Token导航 LogoToken导航

Agent Skill · 研究检索

agent-memory-sr(Agent 记忆 SR)

agent-memory-sr 用于查找、检索和筛选相关信息,适合在 OpenClaw 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。

agent-memory-sr 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 13,136。

总安装 9,648周安装 398GitHub Stars 公开资料未说明下载 3,152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:agent-memory-sr(Agent 记忆 SR)
来源仓库:https://github.com/theshadowrose/agent-memory-sr
安装命令:
openclaw skills install agent-memory-sr
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 agent-memory-sr

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

防止代理遗忘会话间信息,采用三层架构保障上下文连续性。适合多会话切换频繁、需保持角色一致性的协作型代理任务。支持命名空间隔离与日志回溯,提升长期交互的可靠性。安装命令:openclaw skills install agent-memory-sr;建议测试边界情况。注意可能增加存储负载,需监控磁盘使用与响应延迟变化。

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 agent-memory-sr;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

    它需要需要联网,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

agent-memory-sr 怎么安装?

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

agent-memory-sr 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。

agent-memory-sr 需要什么权限?

权限级别是需要联网。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。

agent-memory-sr 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。

agent-memory-sr 用的人多吗?

公开数据是累计安装 9,648 次,近一周安装 398 次,下载 3,152 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。

agent-memory-sr 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

  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agent-memory-sr

Agent 记忆 SR · 本页

9,648—需要联网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
Agent Memory — Persistent Workspace Memory System
description
Stop your AI agent from forgetting everything between sessions. Three-tier memory architecture (long-term owner namespace / daily logs / session handoff), cross-channel isolation so group chats never contaminate private sessions, and MASTER_MAP navigation. One command sets up the complete structure.
author
@TheShadowRose
version
1.0.0
tags
["memory", "persistence", "agent", "workspace", "context", "continuity", "openclaw"]
license
MIT

Agent Memory — Persistent Workspace Memory System

Stop your AI agent from forgetting everything between sessions.


The Problem

Every new session your agent starts from zero. Same explanations. Same context. Same mistakes. Same questions you've already answered.

The agent isn't broken — it just has no memory. This fixes that.


What It Does

One command creates a complete memory structure your agent loads at the start of every session:

FilePurpose
AGENTS.mdWorkspace identity — who the agent is, what rules it follows
USER.mdUser profile — who you are, your preferences, what the agent should always know
MASTER_MAP.mdNavigation index — what's where without loading everything
MEMORY.mdLong-term curated memory — the distilled essence, not raw logs
HEARTBEAT.mdPeriodic check checklist — what to monitor between sessions
HANDOFF.mdSession continuity — write at end of mid-task sessions, read first next session
memory/YYYY-MM-DD.mdDaily logs — raw session notes, auto-created each day

Quick Start

New here? Start with QUICKSTART.md — 5 steps, 20 minutes, persistent memory running.

# Interactive setup (prompts for names and timezone)
python3 init_memory.py

# One-liner with all options
python3 init_memory.py --workspace /path/to/workspace --agent "Assistant" --user "Alice" --timezone "America/New_York"

# Non-interactive with defaults
python3 init_memory.py --non-interactive --workspace .

Then add this to your agent's system prompt:

Before each session:
1. Check HANDOFF.md — if it has content, read it first and follow it, then clear it
2. Read AGENTS.md
3. Read USER.md
4. Read memory/YYYY-MM-DD.md (today's date)
5. Read MASTER_MAP.md
6. Read MEMORY.md (main sessions with your human only)

At end of any mid-task session: fill in HANDOFF.md before closing.

That's it. Your agent now has persistent memory.


How It Works

The init script creates template files in your workspace. You customize them once. Your agent reads them every session.

The key insight: AI agents don't forget because they're bad at remembering — they forget because nobody told them what to remember or where to find it. These files are the instruction set for memory.

MASTER_MAP.md — The Navigation Index

The most important file. A lean table of contents that tells the agent what exists and where — without loading every file. Under 200 lines by design.

## ACTIVE PROJECTS
| Project | Status | Key File | Notes |
|---------|--------|----------|-------|
| API integration | In progress | `src/api.py` | Auth blocked |
| Documentation | Done | `docs/` | |

Agent reads this → knows exactly what to load → loads only what's needed.

MEMORY.md — Long-Term Memory

The curated memory layer. Agent updates this over time with:

  • Decisions made and why
  • Things to always remember
  • Patterns discovered
  • Lessons learned

Not a raw log — a distilled summary. Load only in direct sessions with your human (not group chats or shared contexts).

HANDOFF.md — Session Continuity

The feature MEMORY.md can't cover: picking up exactly where you left off.

Write HANDOFF.md at the end of any session where work is mid-task. The next session reads it first — before anything else — and picks up exactly there. Then clears it.

HANDOFF.md structure:
- Where we left off (1-2 sentences)
- What's in progress (half-done work)
- Next actions in order
- Open questions needing a decision
- Context that won't survive the session break
- Files changed this session

When to write it: Any session where you're mid-task and want to resume without re-briefing. When to skip it: Completed sessions. Casual conversations. Anything that doesn't need continuity.

MEMORY.md is for long-term knowledge. Daily logs are raw notes. HANDOFF.md is for "resume exactly here tomorrow."

Daily Logs — Raw Session Notes

memory/YYYY-MM-DD.md captures everything from a session in raw form. Agent reads today's log at startup for continuity. After sessions accumulate, periodically consolidate the best insights into MEMORY.md.

AGENTS.md — Workspace Rules

Where the agent's behavioral conventions live. Not a system prompt replacement — a supplement. Add:

  • How to handle specific situations
  • Standing permissions
  • Conventions for this workspace
  • What to do at session start/end

Customization

After init_memory.py runs, open each file and fill in the blanks:

USER.md — The most important to fill in. Who are you? What are you working on? What should the agent always know? What drives you crazy when agents do it?

AGENTS.md — What rules should this agent follow? What's off-limits? How should it communicate?

MASTER_MAP.md — Add your projects and systems as you build them. Update it whenever something significant is added.

HEARTBEAT.md — If your agent runs heartbeats (periodic background checks), put the checklist here.


Integration Examples

OpenClaw

Add to your agent's system prompt or AGENTS.md:

Every session: Read AGENTS.md → USER.md → memory/{today}.md → MASTER_MAP.md → MEMORY.md (if main session)

Any File-Based Agent

The memory system works with any agent that can read files — OpenClaw, AutoGPT, CrewAI, custom implementations. The pattern is framework-agnostic.


What's Included

FilePurpose
QUICKSTART.mdStart here — 5-step setup guide, 20 minutes
init_memory.pySetup script — creates all files and directories
templates/AGENTS.md.templateWorkspace rules + channel isolation
templates/MEMORY.md.templateLong-term memory index
templates/USER.md.templateUser profile
templates/MASTER_MAP.md.templateNavigation index
templates/HEARTBEAT.md.templatePeriodic check checklist
templates/HANDOFF.md.templateSession continuity
templates/owner/identity.mdUser + agent identity
templates/owner/preferences.mdCommunication style and preferences
templates/owner/decisions.mdImportant choices + rationale
templates/owner/learnings.mdLessons learned and patterns
templates/owner/people.mdTrusted users and relationships
templates/owner/projects.mdActive and completed work
LIMITATIONS.mdWhat this tool doesn't do

Requirements

  • Python 3.7+
  • No external dependencies (stdlib only)
  • Works on any OS
  • Works with any file-based AI agent

⚠️ Security Note

This skill creates files in your workspace. All files are plain Markdown — no code execution, no network calls, no external dependencies. The init script reads template files from the templates/ directory and writes Markdown to your workspace.

Config is JSON format. No Python config execution.


License

MIT — See LICENSE.md

Author: Shadow Rose


Why This Exists

An AI agent with no memory is a tool. An AI agent with structured persistent memory is a system. The difference between an agent that needs to be re-briefed every session and one that already knows the context is entirely this file structure.

Built from production use — this is the exact pattern running in our own agents.

Collaboration: Owner namespace architecture and cross-channel isolation contributed by Yesterday (Yesterday AI) and Halthasar. The three-tier memory structure evolved from comparing both systems in production.


☕ If this helped: https://ko-fi.com/theshadowrose 🐦 Follow: https://x.com/TheShadowyRose


⚠️ Disclaimer

This software is provided "AS IS", without warranty of any kind, express or implied.

USE AT YOUR OWN RISK.

The author(s) are NOT liable for any damages, losses, or consequences arising from the use or misuse of this software.

By using this software, you acknowledge that you have read this disclaimer and agree to use the software entirely at your own risk.


Support & Links

🐛 Bug ReportsTheShadowyRose@proton.me
☕ Ko-fiko-fi.com/theshadowrose
🛒 Gumroadshadowyrose.gumroad.com
🐦 Twitter@TheShadowyRose

*Built with OpenClaw*

🛠️ Need something custom? Custom OpenClaw agents & skills starting at $500. → Hire me on Fiverr

平台分布

OpenClaw

81.35%
按下载量换算2,564

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

可疑

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。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。

继续浏览同类 Skills