Build a Personal Knowledge Management (PKM) System with OpenClaw

Your Knowledge Is Leaking Away

Every day, you probably:

• Read 10+ articles or tweets
• Take some notes in Notion
• Chat about ideas with ChatGPT
• Learn something new on YouTube
• See valuable discussions on Slack/Discord

A week later, how much do you remember? Probably 10%.

The problem isn’t that you’re not trying hard enough. It’s that your “knowledge management system” has leaks:

Problem	Symptom
Scattered collection	”I remember reading that article, but I can’t find where I saved it…”
No organization	A pile of uncategorized notes in Notion
No review	Save and forget — the bookmark graveyard keeps growing
Manual shuffling	Spending 30 minutes daily copy-pasting data from various sources

---

OpenClaw + PKM = Your Automated Second Brain

OpenClaw’s role in PKM:

Collect → Organize → Store → Review → Apply
  ↑         ↑         ↑       ↑        ↑
  AI auto   AI auto   You     AI       AI searches
  capture   classify  decide  periodic your
                      where   remind   knowledge

You only need to do two things:

1. Tell OpenClaw where to collect from
2. Occasionally review what the AI has organized for you

---

Step 1: Design Your Knowledge Architecture

Workspace Structure

Set up the basic PKM structure in your OpenClaw Workspace:

workspace/
├── SOUL.md           # AI persona: Knowledge Manager
├── AGENTS.md         # Define the knowledge management Agent
├── skills/
│   ├── capture.yml   # Collection Skill
│   ├── organize.yml  # Organization Skill
│   └── review.yml    # Review Skill
├── knowledge/
│   ├── inbox/        # To be organized (AI auto-delivers here)
│   ├── notes/        # Organized notes
│   ├── references/   # Reference materials
│   └── projects/     # Project-related knowledge
└── config.yaml       # MCP connection settings

For detailed Workspace setup instructions, see the Soul Configuration Guide.

Knowledge Classification

Keep it simple. We recommend the PARA Method (by Tiago Forte):

Category	Description	Example
Projects	Ongoing projects	”Q2 Marketing Plan”
Areas	Areas of ongoing interest	”AI Technology” “Personal Finance”
Resources	Reference materials for future use	”Design Templates” “Writing Tips”
Archives	Completed or no longer needed	”2024 Annual Report”

---

Step 2: Automatic Collection

Skill: Web Article Capture

name: capture-article
description: Automatically capture web articles and save to knowledge base
trigger:
  - command: "save this"
  - command: "capture"

steps:
  # Step 1: Scrape the web content
  - action: web_scrape
    input:
      url: "{{url}}"
    output: raw_content

  # Step 2: AI organizes into a note
  - action: llm_generate
    config:
      model: gpt-4o-mini  # Use a cheaper model for simple tasks
    input:
      prompt: |
        Please organize the following web content into a structured note:
        
        ## Format Requirements
        - Title
        - One-sentence summary (under 30 words)
        - 3-5 key takeaways (bullet points)
        - Related tags (3-5)
        - My action items (if any)
        
        ## Content
        {{raw_content}}
    output: organized_note

  # Step 3: Save to Notion (via MCP)
  - action: mcp_call
    server: notion
    tool: create_page
    input:
      database_id: "{{notion_knowledge_db}}"
      content: "{{organized_note}}"
      tags: "{{organized_note.tags}}"

Skill: Daily RSS Knowledge Feed

name: daily-knowledge-feed
description: Automatically collect subscribed article summaries every morning
trigger:
  - schedule: "0 8 * * *"  # Every day at 8 AM

steps:
  - action: rss_fetch
    input:
      feeds:
        - "https://openai.com/blog/rss"
        - "https://blog.google/technology/ai/rss"
        - "your other RSS sources"
      since: "24h"  # Past 24 hours
    output: articles

  - action: llm_generate
    config:
      model: gpt-4o-mini
    input:
      prompt: |
        Here are the new articles from the past 24 hours.
        Pick the 5 most important ones, and for each provide:
        - Title + link
        - One-sentence takeaway
        - Relevance to me (high/medium/low)
        
        My areas of interest: AI Agents, automation, productivity tools
        
        {{articles}}
    output: digest

  - action: notify
    channel: telegram  # Push via Telegram
    input:
      message: "📚 Today's Knowledge Updates\n\n{{digest}}"

For Telegram setup, see the Telegram Integration Guide.

---

Step 3: Smart Organization

AI Auto-Tagging

No need for manual classification. Let AI automatically tag based on content:

name: auto-organize
description: Automatically organize new notes in inbox
trigger:
  - watch: "knowledge/inbox/"  # Monitor the inbox folder

steps:
  - action: llm_generate
    config:
      model: gpt-4o-mini
    input:
      prompt: |
        Analyze the following note content and return JSON:
        {
          "category": "projects|areas|resources|archives",
          "tags": ["tag1", "tag2"],
          "related_notes": ["keywords of potentially related existing notes"],
          "priority": "high|medium|low"
        }
        
        Note content:
        {{note_content}}
    output: classification

  - action: file_move
    input:
      from: "knowledge/inbox/{{filename}}"
      to: "knowledge/{{classification.category}}/{{filename}}"

  - action: metadata_update
    input:
      file: "knowledge/{{classification.category}}/{{filename}}"
      tags: "{{classification.tags}}"

Knowledge Linking

AI discovers connections between notes, similar to Obsidian’s backlinks:

name: link-knowledge
description: Periodically scan the knowledge base to establish links between notes

steps:
  - action: file_list
    input:
      path: "knowledge/notes/"
    output: all_notes

  - action: llm_generate
    config:
      model: gpt-4o  # Needs stronger comprehension
    input:
      prompt: |
        Below are the notes in my knowledge base.
        Please find strongly related note pairs and explain the connection.
        
        Output format:
        - [Note A] ←→ [Note B]: Reason for connection
        
        {{all_notes}}

---

Step 4: Regular Review

Spaced Repetition

The most effective memorization method. AI automatically schedules review times based on your history:

name: knowledge-review
description: Push knowledge that needs review every morning
trigger:
  - schedule: "0 9 * * *"  # Every day at 9 AM

steps:
  - action: review_scheduler
    input:
      algorithm: "sm2"  # SuperMemo 2 algorithm
      count: 5          # Review 5 items per day
    output: review_items

  - action: llm_generate
    config:
      model: gpt-4o-mini
    input:
      prompt: |
        Format the following knowledge into review cards:
        Each card should include:
        - 🃏 Core concept (one sentence)
        - 💡 Why it matters
        - 🔗 Related knowledge
        - ❓ A thought-provoking question
        
        {{review_items}}
    output: review_cards

  - action: notify
    channel: telegram
    input:
      message: "🧠 Today's Knowledge Review\n\n{{review_cards}}\n\nReply with a number 1-5 to rate your recall"

Weekly Knowledge Report

name: weekly-knowledge-report
trigger:
  - schedule: "0 18 * * 5"  # Every Friday at 6 PM

steps:
  - action: knowledge_stats
    input:
      period: "7d"
    output: stats

  - action: llm_generate
    config:
      model: gpt-4o
    input:
      prompt: |
        Based on the following statistics, write a personal knowledge management weekly report:
        
        - Number of new notes this week
        - Most frequent tags
        - Knowledge gaps (topics searched for but not found)
        - Suggested focus areas for next week
        
        {{stats}}

---

Recommended Tool Pairings

OpenClaw’s MCP protocol lets you connect various knowledge management tools:

Function	Recommended Tool	MCP Server
Note Library	Notion / Obsidian	mcp-server-notion
Read Later	Readwise / Pocket	mcp-server-readwise
RSS Feeds	Feedly / Inoreader	mcp-server-rss
Bookmarks	Raindrop.io	mcp-server-raindrop
Push Notifications	Telegram	mcp-server-telegram
File Storage	Google Drive	mcp-server-google-drive

---

Complete Example: My PKM Setup

SOUL.md

You are my personal knowledge management assistant.

## Principles
- Concise beats verbose: Keep core points per note to 5 or fewer
- Connections beat accumulation: Actively find links between knowledge
- Action beats collection: Every note should have at least one "what I can do"

## Tone
- Like a friend giving you a reminder, not too formal
- Use clear, approachable language

## Notes
- Mark uncertain information with ⚠️
- Don't make decisions for me — give me options and let me choose

Daily Flow

08:00 → RSS daily digest pushed to Telegram
09:00 → Knowledge review cards pushed
Anytime → Say "save this" + paste a link → auto-capture and organize
18:00 → Inbox auto-organized (categorized + tagged)
Friday → Weekly report + next week's suggestions

---

Frequently Asked Questions

Can I use Notion?

Absolutely. OpenClaw connects to Notion API via MCP, and can automatically create pages, update databases, and search existing notes.

What if I don’t trust AI organization quality?

You can set it to “AI organize + human review” mode: AI organizes into the inbox, then you review and move items to their permanent location. Quality can be improved with Prompt techniques.

How much does it cost per month?

Using GPT-4o mini for collection and organization, typical usage costs $1-3 per month. Details in Token Economics.

Is my data safe?

OpenClaw runs on your own computer/server — data doesn’t go through third parties. Note content is only transmitted when calling the AI API, and it won’t be used for training.

---

Next Steps

Start building your PKM system:

• 📦 Install OpenClaw first
• 🧩 Learn to write Skills for automation workflows
• 🔗 Connect Notion / Google Drive via MCP
• 💬 Connect Telegram for push notifications
• 👻 Set up your AI assistant’s persona