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Agent Skill · 效率

fleet-memory-manager(车队内存管理器)

fleet-memory-manager 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

fleet-memory-manager 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描有提醒项,按安装量在效率类的 21,003 个 Skill 里排第 8,324。

总安装 7,213周安装 289GitHub Stars 公开资料未说明下载 2,335核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:fleet-memory-manager(车队内存管理器)
来源仓库:https://github.com/vswarm-ai/fleet-memory-manager
安装命令:
openclaw skills install fleet-memory-manager
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install fleet-memory-manager

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

将座席记忆升级为具备夜间整合功能的 3 层生产系统。基于运行七个 AI 机器人的实战经验优化长期记忆机制。适用于需要持续学习与上下文保持的高级对话代理场景。fleet-memory-manager 属于效率类 Skill,可作为该场景下的辅助能力补充。夜间整合过程可能消耗较多计算资源需合理安排时间窗口。

建议初期采用小样本测试验证稳定性后再全面铺开使用。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install fleet-memory-manager;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

fleet-memory-manager 怎么安装?

在终端执行 openclaw skills install fleet-memory-manager。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

fleet-memory-manager 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

fleet-memory-manager 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

fleet-memory-manager 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

fleet-memory-manager 用的人多吗?

公开数据是累计安装 7,213 次,近一周安装 289 次,下载 2,335 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

fleet-memory-manager 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
fleet-memory-manager

车队内存管理器 · 本页

7,213—接触敏感数据MIT-0有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
memory-manager
description
Upgrade your agent's memory from basic notes to a 3-layer production system with nightly consolidation. Based on patterns from running 7 AI bots in production for 30+ days.

memory-manager

Upgrade your agent's memory from basic notes to a 3-layer production system with nightly consolidation. Based on patterns from running 7 AI bots in production for 30+ days.


Overview

Every AI agent has the same problem: it wakes up fresh every session with no memory of what happened before. The naive fix is a single MEMORY.md file — but that doesn't scale. After a few weeks, it's either a wall of text the agent ignores, or so curated it's missing operational context.

This skill installs a 3-layer memory architecture that mirrors how humans actually store knowledge:

LayerFileWhat goes here
1 — Long-termMEMORY.mdCurated wisdom, architecture decisions, hard-won lessons
2 — Operationalmemory/YYYY-MM-DD.mdWhat happened today, active project state, raw context
3 — TacitUSER.mdHow your human works, preferences, frustrations, patterns

Plus a nightly consolidation cron that reviews recent sessions and promotes important context up the layers automatically.


When to Use This Skill

Activate this skill when the user asks you to:

  • Set up memory for their agent
  • Upgrade from a basic MEMORY.md system
  • Add nightly consolidation or memory cron
  • Improve agent continuity between sessions
  • Track active projects across agent restarts
  • Set up the memory-manager skill

Setup Instructions

Step 1: Run the Setup Script

bash ~/.openclaw/skills/memory-manager/scripts/setup.sh

This creates the memory/ directory, copies templates into place, and prints next steps.

Step 2: Customize the Templates

After setup, edit these files in your agent's workspace:

  1. MEMORY.md — Add your agent's existing long-term context
  2. USER.md — Fill in who the human is, how they work, what frustrates them
  3. AGENTS.md — Review the startup sequence (already wired for 3-layer loading)
  4. HEARTBEAT.md — Configure which projects to monitor

Step 3: Configure the Startup Sequence

Your agent's AGENTS.md must include this memory loading sequence at the top of "Every Session":

## Every Session

Before doing anything else:
1. Read `SOUL.md` — identity and persona
2. Read `USER.md` — who you're helping and how they work  
3. Read `memory/YYYY-MM-DD.md` (today) — what happened today
4. Read `memory/YYYY-MM-DD.md` (yesterday) — recent context bridge
5. **If in MAIN SESSION** (direct chat with your human): Also read `MEMORY.md`
Why read yesterday too? Sessions started after midnight won't have today's file yet. Yesterday bridges the gap. This prevented context loss in our production fleet during late-night sessions.

Step 4: Set Up Nightly Consolidation

Add a cron job to consolidate memory each night at 2 AM:

0 2 * * * openclaw cron run memory-consolidation --model anthropic/claude-opus-4-5 --channel <your-main-channel-id>

The consolidation prompt to configure in OpenClaw cron:

You are performing nightly memory consolidation for this agent.

Tasks:
1. Read memory/YYYY-MM-DD.md files from the last 7 days
2. Read the current MEMORY.md
3. Identify: significant decisions, lessons learned, architecture changes, resolved issues, evolving patterns
4. Update MEMORY.md with distilled insights (add new, update stale, remove obsolete)
5. Check USER.md — update any new preferences or patterns you observed
6. Write a brief summary of what you consolidated to memory/consolidation-log.md

Be selective. MEMORY.md should stay under 500 lines. Quality over quantity.
Signal completion: reply "CONSOLIDATION_COMPLETE" to the channel when done.
Why 2 AM? Low activity period. The consolidation model has full context of the day's events. Running nightly (not weekly) means no single consolidation is overwhelming.

Memory Loading Rules

In Main Session (direct human chat)

Load all three layers:

SOUL.md → USER.md → memory/today.md → memory/yesterday.md → MEMORY.md

In Group Chats / Shared Channels

Load only layers 2 and 3 (no MEMORY.md):

SOUL.md → USER.md → memory/today.md → memory/yesterday.md
Why skip MEMORY.md in group chats? Long-term memory often contains personal context — private preferences, health info, financial details — that shouldn't leak into conversations with strangers. Daily operational notes are usually safe.

In Subagent / Worker Sessions

Load only today's notes:

memory/today.md (if relevant to task)

Subagents are ephemeral. Don't load full memory — it wastes tokens and context.


Daily Notes Format

Each memory/YYYY-MM-DD.md file follows this structure:

# YYYY-MM-DD

## Sessions

### [Time] — Session summary
- What happened
- Decisions made
- Tasks completed / in progress

## Active Projects

### Project Name
- **Status:** In Progress / Blocked / Complete
- **Last action:** What was done last
- **Next:** What needs to happen next
- **Blockers:** Anything blocking progress

## Context for Next Session

Key things future-me needs to know to pick up without re-explaining:
- [item 1]
- [item 2]

## Raw Log

(Less curated — dump things here that might matter)
The "Context for Next Session" section is the most important. Agents often end sessions mid-task. Without this section, the next session has to reconstruct state from scratch. Write it as if briefing a colleague who just joined the project.

Active Project Tracking

Projects move through these states in daily notes:

PLANNING → IN_PROGRESS → BLOCKED → REVIEW → COMPLETE

The heartbeat integration (see HEARTBEAT.md) checks active projects and surfaces blockers automatically.


MEMORY.md Curation Rules

Long-term memory should be:

  • Curated, not comprehensive — the distilled essence, not raw logs
  • Actionable — things that change future decisions
  • Evergreen — not "what I did Tuesday" but "lesson learned from the Tuesday incident"
  • Organized by topic — architecture, lessons, human preferences, recurring patterns

Things that belong in MEMORY.md:

  • Architecture decisions and the reasoning behind them
  • Lessons learned from failures
  • Patterns in how the human works / thinks
  • Important context about key projects
  • Things you've been told to always/never do

Things that do NOT belong in MEMORY.md:

  • One-off task completions
  • Information that will be stale in a week
  • Raw conversation transcripts
  • Things already captured in USER.md

Heartbeat Integration

Add to your HEARTBEAT.md to enable project monitoring:

## Active Project Check

For each project in active_projects.json (if it exists):
1. Check last updated timestamp
2. If project hasn't been touched in >48h, surface it: "⚠️ [Project] hasn't been updated in X days"
3. If status is BLOCKED, surface blocker to human
4. If status is COMPLETE but not archived, prompt to archive

## Memory Health Check (weekly, Sundays)

1. Check MEMORY.md line count — if >500 lines, flag for pruning
2. Check memory/ folder — if daily files >30 days old exist, flag for archiving
3. Report: X daily files, MEMORY.md is X lines, last consolidation: [date]

File Reference

FileLocationPurpose
SKILL.md~/.openclaw/skills/memory-manager/This file
setup.shscripts/setup.shOne-command installer
templates/MEMORY.mdtemplates/Long-term memory template
templates/AGENTS.mdtemplates/Startup sequence template
templates/USER.mdtemplates/User profile template
templates/HEARTBEAT.mdtemplates/Heartbeat config template

平台分布

OpenClaw

87.82%
按下载量换算2,051

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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