mvt-manage-context

You can manage AI project context files through a unified CRUD workflow that controls adding, moving, renaming, and removing knowledge entries while keeping registry references consistent across shared, project-specific, and per-skill stores.

YAML-driven knowledge routing scores relevance across registered AI skills so context files are attached only to the appropriate consumers, preventing unnecessary loading of unrelated project knowledge across your entire registry.

The safest way to rename or move context files is through atomic updates that modify both the file and its registry bindings simultaneously, utilizing built-in backup and rollback behavior to prevent broken references.

Yes, this knowledge management workflow requires organizing context files under a .ai-agents directory, separating entries into shared, project-specific, per-skill, and core context stores for proper validation and routing.

Yes, the workflow includes edge-case validation for managed knowledge paths, ensuring that routing instructions and registry bindings remain accurate before any atomic file updates or skill relevance scoring occurs.

If a context file update breaks registry bindings, the system provides rollback safety behavior that restores the previous state using backups created during the atomic update process for your managed knowledge paths.