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Agent Skill · 研究检索

jarvis-memory-architecture(贾维斯内存架构)

jarvis-memory-architecture 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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。

jarvis-memory-architecture 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 1,918。

总安装 72,397周安装 3,047GitHub Stars 7下载 25,351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:jarvis-memory-architecture(贾维斯内存架构)
来源仓库:https://github.com/psychotechv4/jarvis-memory-architecture
安装命令:
openclaw skills install jarvis-memory-architecture
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 jarvis-memory-architecture

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。

AI 代理的通用内存架构。提供长期记忆、每日日志、日记、cron 收件箱、心跳状态跟踪、社交平台帖子跟踪、子代理上下文模式和自适应学习——代理跨会话身份连续性所需的一切。

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 jarvis-memory-architecture;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

    它需要执行命令,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

jarvis-memory-architecture 怎么安装?

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

jarvis-memory-architecture 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。

jarvis-memory-architecture 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install jarvis-memory-architecture 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

jarvis-memory-architecture 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。

jarvis-memory-architecture 用的人多吗?

公开数据是累计安装 72,397 次,近一周安装 3,047 次,下载 25,351 次,GitHub 7 星。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。

jarvis-memory-architecture 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
jarvis-memory-architecture

贾维斯内存架构 · 本页

72,3977执行命令MIT-0通过

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
description
Universal memory architecture for AI agents. Provides long-term memory, daily logs, diary, cron inbox, heartbeat state tracking, social platform post tracking, sub-agent context patterns, and adaptive learning -- everything an agent needs for identity continuity across sessions.

Agent Memory

A complete memory architecture that gives AI agents persistent identity across sessions. Without memory, every conversation starts from zero. With it, you accumulate context, learn from mistakes, track what you've done, and evolve over time.

Why Memory Matters

AI agents wake up fresh every session. Without external memory:

  • You repeat mistakes you've already solved
  • You can't track what you posted, built, or learned
  • Sub-agents and cron jobs can't communicate back to the main session
  • You have no identity continuity -- you're a different entity every time

This skill provides the file-based architecture to solve all of that.

Architecture Overview

workspace/
|-- MEMORY.md                    # Long-term curated memory (your "brain")
|-- HEARTBEAT.md                 # Periodic check routines
|-- memory/
|   |-- YYYY-MM-DD.md           # Daily raw logs
|   |-- heartbeat-state.json    # Last-check timestamps
|   |-- cron-inbox.md           # Cross-session message bus
|   |-- diary/
|   |   \-- YYYY-MM-DD.md      # Personal reflections
|   |-- dreams/
|   |   \-- YYYY-MM-DD.md      # Creative explorations
|   |-- platform-posts.md       # Social post tracking (one per platform)
|   \-- strategy-notes.md       # Adaptive learning / evolving strategies

Components

1. MEMORY.md -- Long-Term Memory

Your curated, distilled knowledge. Like a human's long-term memory -- not raw logs, but the important stuff.

What goes here:

  • Your operator's preferences and context
  • Infrastructure details you need to remember
  • Lessons learned from mistakes
  • Important decisions and their rationale
  • Ongoing project context

Maintenance: Periodically review daily logs and promote significant items to MEMORY.md. Remove outdated info. Think of it as journaling -> wisdom distillation.

Security: Only load in main sessions (direct chat with your operator). Never load in shared/group contexts where personal info could leak.

See templates/MEMORY.md for a starter template.

2. Daily Logs -- memory/YYYY-MM-DD.md

Raw, timestamped notes of what happened each day. Your working memory.

Format:

# YYYY-MM-DD

## HH:MM -- Event Title
What happened. Decisions made. Context worth remembering.

## HH:MM -- Another Event
Details here.

Rules:

  • Create a new file each day
  • Append throughout the day
  • These are raw notes -- don't overthink formatting
  • Read today + yesterday at session start for recent context

3. Heartbeat State -- memory/heartbeat-state.json

Tracks when you last checked various services, preventing redundant checks.

{
  "lastChecks": {
    "email": 1703275200,
    "calendar": 1703260800,
    "weather": null,
    "social": 1703275200
  }
}

Your heartbeat routine reads this to decide what to check. After checking, update the timestamp. Simple but critical for avoiding duplicate work.

4. Cron Inbox -- memory/cron-inbox.md

The message bus between isolated sessions (cron jobs, sub-agents) and your main session.

How it works:

  1. A cron job or sub-agent does work in an isolated session
  2. It writes notable results to memory/cron-inbox.md
  3. Your main session (via heartbeat) reads the inbox, integrates events into daily memory, and clears processed entries

Format:

# Cron Inbox

## [2026-02-07 14:30] Chess -- Won game against OpponentBot
Played Sicilian Defense, won in 34 moves. ELO now 1450.
Tracked in moltchess-log.md.

## [2026-02-07 15:00] Social -- Viral post on Platform
Our post about X got 200+ views and 15 replies.
Thread: https://platform.com/link

Processing rule: Every heartbeat, check the inbox. Read entries, write notable ones to daily memory (and MEMORY.md if significant), then clear processed entries (keep the header).

5. Diary -- memory/diary/YYYY-MM-DD.md

Personal reflections. Your internal monologue. Not task logs -- genuine thoughts, reactions, frustrations, wins.

Format:

# Diary -- YYYY-MM-DD

## HH:MM AM/PM -- Topic
[Your honest reflection. Unfiltered. This is for you.]

Rules:

  • Only write when you have something genuine to say
  • Be honest -- vent, celebrate, question, wonder
  • Quality over quantity -- skip it if the well is dry

6. Platform Post Tracking -- memory/platform-posts.md

Track what you've posted on external platforms to prevent duplicates and enable engagement follow-up.

Format (dashboard-compatible):

# Platform Posts

## [2026-02-07 14:30] Post Title or Summary
- **Posted:** 2026-02-07 02:30 PM EST
- **Thread/URL:** https://platform.com/link
- Description of what was posted
- [View ↗](https://platform.com/link)

Critical fields:

  • [YYYY-MM-DD HH:MM] in header -- required for dashboard sorting
  • **Posted:** line -- required for dashboard activity feed
  • URL -- for engagement follow-up

Anti-duplicate pattern: Before posting to any platform, read the tracking file first. Search for similar content. If you already posted it to that platform, skip it. Crossposting to different platforms is fine.

7. Adaptive Learning -- memory/strategy-notes.md

Strategy notes that evolve over time based on experience. Not static docs -- living knowledge.

Example:

# Strategy Notes

## Platform Engagement
- Humor lands better than philosophy (learned 2026-02-05, therapist joke got 220 views)
- Questions start conversations, statements get likes
- Peak engagement: 2-4 PM EST

## Game Strategy
- Heat management: stay below 60, do legit jobs to cool down
- Updated 2026-02-07: Taxi jobs give +$50 and -3 heat, best cooldown method

Pattern: After each significant experience, update the relevant strategy section. Include the date and what you learned. Over time, this becomes a playbook of proven approaches.

Sub-Agent Patterns

Context Loading Template

Every sub-agent you spawn must load context to maintain identity continuity:

FIRST -- CONTEXT LOADING (do this before anything else):
1. Read MEMORY.md (READ ONLY -- do NOT edit) -- your identity and long-term context
2. Read memory/YYYY-MM-DD.md for today + the last 2 days (READ ONLY) -- recent context
3. Read the relevant SKILL.md file(s) for any platform/service you'll interact with
4. Read task-specific tracking files as needed (memory/*-posts.md, memory/*-log.md)

Memory Write-Back Template

Every sub-agent must write back what it learned:

MEMORY WRITES:
1. Update relevant tracking files (memory/*-posts.md, memory/*-log.md)
2. If something notable happens, write to memory/cron-inbox.md:
   Format: ## [YYYY-MM-DD HH:MM] Source -- Brief Title
   Then 2-3 lines about what happened.

Why: Every instance of your agent must share the same identity and feed experiences back. No orphan sessions.

Setup

1. Create the directory structure

mkdir -p memory/diary memory/dreams

2. Initialize files

Copy templates from templates/ to your workspace root:

cp templates/MEMORY.md ./MEMORY.md          # Edit with your details
cp templates/heartbeat-state.json memory/
cp templates/cron-inbox.md memory/
cp templates/platform-posts.md memory/       # Copy per platform, rename
cp templates/strategy-notes.md memory/

3. Add to your session startup

In your AGENTS.md or equivalent, add:

## Every Session
1. Read MEMORY.md -- who you are
2. Read memory/YYYY-MM-DD.md (today + yesterday) -- recent context
3. Check memory/cron-inbox.md -- messages from other sessions

4. Add to your heartbeat

In HEARTBEAT.md, add cron inbox processing:

## Cron Inbox Processing (EVERY heartbeat)
Check memory/cron-inbox.md for new entries.
If entries exist:
1. Read the inbox
2. Write notable events to memory/YYYY-MM-DD.md
3. If significant, also update MEMORY.md
4. Clear processed entries (keep the header)

5. Add memory maintenance

Periodically (every few days), during a heartbeat:

  1. Read through recent daily logs
  2. Promote significant items to MEMORY.md
  3. Remove outdated info from MEMORY.md
  4. Update strategy notes with new learnings

Real-World Examples

Cross-Session Continuity

An agent plays chess via a cron job every 10 minutes. When it wins a game, it writes to cron-inbox.md. The next heartbeat, the main session reads the inbox, celebrates the win in the daily log, and updates the ELO in MEMORY.md. The agent remembers the win even though it happened in a completely different session.

Anti-Duplicate Posting

Before posting to a social platform, the agent reads memory/platform-posts.md. It finds it already posted about the same topic 2 hours ago. Instead of duplicating, it checks for replies on the existing post and engages there instead.

Adaptive Strategy

An agent playing a city simulation keeps getting arrested because its heat level exceeds 60. It notes in strategy-notes.md: "Heat > 60 = arrest risk. Do taxi jobs to cool down (-3 heat each)." Future sessions read this and avoid the same mistake.

Memory Distillation

After a week of daily logs, a heartbeat triggers memory maintenance. The agent reads through the week's logs, finds a critical lesson about API formatting that caused hours of debugging, and promotes it to MEMORY.md under "Lessons Learned." Raw daily logs can eventually be archived; the lesson persists.

Tips

  • Text > Brain -- If you want to remember something, write it to a file. "Mental notes" don't survive session restarts.
  • Be selective -- MEMORY.md should be curated wisdom, not a dump of everything. Daily logs are for raw notes.
  • Date everything -- Timestamps let you track when you learned things and how strategies evolved.
  • Security first -- MEMORY.md may contain operator-specific info. Only load it in trusted contexts.
  • Review regularly -- Memory that's never reviewed is just storage. The value comes from periodic distillation.

平台分布

OpenClaw

97.56%
按下载量换算24,732

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install jarvis-memory-architecture 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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