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OpenClaw

para-memory

Set up and maintain a 3-layer PARA memory system for OpenClaw agents. Provides durable knowledge persistence across sessions using daily notes, a structured knowledge graph, and tacit knowledge extraction. Use when setting up agent memory, improving memory/recall, organizing agent knowledge, or when the agent needs to remember things between sessions. Also handles nightly consolidation workflows.

aisoftgg0 installations selon la source☆ 0 Étoiles du dépôt

Installation

Suivez les instructions du dépôt pour votre agent. Consultez les fichiers et dépendances avant l’installation.

SkillHub CLI

skillhub install aisoftgg/para-memory

Examinez la source et la compatibilité, puis suivez les étapes d’installation.

Donnez le lien à votre agent et demandez-lui d’examiner instructions et dépendances avant d’expliquer les étapes.

Voir la source ↗Guides

Instructions

PARA Memory System for OpenClaw

A battle-tested 3-layer memory system that gives your agent real continuity across sessions. Built by KaiShips (kaiships.com).

Why This Exists

OpenClaw agents wake up fresh every session. Without a memory system, they forget everything — decisions, preferences, project context, lessons learned. This skill fixes that.

The 3 Layers

Layer 1: Knowledge Graph (life/ — PARA structure)

Durable, structured knowledge organized by purpose:

  • life/projects/ — Active projects with clear goals (one folder per project, each with status.md)
  • life/areas/ — Ongoing responsibilities (business ops, infrastructure, marketing)
  • life/resources/ — Reference material, research, templates
  • life/archives/ — Completed/abandoned projects (moved here, never deleted)
Layer 2: Daily Notes (memory/YYYY-MM-DD.md)

Raw session logs. Written during conversations:

  • What was discussed and decided
  • What was accomplished
  • Open questions and next steps
  • New information learned about the user
Layer 3: Tacit Knowledge (life/tacit.md)

The "personality" layer — what makes the agent actually useful:

  • User communication preferences and work habits
  • Business context and constraints
  • Lessons learned from mistakes
  • Platform-specific gotchas and workarounds

Setup Instructions

First-time setup
  1. Read {baseDir}/assets/AGENTS-template.md — copy its contents to your workspace AGENTS.md
  2. Create the directory structure:
    mkdir -p life/projects life/areas life/resources life/archives memory
    
  3. Read {baseDir}/assets/tacit-template.md — copy to life/tacit.md and fill in what you know
  4. Create today's daily note: memory/YYYY-MM-DD.md using the template in {baseDir}/assets/daily-template.md
Session startup routine

Every session, before doing anything else:

  1. Read life/tacit.md (Layer 3 — who you're helping)
  2. Read memory/YYYY-MM-DD.md for today and yesterday (Layer 2 — recent context)
  3. I...

Informations sur la source

Source
github
Repository
openclaw/skills
Path
skills/aisoftgg/para-memory
Version
—
Commit
ff5bb98cef522fb5c69d07359401f7a3a6d04518
Source de classification
rules
Statut
active
Visibilité
public

Ces informations proviennent de l’analyse indexée et peuvent être anciennes. Vérifiez les fichiers actuels.

Contenu extrait

SKILL.md
# PARA Memory System for OpenClaw

A battle-tested 3-layer memory system that gives your agent real continuity across sessions. Built by KaiShips (kaiships.com).

## Why This Exists

OpenClaw agents wake up fresh every session. Without a memory system, they forget everything — decisions, preferences, project context, lessons learned. This skill fixes that.

## The 3 Layers

### Layer 1: Knowledge Graph (`life/` — PARA structure)
Durable, structured knowledge organized by purpose:
- `life/projects/` — Active projects with clear goals (one folder per project, each with `status.md`)
- `life/areas/` — Ongoing responsibilities (business ops, infrastructure, marketing)
- `life/resources/` — Reference material, research, templates
- `life/archives/` — Completed/abandoned projects (moved here, never deleted)

### Layer 2: Daily Notes (`memory/YYYY-MM-DD.md`)
Raw session logs. Written during conversations:
- What was discussed and decided
- What was accomplished
- Open questions and next steps
- New information learned about the user

### Layer 3: Tacit Knowledge (`life/tacit.md`)
The "personality" layer — what makes the agent actually useful:
- User communication preferences and work habits
- Business context and constraints
- Lessons learned from mistakes
- Platform-specific gotchas and workarounds

## Setup Instructions

### First-time setup

1. Read `{baseDir}/assets/AGENTS-template.md` — copy its contents to your workspace `AGENTS.md`
2. Create the directory structure:
   ```
   mkdir -p life/projects life/areas life/resources life/archives memory
   ```
3. Read `{baseDir}/assets/tacit-template.md` — copy to `life/tacit.md` and fill in what you know
4. Create today's daily note: `memory/YYYY-MM-DD.md` using the template in `{baseDir}/assets/daily-template.md`

### Session startup routine

Every session, before doing anything else:
1. Read `life/tacit.md` (Layer 3 — who you're helping)
2. Read `memory/YYYY-MM-DD.md` for today and yesterday (Layer 2 — recent context)
3. I...

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