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memory-cleanup

Consolidate MEMORY.md files by detecting duplicates, resolving contradictions, and generating abstractions.

127|22|Updated Feb 20, 2026
Search Tags:#research#knowledge base#memory management#abstraction#consolidation
One-click install
npx skills add https://github.com/flonat/flonat-research --skill memory-cleanup-flonat
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-cleanup
Source: https://github.com/flonat/flonat-research/tree/main/skills/memory-cleanup
Command: npx skills add https://github.com/flonat/flonat-research --skill memory-cleanup-flonat

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill helps researchers manage and refine their knowledge base by pruning duplicates, merging overlapping entries, and generating higher-order abstractions from accumulated patterns.

Core Features & Use Cases

  • Duplicate Detection and Resolution: Identifies and merges duplicate entries in MEMORY.md files.
  • Contradiction Resolution: Resolves contradictions between entries.
  • Staleness Detection: Flags and removes outdated entries.
  • Tier Routing Check: Moves entries between personal memory and project memory.
  • Abstraction Generation: Generates higher-order patterns from accumulated entries.
  • Memory Consolidation: Consolidates memory across projects and personal memory files.
  • Propagation to Shared Auto-Memory: Updates shared memory locations with changes.

Quick Start

Run the memory-cleanup skill with the 'project' mode to consolidate the MEMORY.md file for the current project.

Frequently Asked Questions about memory-cleanup

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I consolidate a research knowledge base to remove duplicate entries?▼

Consolidate a research knowledge base by detecting and merging duplicate entries within MEMORY.md files. This process prunes overlapping records and refines the accumulated knowledge to maintain accuracy.

What is the best way to resolve contradictions in memory management files?▼

Resolving contradictions in memory management involves analyzing MEMORY.md files to identify conflicting records and merging them. This ensures the research knowledge base remains internally consistent.

Do I need Python to detect staleness and generate abstractions in MEMORY.md files?▼

Yes, you need Python installed to detect staleness and generate abstractions in MEMORY.md files. The Skill relies on Python for executing scripts and manipulating memory files during consolidation.

Can I generate higher-order abstractions from accumulated research patterns?▼

Yes, you can generate higher-order abstractions from accumulated research patterns. The consolidation process identifies recurring themes in MEMORY.md files and synthesizes them into generalized knowledge entries.

How does memory consolidation handle project-specific versus global knowledge bases?▼

Memory consolidation handles both project-specific and global knowledge bases by routing entries between personal memory and project memory files. It propagates updates to shared locations to maintain consistency.

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