research-memory-cleanup

Consolidating duplicate papers involves backing up your memory, running the memory-subagent cleanup workflow to merge scattered paper entries into canonical records, and restoring the deduplicated result. The Skill automates this 3-step process with rollback support to ensure safe consolidation across your research domains.

Yes. The Skill organizes scattered notes into clearly defined research domains while maintaining data integrity through explicit backup and rollback capability. The deterministic workflow ensures you can restore your original memory if needed before applying domain organization.

Use the 3-step backup-cleanup-restore workflow. First backup your current memory, then spawn a memory-subagent to trim discovery configs and remove redundancy, finally restore the cleaned memory. This auditable approach lets you roll back if the cleanup removes data you need.

The Skill applies deterministic deduplication and cleanup to large research memories spanning multiple domains. It consolidates citation networks and discovery configs while preserving domain structure, using the memory-subagent to process scattered notes and redundant entries systematically.

No external dependencies are required. You need access to your agent ID and a backup directory. The Skill uses built-in scripts and a memory-subagent for cleanup, making it portable across research environments without additional tools or configuration.

Manual organization is time-consuming and error-prone at scale. Deduplication automatically consolidates redundant paper entries, removes outdated discovery configs, and organizes notes deterministically, freeing you to focus on research rather than memory maintenance.