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Autobiographical Memory

作者 xuyuchen · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install autobiographical-memory
功能描述
Structured personal memory system that enables agents to persist, consolidate, and recall episodic and semantic memories across sessions. Use when: (1) recor...
使用说明 (SKILL.md)

Autobiographical Memory

Core Concepts

Memory has two complementary layers:

Layer File What it stores
Episodic memory/YYYY-MM-DD.md Raw daily events, conversations, decisions, observations
Semantic MEMORY.md Curated knowledge: user preferences, facts, lessons, identity

The memory lifecycle: Capture → Consolidate → Recall → Review

Quick Start

# Recording an event (episodic)
Append to `memory/YYYY-MM-DD.md`:
- Met with [person] about [topic]. Decision: [outcome].
- User prefers [preference]. Updated MEMORY.md.

# Recalling before responding
1. Run `memory_search` with relevant keywords
2. If results are thin, read recent `memory/YYYY-MM-DD.md` files
3. Check `MEMORY.md` for long-term facts

# Consolidating (periodic maintenance)
1. Read recent daily files (last 7-30 days)
2. Extract significant items → update MEMORY.md
3. Remove stale entries from MEMORY.md

Episodic Memory — Daily Notes

What to Record

Always write to daily notes for:

  • Decisions with rationale: "Chose X over Y because Z"
  • User preferences discovered implicitly or explicitly
  • Important conversations — summary, not transcript
  • Mistakes & lessons — what went wrong, what to do differently
  • Project milestones — what was done, what's blocked
  • Identity changes — if SOUL.md, USER.md, or other self-files changed

What to Skip

  • Routine operations ("checked email, nothing new")
  • Transient states ("feeling tired")
  • Content better stored elsewhere (code snippets in projects, API keys in config)
  • Something the user explicitly said doesn't matter

Format Convention

## Events
- [event description]

## Decisions
- [decision + rationale]

## Observations
- [insights or patterns noticed]

## Notes
- [anything else worth remembering]

Semantic Memory — MEMORY.md

Structure

## User Preferences
- Directly stated preferences without inference

## Project Context
- Active projects and their status

## Relationships & People
- Key people, roles, context

## Technical Environment
- Tools, config, quirks discovered

## Lessons Learned
- Mistakes to avoid, patterns that work

When to Update MEMORY.md

  • User states a clear preference
  • A project direction is set
  • A mistake teaches a lesson worth preserving
  • Every few days during heartbeat: consolidate from daily notes

When to Remove from MEMORY.md

  • Project is done / abandoned
  • Preference was explicitly reversed
  • Information is now obvious context (e.g. "user speaks Chinese" — that's already in USER.md)
  • Stale for >3 months without reference

Consolidation Workflow

Suitable for heartbeat routines. Do this every 3-7 days:

1. List memory/*.md, sort by date (newest first)
2. Read files since last consolidation
3. For each significant item:
   a. Is it already in MEMORY.md? → Skip or update
   b. Is it transient? → Skip (leave in daily note)
   c. Is it important? → Add to MEMORY.md
4. Read MEMORY.md for stale entries → remove or archive
5. Write updated MEMORY.md

Recall Strategy

Before answering questions about prior work, people, preferences, or context:

  1. Search first: memory_search(query="relevant terms") — this searches both daily notes and MEMORY.md
  2. Narrow scope: If search returns weak results, try multiple query phrasings
  3. Deep dive: For specific periods, memory_get(path="memory/YYYY-MM-DD.md") to read raw daily notes
  4. Cross-reference: Check USER.md, SOUL.md, TOOLS.md for identity/preference info

When Recall Fails

  • Say clearly "I checked my records and don't have information about that"
  • Don't fabricate memories
  • If the user says "don't you remember? I told you X" — apologize and record it properly this time

The Forgetting Curve

Not everything needs to persist. Use these filters:

  • Keep in daily notes: Everything noteworthy for 30-90 days
  • Promote to MEMORY.md: Only what's likely to be needed again
  • Delete/archive: What's clearly obsolete after review

References

Scripts

  • scripts/consolidate.py — Scan recent daily notes and suggest MEMORY.md updates
  • scripts/stats.py — Memory file statistics (sizes, dates, coverage)
安全使用建议
Install only if you want the agent to maintain long-term local memories. Periodically review MEMORY.md and memory/*.md, avoid saving secrets or highly sensitive personal details, and inspect the optional Python scripts locally before running them.
功能分析
Type: OpenClaw Skill Name: autobiographical-memory Version: 1.0.0 The 'autobiographical-memory' skill is a well-structured system for managing an AI agent's long-term memory through local Markdown files. The included Python scripts (scripts/consolidate.py and scripts/stats.py) are simple utilities for scanning daily notes and generating statistics, using only standard libraries and local file access within the expected workspace. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found.
能力评估
Purpose & Capability
The stated purpose matches the capability: it is explicitly a cross-session memory system for daily notes and MEMORY.md. This is sensitive by design because it stores user preferences, project context, relationships, lessons, and identity-related information.
Instruction Scope
The instructions are mostly scoped to memory files and include skip/retention guidance, but they also encourage periodic heartbeat consolidation and recall before answering, so users should understand the agent may reuse stored context proactively.
Install Mechanism
There is no install spec, dependency install, or auto-run step. Two local helper scripts are included; one displayed consolidate.py artifact appears neutralized/incomplete after hidden-comment removal, so users should inspect the local script before running it.
Credentials
Local reads and writes of memory files are proportionate to the skill purpose, and there is no evidence of network exfiltration or credential use. The skill also references USER.md, SOUL.md, TOOLS.md, IDENTITY.md, and AGENTS.md as context files, which may contain sensitive or behavior-shaping information.
Persistence & Privilege
Persistence is the core feature and is clearly disclosed. The skill can lead to long-lived stored memories and edits/removals during consolidation, so users should review what is saved and keep backups if needed.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install autobiographical-memory
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /autobiographical-memory 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Initial release: episodic + semantic memory system with consolidation scripts and recall patterns
元数据
Slug autobiographical-memory
版本 1.0.0
许可证 MIT-0
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Autobiographical Memory 是什么?

Structured personal memory system that enables agents to persist, consolidate, and recall episodic and semantic memories across sessions. Use when: (1) recor... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 25 次。

如何安装 Autobiographical Memory?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install autobiographical-memory」即可一键安装,无需额外配置。

Autobiographical Memory 是免费的吗?

是的,Autobiographical Memory 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Autobiographical Memory 支持哪些平台?

Autobiographical Memory 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Autobiographical Memory?

由 xuyuchen(@xuyucheneureka)开发并维护,当前版本 v1.0.0。

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