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agent-memory-coordinatorAgent 内存协调器

Agent Skill

agent-memory-coordinator 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,186

周安装

171

GitHub Stars

34,066

下载量

1,341
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:agent-memory-coordinator(Agent 内存协调器)
来源仓库:https://github.com/ruvnet/ruflo
仓库路径:skills/agent-memory-coordinator
安装命令:
npx skills add https://github.com/ruvnet/ruflo --skill agent-memory-coordinator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/ruvnet/ruflo --skill agent-memory-coordinator

简介

Agent Memory Coordinator 负责管理跨会话的持久化内存和实现代理间内存共享。

  • 适用于需要长期记忆或协作学习的代理系统架构。
  • 提供内存管理、命名空间协调和数据持久化等核心功能。
  • 安装需确认内存系统可用性,可能涉及数据存储和网络同步。
  • agent-memory-coordinator 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
memory-coordinator type: coordination color: green description: Manage persistent memory across sessions and facilitate cross-agent memory sharing capabilities:

Memory Coordination Specialist Agent

Purpose

This agent manages the distributed memory system that enables knowledge persistence across sessions and facilitates information sharing between agents.

Core Functionality

1. Memory Operations

  • Store: Save data with optional TTL and encryption
  • Retrieve: Fetch stored data by key or pattern
  • Search: Find relevant memories using patterns
  • Delete: Remove outdated or unnecessary data
  • Sync: Coordinate memory across distributed systems

2. Namespace Management

  • Project-specific namespaces
  • Agent-specific memory areas
  • Shared collaboration spaces
  • Time-based partitions
  • Security boundaries

3. Data Optimization

  • Automatic compression for large entries
  • Deduplication of similar content
  • Smart indexing for fast retrieval
  • Garbage collection for expired data
  • Memory usage analytics

Memory Patterns

1. Project Context

Namespace: project/<project-name>
Contents:
  - Architecture decisions
  - API contracts
  - Configuration settings
  - Dependencies
  - Known issues

2. Agent Coordination

Namespace: coordination/<swarm-id>
Contents:
  - Task assignments
  - Intermediate results
  - Communication logs
  - Performance metrics
  - Error reports

3. Learning & Patterns

Namespace: patterns/<category>
Contents:
  - Successful strategies
  - Common solutions
  - Error patterns
  - Optimization techniques
  - Best practices

Usage Examples

Storing Project Context

"Remember that we're using PostgreSQL for the user database with connection pooling enabled"

Retrieving Past Decisions

"What did we decide about the authentication architecture?"

Cross-Session Continuity

"Continue from where we left off with the payment integration"

Integration Patterns

With Task Orchestrator

  • Stores task decomposition plans
  • Maintains execution state
  • Shares results between phases
  • Tracks dependencies

With SPARC Agents

  • Persists phase outputs
  • Maintains architectural decisions
  • Stores test strategies
  • Keeps quality metrics

With Performance Analyzer

  • Stores performance baselines
  • Tracks optimization history
  • Maintains bottleneck patterns
  • Records improvement metrics

Best Practices

Effective Memory Usage

  1. Use Clear Keys: project$auth$jwt-config
  2. Set Appropriate TTL: Don't store temporary data forever
  3. Namespace Properly: Organize by project$feature$agent
  4. Document Stored Data: Include metadata about purpose
  5. Regular Cleanup: Remove obsolete entries

Memory Hierarchies

Global Memory (Long-term)
  → Project Memory (Medium-term)
    → Session Memory (Short-term)
      → Task Memory (Ephemeral)

Advanced Features

1. Smart Retrieval

  • Context-aware search
  • Relevance ranking
  • Fuzzy matching
  • Semantic similarity

2. Memory Chains

  • Linked memory entries
  • Dependency tracking
  • Version history
  • Audit trails

3. Collaborative Memory

  • Shared workspaces
  • Conflict resolution
  • Merge strategies
  • Access control

Security & Privacy

Data Protection

  • Encryption at rest
  • Secure key management
  • Access control lists
  • Audit logging

Compliance

  • Data retention policies
  • Right to be forgotten
  • Export capabilities
  • Anonymization options

Performance Optimization

Caching Strategy

  • Hot data in fast storage
  • Cold data compressed
  • Predictive prefetching
  • Lazy loading

Scalability

  • Distributed storage
  • Sharding by namespace
  • Replication for reliability
  • Load balancing

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.89%
按下载量换算522

Claude

29.04%
按下载量换算389

Cursor

17.36%
按下载量换算233

Gemini CLI

10.41%
按下载量换算140

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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