memory-consolidation

Name: memory-consolidation
Availability: InStock
Author: Heretek-AI

Consolidate episodic memories into semantic storage and archive outdated data.

Updated Mar 22, 2026

Search Tags:#automation #memory #semantic #consolidation #knowledge-graph #data-management #episodic

Ready to run

npx skills add https://github.com/Heretek-AI/heretek-openclaw --skill memory-consolidation-heretek-ai

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: memory-consolidation
Source: https://github.com/Heretek-AI/heretek-openclaw/tree/main/skills/memory-consolidation
Command: npx skills add https://github.com/Heretek-AI/heretek-openclaw --skill memory-consolidation-heretek-ai

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Maintains a healthy memory system by reviewing, organizing, and promoting episodic memories into semantic storage while archiving outdated information to prevent clutter and drift.

Core Features & Use Cases

Consolidation phases: review, promote, archive, decay, and health reporting to keep the memory store efficient and coherent.
Configurable policies: thresholds, ages, and decay rates to balance recency and long-term retention.
Use Case: perform periodic health checks and automated memory hygiene across agent workspaces and the knowledge graph.

Quick Start

Execute the memory-consolidation.sh consolidate command to start a full memory health cycle.

Frequently Asked Questions about memory-consolidation

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

FAQPage Schema

How do I consolidate episodic memories into a semantic knowledge graph?▼

Consolidating episodic memories into semantic storage involves running review, promote, and archive phases that organize episodic data into long-term knowledge while archiving outdated information to prevent clutter and drift.

What is the best way to automate memory maintenance across agent workspaces?▼

Automating memory maintenance across agent workspaces is achieved by executing periodic health checks and consolidation cycles that review, promote, archive, and decay episodic data based on configurable age thresholds and decay policies.

How does memory decay and aging policy work for semantic storage?▼

Memory decay and aging policies apply configurable thresholds and decay rates to balance recency against long-term retention, automatically archiving outdated episodic memories while promoting stable data into semantic storage.

Can I configure custom thresholds for episodic memory promotion?▼

You can configure custom thresholds, ages, and decay rates to define when episodic memories are promoted to semantic storage or archived, allowing you to balance recency and long-term retention within your agent workspaces.

How do I run a full memory health cycle from the CLI?▼

Running a full memory health cycle from the CLI requires executing the memory-consolidation consolidate command, which triggers the complete review, promote, archive, and decay workflow to clean and optimize the memory store.

When should I archive outdated memories to prevent knowledge graph drift?▼

You should archive outdated memories during periodic health checks when episodic data exceeds configured age thresholds, preventing knowledge graph drift and maintaining coherent semantic storage across agent workspaces.