memory-manager

Name: memory-manager
Availability: InStock
Author: tiankong0101-byte

Store, retrieve, and organize agent memories with metadata and namespaces.

Updated May 17, 2026

Search Tags:#knowledge management #semantic search #retrieval #memory #agent memory #context storage

Ready to run

npx skills add https://github.com/tiankong0101-byte/skills-registry --skill memory-manager-tiankong0101-byte

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: memory-manager
Source: https://github.com/tiankong0101-byte/skills-registry/tree/main/skills/memory-manager
Command: npx skills add https://github.com/tiankong0101-byte/skills-registry --skill memory-manager-tiankong0101-byte

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps agents reliably store, retrieve, and organize knowledge so important context is not lost between tasks, sessions, or conversations.

Core Features & Use Cases

Memory Storage: Save structured or unstructured information with metadata for later use.
Context Retrieval: Find relevant memories using semantic similarity or keywords.
Knowledge Management: Organize memories by namespace, topic, time, or relevance, and update, delete, export, or import them as needed.
Use Case: If an agent needs to remember user preferences, project decisions, or prior reasoning, this Skill provides a centralized memory layer to keep that information accessible.

Quick Start

Use the memory-manager skill to store this conversation summary with metadata for future retrieval.

Frequently Asked Questions about memory-manager

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

FAQPage Schema

How do I store and retrieve agent memory for persistent context across sessions?▼

Agent memory storage allows you to save structured or unstructured information with metadata, then retrieve relevant context later using semantic similarity or keywords across different sessions.

What is semantic search for agent memory and when do I need it?▼

Semantic search for agent memory finds relevant stored context using meaning rather than exact keywords. You need it when recalling user preferences, project decisions, or prior reasoning across conversational turns.

How do I organize knowledge base memories by namespace and topic?▼

You organize knowledge base memories by namespace, topic, time, or relevance. This allows structured memory operations including updating, deleting, importing, or exporting snapshots for contextual reuse.

Do I need configured storage support to manage agent context lifecycle operations?▼

Yes, managing agent context lifecycle operations requires local or configured storage support. This backend enables structured memory operations, namespace management, and snapshot import or export functionality.

Can I export and import memory snapshots for knowledge management workflows?▼

Yes, you can export and import memory snapshots. This knowledge management feature allows you to transfer stored context, metadata, and namespace configurations between different environments or backup sessions.

What's the best way to track user preferences with a centralized memory layer?▼

Using a centralized memory layer to track user preferences involves saving the information with metadata during interactions, then retrieving it via semantic lookup workflows for personalized agent responses.