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memory-manager

Parse, classify, route, and save conversational memory chunks to a persistent store.

1|Updated Mar 11, 2025
Search Tags:#agent orchestration#memory#data management#conversation#storage
One-click install
npx skills add https://github.com/danielstewart77/hive_mind --skill memory-manager-danielstewart77
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: memory-manager
Source: https://github.com/danielstewart77/hive_mind/tree/main/specs/skills/memory-manager
Command: npx skills add https://github.com/danielstewart77/hive_mind --skill memory-manager-danielstewart77

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill manages the complete process of storing conversational memories, ensuring that important information is captured and retained effectively.

Core Features & Use Cases

  • Automated Memory Storage: Automatically saves conversation transcripts when a new session begins.
  • Manual Memory Storage: Allows users to explicitly request that specific information or entire threads be remembered.
  • Sequential Agent Execution: Orchestrates a series of sub-agents (parse, classify, route, save) to handle memory storage in a structured manner.
  • Use Case: After a long discussion about project requirements, you can tell Ada "remember this" and she will use the memory manager to store the key decisions and action items for future reference.

Quick Start

Use the memory manager to remember the key points from our last conversation.

Frequently Asked Questions about memory-manager

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

FAQPage Schema
How do I save conversational memories for AI agents automatically?▼

Conversational memory storage is automated by triggering sub-agents on new session starts to parse, classify, route, and save transcripts to a persistent store.

Can I manually tell my conversational AI to remember specific information?▼

Manual memory storage is supported by triggering the orchestrator via user commands like "remember this," which executes sub-agents to parse and save targeted conversation chunks.

How does agent orchestration work for data management and memory storage?▼

Agent orchestration for memory storage works by executing a structured sequence of sub-agents responsible for parsing, classification, routing, and saving memory chunks sequentially.

What is the best way to retain key decisions from a long conversation thread?▼

Retaining key decisions from conversation threads is best handled by manually prompting the AI to remember the discussion, triggering memory parsing and routing sub-agents for persistent storage.

Do I need any external dependencies to manage memory storage lifecycle?▼

Managing the memory storage lifecycle requires no external dependencies, as the orchestrator operates independently to parse, classify, route, and save conversational data chunks.

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