How is performance optimized for large datasets?

It uses smart indexing, automatic compression for large entries, and periodic garbage collection for expired data to maintain fast search and retrieval speeds.

Does it support data security?

Yes, the coordinator includes security features such as encryption at rest and access control lists to protect sensitive project information and configuration data.

What is the Agent Memory Coordinator?

It is a Claude Code skill that manages a distributed memory system, allowing AI agents to store and retrieve information across different sessions and collaborate more effectively.

How does namespace management work?

The skill organizes memory into distinct namespaces like project-specific, agent-specific, or shared spaces, preventing data collisions and ensuring secure access boundaries.

Agent Memory Coordinator

Name: Agent Memory Coordinator
Author: nbossn

bynbossn

0•

생산성 및 워크플로

Manages persistent cross-session memory and facilitates seamless information sharing between multiple AI agents.

The Agent Memory Coordinator is a sophisticated management layer designed to solve the challenge of context loss in AI workflows by providing a centralized, persistent memory system. It organizes data into logical namespaces—such as project-specific, agent-specific, or shared collaboration spaces—ensuring that architectural decisions, API contracts, and task states remain available across different sessions. By implementing features like data compression, smart indexing, and TTL-based cleanup, it optimizes information retrieval and prevents context drift, making it an essential tool for complex, multi-agent development environments and long-term project maintenance.

주요 기능

01Hierarchical namespace management for project, agent, and shared memory

02Automatic data optimization including compression and deduplication

03Synchronized memory sharing for collaborative agent workflows

04Smart search and semantic retrieval for fast context recovery

050 GitHub stars

06Cross-session data persistence with optional TTL and encryption

사용 사례

01Storing and retrieving reusable design patterns and historical optimization techniques

02Maintaining long-term architectural decisions and project context across multiple coding sessions

03Coordinating state and task progress between different AI agents in a swarm architecture

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add nbossn/claude-code-base agent-memory-coordinator

For use in Claude.ai and ChatGPT

주요 기능

01Hierarchical namespace management for project, agent, and shared memory

02Automatic data optimization including compression and deduplication

03Synchronized memory sharing for collaborative agent workflows

04Smart search and semantic retrieval for fast context recovery

050 GitHub stars

06Cross-session data persistence with optional TTL and encryption

사용 사례

01Storing and retrieving reusable design patterns and historical optimization techniques

02Maintaining long-term architectural decisions and project context across multiple coding sessions

03Coordinating state and task progress between different AI agents in a swarm architecture