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πŸ¦€ ClawHub

Memory Augment

by @indigas

Long-term memory system for OpenClaw agents. Store, retrieve, and query conversation history and learned information across sessions.

Versionv1.0.0
Downloads316
TERMINAL
clawhub install claw-memory-augment

πŸ“– About This Skill


name: memory-augment description: Long-term memory system for OpenClaw agents. Store, retrieve, and query conversation history and learned information across sessions.

Memory Augment Skill

Provide long-term memory for OpenClaw agents. Store conversation history, learned facts, preferences, and context that persists across sessions.

Quick Start

# Install via clawhub
npx clawhub install memory-augment

Trigger

"Remember that I prefer Python for automation scripts" "Find all notes about my workspace setup"

Core Features

1. Long-Term Storage

Store any information that should persist:

  • User preferences: Coding style, workspace config, tool choices
  • Learned facts: Project details, technical decisions, patterns
  • Conversation history: Context from past sessions, decisions made
  • Task tracking: Todo items, progress, completed work
  • 2. Semantic Search

    Find stored information using natural language:

    clawhub memory search "what did I decide about the inbox triage skill?"
    

    3. Automatic Context Injection

    Before each turn, automatically inject relevant memories:

    {
      "context": {
        "recent_memories": [
          {"topic": "income", "content": "User approved inbox-triage for publishing"},
          {"topic": "workspace", "content": "OpenClaw running on marekserver"}
        ],
        "preferences": {
          "model": "local/qwen3.5-35B-A3B",
          "compute_tracked": true
        }
      }
    }
    

    4. Memory Expiry & Archiving

  • Temporary memories: Auto-expire after 7 days (session notes)
  • Permanent memories: Never expire (user preferences, core facts)
  • Archival: Compress old memories to reduce token usage
  • When to Use This Skill

    βœ… Need to remember user preferences across sessions βœ… Track conversation context over time βœ… Store learnings and decisions for future reference βœ… Query past information semantically βœ… Maintain agent personality and behavior consistency

    ❌ Not for storing sensitive data (passwords, API keys) ❌ Not for real-time data (current weather, live prices) ❌ Not for replacing database storage (structured data)

    How It Works

    Storage Layer

    # ~/.memory-augment/storage.yaml
    memories:
      - id: uuid-123
        content: "User prefers Python for automation"
        type: preference
        tags: ["coding", "python", "automation"]
        created: "2026-04-15T10:00:00Z"
        expires: null  # permanent
        score: 0.85   # confidence/relevance

    - id: uuid-124 content: "Approved inbox-triage skill for publishing" type: decision tags: ["income", "skills", "approval"] created: "2026-04-15T20:37:00Z" expires: "2026-04-22T20:37:00Z" # 7 days score: 0.95

    Retrieval System

    Uses hybrid search (keyword + semantic): 1. Parse query for keywords 2. Calculate relevance scores 3. Return top-K relevant memories 4. Inject into agent context

    Scoring Algorithm

    Memories are scored based on:

  • Recency: Newer = higher score
  • Tags match: Query tags vs memory tags
  • Type relevance: Preferences > decisions > context
  • Score boost: User-corrected memories boost their own score
  • Configuration

    # ~/.memory-augment/config.yaml
    storage:
      path: ~/.memory-augment/storage.yaml
      format: yaml  # or json

    settings: max_memories: 1000 default_expiry: 7 # days score_decay: 0.95 # daily decay factor search: top_k: 20 min_score: 0.3 include_tags: true

    auto_inject: enabled: true max_tokens: 5000 inject_before: ["each_turn", "weekly_summary"]

    Memory Types

    Preference

    User preferences, preferences, coding style, tool choices.

    type: preference
    tags: ["coding", "style"]
    content: "Prefers concise code over comments"
    

    Decision

    Decisions made, approvals, blocking choices.

    type: decision
    tags: ["income", "skills"]
    content: "Published inbox-triage to clawhub"
    

    Context

    Session context, project state, ongoing work.

    type: context
    tags: ["project", "setup"]
    content: "Building memory-augment skill, 60% complete"
    

    Learning

    What the agent learned, patterns discovered, corrections.

    type: learning
    tags: ["pattern", "optimization"]
    content: "Sub-agent spawning reduces context by 30%"
    

    Commands

    Store Memory

    clawhub memory store "Remember my workspace is at /home/marek/.openclaw/workspace"
    clawhub memory store "User prefers minimal markdown formatting" --tag preferences
    

    Search Memories

    clawhub memory search "what did I decide about income?"
    clawhub memory search "all memories about skills" --tag skills
    

    List Memories

    clawhub memory list --type decision
    clawhub memory list --since "2026-04-14"
    

    Delete Memory

    clawhub memory delete 
    clawhub memory delete --tag "temporary" --older-than "7d"
    

    Export/Import

    clawhub memory export > memories.json
    clawhub memory import < memories.json
    

    Output Format

    JSON

    {
      "query": "income decisions",
      "results": [
        {
          "id": "uuid-123",
          "content": "Published inbox-triage skill",
          "score": 0.92,
          "tags": ["income", "skills"]
        }
      ],
      "total": 5,
      "took_ms": 45
    }
    

    Markdown

    ## Found 5 memories for "income decisions"

    🎯 Published inbox-triage skill (score: 0.92)

    Type: decision Tags: income, skills Created: 2026-04-15 Content: Published inbox-triage skill to clawhub for passive income

    Limitations

  • Token budget: Context injection respects 48k token ceiling
  • Search accuracy: Semantic search may miss nuanced queries
  • Privacy: Do not store sensitive data (passwords, secrets)
  • Sync: Local storage only (no cloud sync yet)
  • Expiry: Temporary memories auto-expire (configurable)
  • Integration

    With Inbox Triage

    # Inject triage context when discussing messages
    auto_inject:
      triggers:
        - "inbox"
        - "messages"
        - "notification"
      memories:
        - "inbox-triage skill is complete and ready for publishing"
    

    With Cron Manager

    # Weekly memory summary
    cron:
      schedule: "0 0 * * 0"  # Sunday midnight
      action: "memory summarize --output weekly-summary.md"
    

    With Weather Alert

    # Memory context for weather queries
    auto_inject:
      triggers:
        - "weather"
        - "forecast"
      memories:
        - "User is in UTC timezone"
        - "Prefers concise weather summaries"
    

    Iteration

    Track search quality:

    # Correct a bad search result
    echo "CORRECT: uuid-123 - relevant to income query" >> ~/.memory-augment/corrections.log
    echo "INCORRECT: uuid-124 - should not have matched" >> ~/.memory-augment/corrections.log
    

    The system learns from corrections to improve scoring.


    Roadmap

  • [x] Basic storage system
  • [x] Semantic search implementation
  • [x] Automatic context injection
  • [ ] Multi-source sync (cloud backup)
  • [ ] Encrypted storage for sensitive data
  • [ ] Collaborative memories (shared between agents)
  • Built for the OpenClaw ecosystem.

    πŸ’‘ Examples

    # Install via clawhub
    npx clawhub install memory-augment

    Trigger

    "Remember that I prefer Python for automation scripts" "Find all notes about my workspace setup"

    βš™οΈ Configuration

    # ~/.memory-augment/config.yaml
    storage:
      path: ~/.memory-augment/storage.yaml
      format: yaml  # or json

    settings: max_memories: 1000 default_expiry: 7 # days score_decay: 0.95 # daily decay factor search: top_k: 20 min_score: 0.3 include_tags: true

    auto_inject: enabled: true max_tokens: 5000 inject_before: ["each_turn", "weekly_summary"]