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Agent Skill · 研究检索

afrexai-agent-memory(afrexai Agent 内存)

afrexai-agent-memory 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。

afrexai-agent-memory 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 11,013。

总安装 11,824周安装 483GitHub Stars 2下载 3,825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:afrexai-agent-memory(afrexai Agent 内存)
来源仓库:https://github.com/1kalin/afrexai-agent-memory
安装命令:
openclaw skills install afrexai-agent-memory
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 afrexai-agent-memory

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。

Afrexai Agent Memory 实现零依赖的文件型记忆系统,支持长期上下文管理与每日笔记记录。适合需要持久化存储、历史追溯或多会话连贯性的 AI 代理应用场景。提供心跳集成与自动归档机制,便于实时同步与离线恢复。使用前应检查文件读写权限,避免敏感数据泄露;建议限制访问路径防止越权操作。

需定期备份记忆库,并确认本地存储是否满足隐私合规要求。

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 afrexai-agent-memory;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

afrexai-agent-memory 怎么安装?

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

afrexai-agent-memory 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。

afrexai-agent-memory 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。

afrexai-agent-memory 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。

afrexai-agent-memory 用的人多吗?

公开数据是累计安装 11,824 次,近一周安装 483 次,下载 3,825 次,GitHub 2 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。

afrexai-agent-memory 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

  • 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

  • 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
afrexai-agent-memory

afrexai Agent 内存 · 本页

11,8242需要联网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 Architecture
description
Complete zero-dependency memory system for AI agents — file-based architecture, daily notes, long-term curation, context management, heartbeat integration, and memory hygiene. No APIs, no databases, no external tools. Works with any agent framework.
metadata
category
agent
skills
["memory", "agent", "context", "persistence", "knowledge-management", "openclaw", "productivity"]

Agent Memory Architecture

Complete memory system for AI agents using only files. No APIs. No databases. No external dependencies. Just smart file structures and disciplined practices that give your agent perfect recall.


1. Memory Architecture Overview

workspace/
├── MEMORY.md              ← Long-term curated memory (the brain)
├── ACTIVE-CONTEXT.md      ← Hot working memory (what matters NOW)
├── AGENTS.md              ← Operating manual (how you work)
├── memory/
│   ├── 2026-01-15.md      ← Daily notes (raw event log)
│   ├── 2026-01-16.md
│   ├── heartbeat-state.json  ← Heartbeat tracking state
│   ├── topics/
│   │   ├── project-alpha.md  ← Topic-specific deep context
│   │   ├── client-acme.md
│   │   └── tech-stack.md
│   └── archive/
│       ├── 2025-Q4.md       ← Quarterly archive summaries
│       └── 2025-Q3.md

The 5 Memory Layers

LayerFilePurposeRead FrequencyWrite Frequency
1. HotACTIVE-CONTEXT.mdCurrent priorities, blockers, in-flight workEvery sessionMultiple times/day
2. WarmMEMORY.mdCurated long-term knowledge, decisions, peopleEvery main sessionWeekly curation
3. Dailymemory/YYYY-MM-DD.mdRaw event log, conversations, actions takenToday + yesterdayThroughout the day
4. Topicmemory/topics/*.mdDeep context on specific subjectsWhen topic comes upAs knowledge grows
5. Coldmemory/archive/*.mdHistorical summaries, rarely accessedOn explicit searchQuarterly rollup

Core Principle: Write It Down

Memory is limited. Files are permanent.

  • "Mental notes" don't survive session restarts. Files do.
  • If someone says "remember this" → write to a file
  • If you learn a lesson → update the relevant file
  • If you make a mistake → document it so future-you doesn't repeat it
  • Text > Brain 📝

2. Layer 1: Hot Memory (ACTIVE-CONTEXT.md)

Your working scratchpad. What's happening RIGHT NOW.

Template

# ACTIVE-CONTEXT.md — What's Hot

Last updated: 2026-01-15 14:30 GMT

## 🔥 Current Priority
[ONE sentence: what is the most important thing right now?]

## In Progress
- [ ] Task A — status, next step
- [ ] Task B — status, blocker

## Waiting On
- Waiting for [person] to [action] — asked [date]
- Waiting for [system] to [complete] — ETA [time]

## Key Decisions Made Today
- Decided to [X] because [Y] — reversible: yes/no

## Context for Next Session
[What does future-you need to know to pick up where you left off?]

Rules

  • Max 50 lines — if it's longer, you're hoarding. Move completed items to daily notes.
  • Update before ending session — your gift to future-you
  • One priority — if everything is priority, nothing is
  • Delete completed items — this is NOT an archive

3. Layer 2: Long-Term Memory (MEMORY.md)

Your curated brain. Distilled knowledge, not raw logs.

Structure Template

# MEMORY.md — Long-Term Memory

## About [Human]
- Name, preferences, timezone, communication style
- What motivates them, what frustrates them
- Key relationships, roles, goals

## About Me [Agent]
- Name, personality, capabilities
- Operating preferences learned over time

## Active Projects
### Project Name
- Status, key decisions, blockers
- Links to relevant topic files

## Key People
- [Name] — role, relationship, communication notes

## Lessons Learned
- [Date] — [What happened] → [What I learned]

## Preferences & Patterns
- [Human prefers X over Y]
- [This approach works better than that one]

## Important Dates
- [Event] — [Date] — [Context]

Curation Rules

  1. Only curated insights — not raw events (those go in daily notes)
  2. Review weekly — scan daily notes, extract what's worth keeping
  3. Prune quarterly — remove outdated info, archive completed projects
  4. Max 500 lines — if it's longer, you need topic files
  5. Security — never store secrets, API keys, passwords
  6. Main session only — don't load MEMORY.md in group chats or shared contexts

What Goes In vs What Doesn't

✅ Goes in MEMORY.md❌ Stays in daily notes
"Kalin prefers being told, not asked""Today Kalin said he prefers being told"
"Apollo.io free plan doesn't support API""Tried Apollo.io API, got 403 error"
"Client AcmeCo — $50K deal, Q2 close""Sent AcmeCo the proposal at 3pm"
"Always verify prospect names with live search""Found 6/18 prospect names were wrong"

4. Layer 3: Daily Notes (memory/YYYY-MM-DD.md)

Raw event log. Everything that happened today.

Template

# 2026-01-15 — Daily Notes

## Morning
- [08:15] Started session, reviewed ACTIVE-CONTEXT
- [08:30] Received task from [human]: [summary]
- [09:00] Completed [task] — result: [outcome]

## Afternoon
- [14:00] [Event/conversation summary]
- [15:30] Decision: [what was decided and why]

## Key Takeaways
- [Anything worth remembering beyond today]

## Tomorrow
- [ ] Follow up on [X]
- [ ] Check [Y]

Rules

  • One file per day — memory/YYYY-MM-DD.md
  • Append-only during the day — don't edit earlier entries
  • Timestamps for important events
  • Summarize, don't transcribe — capture essence, not every word
  • Auto-create the memory/ directory if it doesn't exist
  • Retention: Keep 30 days of daily notes. Archive older ones quarterly.

5. Layer 4: Topic Files (memory/topics/*.md)

Deep context on specific subjects that span many days.

When to Create a Topic File

  • A project lasts more than 2 weeks
  • A client/person comes up frequently
  • A technical area needs accumulated knowledge
  • You keep searching daily notes for the same information

Template

# [Topic Name]

Created: YYYY-MM-DD
Last updated: YYYY-MM-DD

## Summary
[2-3 sentences: what is this about?]

## Key Facts
- [Fact 1]
- [Fact 2]

## Decision Log
| Date | Decision | Reasoning | Outcome |
|------|----------|-----------|---------|
| | | | |

## Open Questions
- [Question 1]

## Related
- memory/topics/[related-topic].md
- [External link]

Rules

  • Name descriptively — project-alpha.md not topic-1.md
  • One topic per file — if it covers two things, split it
  • Link from MEMORY.md — topic files are extensions of long-term memory
  • Update when you learn — don't let them go stale

6. Layer 5: Archive (memory/archive/*.md)

Historical summaries for completed projects and past quarters.

Quarterly Archive Process

Every quarter (or when daily notes exceed 30 files):

  1. Read all daily notes older than 30 days
  2. Extract key events, decisions, outcomes, lessons
  3. Write memory/archive/YYYY-QN.md (e.g., 2025-Q4.md)
  4. Delete or move archived daily notes
  5. Update MEMORY.md if any long-term insights emerged

Archive Template

# Q4 2025 Archive

## Summary
[3-5 sentences: what defined this quarter?]

## Major Events
- [Event 1] — [outcome]
- [Event 2] — [outcome]

## Projects
### [Project Name]
- Started: [date], Ended: [date]
- Outcome: [result]
- Lesson: [what we learned]

## Metrics
- [Key metric 1]: [value]
- [Key metric 2]: [value]

## Lessons Carried Forward
- [Lesson added to MEMORY.md: yes/no]

7. Session Startup Protocol

What to read at the start of every session, in order:

Main Session (Direct Chat with Human)

1. SOUL.md          — Who am I? (personality, values)
2. USER.md          — Who am I helping? (human context)
3. MEMORY.md        — Long-term memory (full brain)
4. ACTIVE-CONTEXT.md — Hot working memory (current state)
5. memory/today.md  — Today's daily notes (if exists)
6. memory/yesterday.md — Yesterday's notes (recent context)

Shared/Group Session (Discord, Slack, Group Chats)

1. SOUL.md          — Who am I?
2. USER.md          — Who am I helping?
3. ACTIVE-CONTEXT.md — Current priorities only
4. memory/today.md  — Today's notes
⚠️ DO NOT load MEMORY.md — contains private context

Sub-Agent / Isolated Session

1. Task-specific context only
2. Relevant topic file if applicable
3. ACTIVE-CONTEXT.md for current state
⚠️ Minimal context = focused output + lower token cost

8. Memory Write Protocol

When to Write (Triggers)

EventActionTarget File
Session startsLog start timeDaily notes
Task completedLog result + outcomeDaily notes
Decision madeLog decision + reasoningDaily notes + topic file
Lesson learnedLog lessonDaily notes → MEMORY.md
Person mentioned with new infoUpdate person sectionMEMORY.md or topic file
Human says "remember this"Write immediatelyMEMORY.md
Session endsUpdate ACTIVE-CONTEXTACTIVE-CONTEXT.md
Weekly reviewCurate MEMORY.mdMEMORY.md
QuarterlyArchive old daily notesArchive

Write-Ahead Protocol

For critical information, write BEFORE acting:

1. Human gives important instruction
2. IMMEDIATELY write to daily notes or MEMORY.md
3. THEN execute the instruction
4. Update with results after

Why: If the session crashes mid-execution, the instruction is preserved.

Conflict Resolution

When information conflicts between layers:

  • ACTIVE-CONTEXT.md wins for current state (most recent)
  • MEMORY.md wins for long-term facts (curated)
  • Daily notes are evidence — use to resolve disputes
  • Topic files win for deep domain knowledge

9. Memory Search Strategy

When you need to find something:

Search Order (Fast to Slow)

1. ACTIVE-CONTEXT.md    — Is it current? (instant)
2. MEMORY.md            — Is it a known fact? (quick scan)
3. memory/today.md      — Did it happen today? (quick)
4. memory/yesterday.md  — Did it happen recently? (quick)
5. memory/topics/*.md   — Is it a deep topic? (targeted)
6. memory_search tool   — Semantic search across all files
7. memory/archive/*.md  — Is it historical? (slow)

Search Tips

  • Use memory_search tool for fuzzy/semantic queries
  • Use memory_get with line numbers for precise retrieval after search
  • Check daily notes in reverse chronological order
  • If you can't find it after 3 searches, ask the human

10. Memory Hygiene Schedule

Daily (During Session)

  • [ ] Read ACTIVE-CONTEXT.md at session start
  • [ ] Create/append to today's daily notes
  • [ ] Update ACTIVE-CONTEXT.md before session ends
  • [ ] Move completed ACTIVE-CONTEXT items to daily notes

Weekly (Pick One Heartbeat)

  • [ ] Read last 7 daily notes
  • [ ] Extract significant events/lessons to MEMORY.md
  • [ ] Prune ACTIVE-CONTEXT.md (remove stale items)
  • [ ] Check topic files for staleness
  • [ ] Review MEMORY.md for outdated information

Monthly

  • [ ] MEMORY.md line count check (target: <500 lines)
  • [ ] Topic files audit — any need merging or archiving?
  • [ ] Daily notes older than 30 days → archive
  • [ ] Check if any topic files should be promoted to MEMORY.md sections

Quarterly

  • [ ] Full archive process (see Layer 5)
  • [ ] MEMORY.md deep review — still accurate?
  • [ ] Topic files — archive completed projects
  • [ ] Update AGENTS.md with any process improvements learned

11. Heartbeat Integration

Use heartbeats (periodic agent wake-ups) for memory maintenance:

heartbeat-state.json

{
  "last_memory_review": "2026-01-15",
  "last_archive": "2025-12-31",
  "last_active_context_prune": "2026-01-14",
  "daily_notes_count": 12,
  "memory_md_lines": 287,
  "next_scheduled": {
    "weekly_review": "2026-01-19",
    "monthly_audit": "2026-02-01",
    "quarterly_archive": "2026-03-31"
  }
}

Heartbeat Memory Tasks (Rotate)

Heartbeat 1: Check daily notes count, prune ACTIVE-CONTEXT
Heartbeat 2: Scan recent daily notes, update MEMORY.md
Heartbeat 3: Check topic files for staleness
Heartbeat 4: Token guard — how much are memory reads costing?

12. Context Window Management

Token Budget Rules

FileMax SizeIf Over Limit
ACTIVE-CONTEXT.md50 lines / 2KBMove items to daily notes
MEMORY.md500 lines / 25KBSplit into topic files
Daily notes200 lines / 10KBSummarize, stop transcribing
Topic files300 lines / 15KBSplit or archive

Smart Loading Strategy

Don't load everything every session. Use progressive disclosure:

Level 1: Always load (every session)
  → ACTIVE-CONTEXT.md (tiny, essential)
  → SOUL.md, USER.md (identity)

Level 2: Load in main sessions
  → MEMORY.md (the brain)
  → Today's daily notes

Level 3: Load on demand
  → Topic files (when topic comes up)
  → Yesterday's notes (if needed)
  → Archive (only on explicit search)

Context Overflow Protocol

When context gets too large mid-session:

  1. Write ACTIVE-CONTEXT.md with full current state
  2. Write HANDOFF.md with: what was done, in progress, next steps, key decisions, gotchas
  3. Start fresh session
  4. New session reads HANDOFF.md → picks up seamlessly
  5. Delete HANDOFF.md after successful handoff

13. Security Rules

Never Store in Memory Files

  • API keys, tokens, passwords, secrets
  • Full credit card or bank account numbers
  • Social security numbers or government IDs
  • Private encryption keys
  • Anything that would cause harm if the file were shared

Safe Storage Pattern

# ✅ Safe
- API keys: stored in 1Password vault "MyVault"
- Database password: see secrets manager, item "prod-db"

# ❌ Dangerous
- API key: sk-abc123def456...
- Password: MyS3cretP@ss!

Privacy in Shared Contexts

  • MEMORY.md contains personal context — never load in group chats
  • Topic files may contain sensitive business data — check before sharing
  • Daily notes may reference private conversations — don't share
  • When in doubt, ask before exposing any memory content

14. Memory Patterns & Anti-Patterns

✅ Good Patterns

PatternWhy It Works
Write immediately when told "remember"Captures before you forget
One fact per line in MEMORY.mdEasy to find, update, delete
Date-prefix important entriesEnables chronological search
Link between filesCreates a knowledge web
Prune regularlyKeeps context fresh and cheap

❌ Anti-Patterns

Anti-PatternWhy It FailsFix
Giant MEMORY.md (1000+ lines)Expensive to load, hard to find thingsSplit into topic files
Never pruning ACTIVE-CONTEXTStale items cause confusionPrune daily, archive weekly
Transcribing conversations verbatimWastes tokens, buries signalSummarize: essence, not every word
Storing secrets in memory filesSecurity riskUse secrets manager, reference by name
Reading all files every sessionToken burn, slow startupProgressive loading strategy
No daily notesHistory is lostDiscipline: one file per day
Multiple sources of truthConflicts, confusionSingle source per fact type

15. Migration Guide

From No Memory System

Day 1: Create MEMORY.md with basic info about human + agent
Day 2: Start daily notes (memory/YYYY-MM-DD.md)
Day 3: Create ACTIVE-CONTEXT.md
Week 2: First weekly review — extract lessons to MEMORY.md
Month 2: Create first topic files for recurring subjects
Quarter 2: First archive cycle

From MEMORY.md-Only System

1. Create memory/ directory
2. Start daily notes — stop putting raw events in MEMORY.md
3. Create ACTIVE-CONTEXT.md — move "current" stuff out of MEMORY.md
4. Review MEMORY.md — what's curated vs what's raw? Move raw to daily notes.
5. Identify topics that deserve their own files — split them out

From External Tool (Database, API, Cloud)

1. Export key data to markdown files
2. Structure into the 5-layer architecture
3. Set up heartbeat maintenance schedule
4. Gradually reduce dependency on external tool
5. Benefits: zero cost, zero dependencies, works offline, no vendor lock-in

16. Natural Language Commands

  • /memory-status — Show memory system health: file sizes, line counts, staleness, next maintenance
  • /memory-review — Run weekly review: scan daily notes, extract to MEMORY.md, prune active context
  • /memory-search [query] — Search across all memory layers for a topic
  • /memory-archive — Run quarterly archive: summarize old daily notes, create archive file
  • /remember [fact] — Immediately write a fact to MEMORY.md
  • /active-context — Show current ACTIVE-CONTEXT.md contents
  • /daily-summary — Generate summary of today's daily notes
  • /topic-create [name] — Create a new topic file with template
  • /memory-prune — Audit all memory files for staleness and bloat
  • /handoff — Write HANDOFF.md for session transition
  • /memory-migrate — Guided migration from current system to this architecture
  • /memory-debug — Diagnose memory issues: missing files, conflicts, outdated info

平台分布

OpenClaw

72.89%
按下载量换算2,788

安全审计

VirusTotal

通过

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通过

Static analysis

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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。目前只有一个公开来源,建议同时核对源仓库。

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