Token导航 LogoToken导航TokenDH.com
中转站排行榜
效率只读clawhub未标认证来源可访问clear审计通过

memory-system-sidecar（内存系统边车）

Agent Skill

memory-system-sidecar 用于辅助前端页面、组件、样式和交互逻辑开发，适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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

4,412

周安装

182

GitHub Stars

公开资料未说明

下载量

1,441
OpenClaw

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：memory-system-sidecar（内存系统边车）
来源仓库：https://github.com/sjingh/memory-system-sidecar
安装命令：
openclaw skills install memory-system-sidecar
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 memory-system-sidecar

简介

操作、验证、重建和调试已实施的 MemoryLab 长期内存 sidecar，提供活动任务和实时上下文文件。

SKILL.md

name
memory-system-sidecar
description
Operate, verify, rebuild, and debug the actual MemoryLab long-term memory sidecar that feeds memory/ACTIVE_TASK_STATE.md and memory/LIVE_CONTEXT_PACKET.md. Use when working on this repo’s implemented memory system: refreshing from session history, rebuilding indexes, running evals/tests, auditing milestone status, checking contamination boundaries, or inspecting memory artifacts under memory-system/, memory/, history/, and scripts/context-refresh*.

Memory System Sidecar

Use this skill for the implemented MemoryLab memory system, not just abstract planning.

The system boundary is:

  • Context manager = hot-path compactor
  • Memory sidecar = long-term extraction, indexing, retrieval, consolidation
  • Bridge = feeds retrieved memory back into ACTIVE_TASK_STATE / LIVE_CONTEXT_PACKET without treating them as source of truth

Quick workflow

Choose the smallest workflow that matches the task.

1. Refresh live context + sidecar from a real session

Use when the user says things like:

  • "refresh memory"
  • "rebuild context from the laptop session"
  • "update the live packet from the current session"

Run:

./skills/memory-system-sidecar/scripts/refresh_memory_system.sh

This wraps the repo’s standard end-to-end refresh path.

2. Verify the memory system still passes

Use when the user asks:

  • "is the memory system working?"
  • "does milestone 5 still hold?"
  • "run the checks"

Run:

./skills/memory-system-sidecar/scripts/verify_memory_system.sh

This runs the main unit tests plus the eval harness.

3. Rebuild indexes only

Use when eval/retrieval drifts or docs mention stale-index behavior.

Run:

./skills/memory-system-sidecar/scripts/rebuild_memory_indexes.sh

Then rerun verify.

Operating rules

  • Treat raw history / transcripts as source of truth.
  • Treat memory/LIVE_CONTEXT_PACKET.md as working memory, not durable storage.
  • Do not treat retrieved-memory injection as new durable truth.
  • Prefer repo wrappers (scripts/context-refresh*) over ad-hoc manual command chains.
  • When status docs and runtime disagree, trust runtime checks after rebuild.

Read these references when needed

  • references/commands.md — exact command map for refresh / rebuild / verify / inspect
  • references/docs-map.md — which doc is design vs status vs restore vs checklist

Common files to inspect

  • memory-system/MILESTONE_STATUS.md
  • docs/designs/MEMORYLAB_MEMORY_SYSTEM_MILESTONE_RESTORE.md
  • docs/designs/MEMORYLAB_MEMORY_SYSTEM_BLUEPRINT.md
  • memory/ACTIVE_TASK_STATE.md
  • memory/LIVE_CONTEXT_PACKET.md
  • memory/RETRIEVAL_CONTEXT_BUNDLE.json
  • history/transcripts/*.md

Default debug order

When output looks wrong, inspect in this order:

  1. memory/ACTIVE_TASK_STATE.md
  2. memory/LIVE_CONTEXT_PACKET.md
  3. memory/RETRIEVAL_CONTEXT_BUNDLE.json
  4. history/transcripts/*.md
  5. memory-system/index/memory.db freshness / rebuild state

Compatibility rule

This skill operates the real sidecar already implemented in this repo. It should complement:

  • context-manager
  • live-context-management
  • long-term-memory

Use this skill when the task is about running or auditing the built system, not just designing one.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

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。

平台分布

OpenClaw

91.5%
按下载量换算1,319

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容，本身偏只读；真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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

GitHub 仓库

github.com

/sjingh/memory-system-sidecar

SKILL.md 来源

clawhub.ai

/sjingh/memory-system-sidecar

继续浏览同类 Skills

更多效率 Skills（21,003）返回 Skills 目录

上一个 Skill

memory-system-optimizer（内存系统优化器）

memory-system-optimizer 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。

下一个 Skill

memory-taxonomist-clarkchenkai（记忆分类学家克拉克琴凯）

memory-taxonomist-clarkchenkai 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。