housekeeping-review

Automated pruning of old backups and outdated files is handled by executing shell and Python scripts that identify stale metadata and manage cleanup candidates for deletion. This streamlines housekeeping operations by truncating or deleting obsolete project data.

The approval process for cleanup candidates works by scanning and classifying outdated files, then posting them to a Slack channel for explicit review. No deletion actions occur until explicit approval is granted for the identified candidates.

Yes, you need bash and Python installed to execute the automated file cleanup workflows. The Skill relies on a shell script for pruning operations and a Python script for rendering cleanup candidates and posting them to Slack.

Identifying and classifying stale files for data lifecycle management is best achieved by scanning project directories for cleanup candidates. The Skill evaluates outdated files and stale metadata, preparing them for an explicit approval workflow before deletion.

Yes, you can post cleanup candidates directly to a Slack channel for review. The workflow uses a Python script to render identified pruning candidates and sends them to Slack, facilitating an explicit approval process before any files are deleted.

You should not use an automated housekeeping script for project directories if your files lack clear age or staleness metadata for classification, or if your environment cannot support the required bash and Python dependencies for Slack integration.