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fleet-memory-manager车队内存管理器

Agent Skill

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。

总安装

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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

MIT-0

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: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

简介

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。

SKILL.md

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

适合场景

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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

补充不同宿主或平台的使用分布数据

能力 5

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。

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安装前确认

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