing other completed tasks for optional batch archiving. - Clean-tree safety check: Verifies git status is clean (excluding .trellis/workspace and .trellis/tasks paths) and stops with a clear message if uncommitted code remains, directing the user back to the commit phase. - Task archiving and journaling: Archives the active task via task.py (producing chore(task) commits) and records a session journal with add_session.py, linking work commit hashes to a title and summary. - Use Case: After finishing a feature and committing the code, invoke this Skill to archive the task, log the session with its commit hashes, and leave the repository in a clean, well-documented state. ## Quick Start Ask the AI to finish the work session by archiving the current task and recording the session journal with the recent commit hashes.
