record-session

You can record a git session summary to a journal by triggering the record-session workflow, which persists session summaries, commit hashes, and developer index updates into .trellis/workspace files after you have finished testing and committing code.

Preserving AI context across coding sessions involves recording completed work progress to journal files. This skill captures session summaries and commit hashes, creating a readable record that can be loaded into future AI tasks.

Session journaling integrates with the .trellis workspace tooling by running Python scripts that manage context extraction, automate archive decisions, and update developer index files to maintain continuity across tasks.

You should run a session recording workflow at the end of your development cycle, specifically after a feature is completed, human testing is finished, and code changes are committed, to ensure session knowledge is persisted for future AI sessions.

Session recording does not require manual entry of commit hashes and context summaries. The workflow automatically extracts context, captures commit hashes, and updates developer index files after the human commits the code.

Yes, you can use session journaling to automate archive decisions for completed tasks. The skill integrates with .trellis tooling to manage context extraction and maintain continuity, automatically preserving work progress for future reference.