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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 source installs☆ 0 Repository stars
View source ↗InstallationSKILL.md ↗

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install aisoftgg/para-memory

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill 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...

Source information

Source
github
Repository
openclaw/skills
Path
skills/aisoftgg/para-memory
Version
—
Commit
ff5bb98cef522fb5c69d07359401f7a3a6d04518
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

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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