autobiographical-memory

Structured personal memory system that enables agents to persist, consolidate, and recall episodic and semantic memories across sessions. Use when: (1) recording significant events, decisions, or conversations, (2) consolidating daily logs into long-term memory, (3) recalling relevant past context before answering, (4) managing memory files (MEMORY.md, daily notes), (5) reasoning about what to remember vs forget.

Safety Notice

This listing is from the official public ClawHub registry. Review SKILL.md and referenced scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "autobiographical-memory" with this command: npx skills add xuyucheneureka/autobiographical-memory

Autobiographical Memory

Core Concepts

Memory has two complementary layers:

LayerFileWhat it stores
Episodicmemory/YYYY-MM-DD.mdRaw daily events, conversations, decisions, observations
SemanticMEMORY.mdCurated 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)

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Automation

Digaide Assistant

Persistent identity and memory context layer for AI agents across platforms.

Registry SourceRecently Updated
1500Profile unavailable
Coding

MEMORIA: Persistent Memory Layer for AI Agents

Gives your OpenClaw agent persistent memory across every session. MEMORIA maintains a structured knowledge layer: who you are, what you're building, every de...

Registry SourceRecently Updated
6201Profile unavailable
Automation

Agent Memory Persistent Workspace Memory System

Stop your AI agent from forgetting everything between sessions. Three-tier memory architecture (long-term owner namespace / daily logs / session handoff), cr...

Registry SourceRecently Updated
4160Profile unavailable
Automation

Team Collaboration Skill

快速搭建多 Agent 协作系统。创建产品/研发/运营团队,支持持久化、任务路由、知识提取、并行协作。

Registry SourceRecently Updated
5841Profile unavailable