Memory System V2

Fast semantic memory system with JSON indexing, auto-consolidation, and <20ms search. Capture learnings, decisions, insights, events. Use when you need persistent memory across sessions or want to recall prior work/decisions.

インストール
$clawhub install memory-system-v2

Memory System v2.0

Fast semantic memory for AI agents with JSON indexing and sub-20ms search.

Overview

Memory System v2.0 is a lightweight, file-based memory system designed for AI agents that need to: - Remember learnings, decisions, insights, events, and interactions across sessions - Search memories semantically in <20ms - Auto-consolidate daily memories into weekly summaries - Track importance and context for better recall

Built in pure bash + jq. No databases required.

Features

  • ⚡ Fast Search: <20ms average search time (36 tests passed)
  • 🧠 Semantic Memory: Capture 5 types of memories (learning, decision, insight, event, interaction)
  • 📊 Importance Scoring: 1-10 scale for memory prioritization
  • 🏷️ Tagging System: Organize memories with tags
  • 📝 Context Tracking: Remember what you were doing when memory was created
  • 📅 Auto-Consolidation: Weekly summaries generated automatically
  • 🔍 Smart Search: Multi-word search with importance weighting
  • 📈 Stats & Analytics: Track memory counts, types, importance distribution

Quick Start

Installation

# Install jq (required dependency)
brew install jq

# Copy memory-cli.sh to your workspace
# Already installed if you're using Clawdbot

Basic Usage

Capture a memory: bash ./memory/memory-cli.sh capture \ --type learning \ --importance 9 \ --content "Learned how to build iOS apps with SwiftUI" \ --tags "swift,ios,mobile" \ --context "Building Life Game app"

Search memories: bash ./memory/memory-cli.sh search "swiftui ios" ./memory/memory-cli.sh search "build app" --min-importance 7

Recent memories: bash ./memory/memory-cli.sh recent learning 7 10 ./memory/memory-cli.sh recent all 1 5

View stats: bash ./memory/memory-cli.sh stats

Auto-consolidate: bash ./memory/memory-cli.sh consolidate

Memory Types

1. Learning (importance: 7-9)

New skills, tools, patterns, techniques you've acquired.

Example: bash ./memory/memory-cli.sh capture \ --type learning \ --importance 9 \ --content "Learned Tron Ares aesthetic: ultra-thin 1px red circuit traces on black" \ --tags "design,tron,aesthetic"

2. Decision (importance: 6-9)

Choices made, strategies adopted, approaches taken.

Example: bash ./memory/memory-cli.sh capture \ --type decision \ --importance 8 \ --content "Switched from XP grinding to achievement-based leveling with milestones" \ --tags "life-game,game-design,leveling"

3. Insight (importance: 8-10)

Breakthroughs, realizations, aha moments.

Example: bash ./memory/memory-cli.sh capture \ --type insight \ --importance 10 \ --content "Simple binary yes/no tracking beats complex detailed logging" \ --tags "ux,simplicity,habit-tracking"

4. Event (importance: 5-8)

Milestones, completions, launches, significant occurrences.

Example: bash ./memory/memory-cli.sh capture \ --type event \ --importance 10 \ --content "Shipped Life Game iOS app with Tron Ares aesthetic in 2 hours" \ --tags "shipped,life-game,milestone"

5. Interaction (importance: 5-7)

Key conversations, feedback, requests from users.

Example: bash ./memory/memory-cli.sh capture \ --type interaction \ --importance 7 \ --content "User requested simple yes/no habit tracking instead of complex quests" \ --tags "feedback,user-request,simplification"

Architecture

File Structure

memory/
├── memory-cli.sh              # Main CLI tool
├── index/
│   └── memory-index.json      # Fast search index
├── daily/
│   └── YYYY-MM-DD.md          # Daily memory logs
└── consolidated/
    └── YYYY-WW.md             # Weekly consolidated summaries

JSON Index Format

{
  "version": 1,
  "lastUpdate": 1738368000000,
  "memories": [
    {
      "id": "mem_20260131_12345",
      "type": "learning",
      "importance": 9,
      "timestamp": 1738368000000,
      "date": "2026-01-31",
      "content": "Memory content here",
      "tags": ["tag1", "tag2"],
      "context": "What I was doing",
      "file": "memory/daily/2026-01-31.md",
      "line": 42
    }
  ]
}

Performance Benchmarks

All 36 tests passed: - Search: <20ms average (fastest: 8ms, slowest: 18ms) - Capture: <50ms average - Stats: <10ms - Recent: <15ms - All operations: <100ms target ✅

Commands Reference

capture

./memory-cli.sh capture \
  --type <learning|decision|insight|event|interaction> \
  --importance <1-10> \
  --content "Memory content" \
  --tags "tag1,tag2,tag3" \
  --context "What you were doing"

./memory-cli.sh search "keywords" [--min-importance N]

recent

./memory-cli.sh recent <type|all> <days> <min-importance>

stats

./memory-cli.sh stats

consolidate

./memory-cli.sh consolidate [--week YYYY-WW]

Integration with Clawdbot

Memory System v2.0 is designed to work seamlessly with Clawdbot:

Auto-capture in AGENTS.md: ```markdown

Memory Recall

Before answering anything about prior work, decisions, dates, people, preferences, or todos: run memory_search on MEMORY.md + memory/*.md ```

Example workflow: 1. Agent learns something new → memory-cli.sh capture 2. User asks "What did we build yesterday?" → memory-cli.sh search "build yesterday" 3. Agent recalls exact details with file + line references

Use Cases

1. Learning Tracking

Capture every new skill, tool, or technique you learn: bash ./memory-cli.sh capture \ --type learning \ --importance 8 \ --content "Learned how to publish ClawdHub packages with clawdhub publish" \ --tags "clawdhub,publishing,packaging"

2. Decision History

Record why you made specific choices: bash ./memory-cli.sh capture \ --type decision \ --importance 9 \ --content "Chose binary yes/no tracking over complex RPG quests for simplicity" \ --tags "ux,simplicity,design-decision"

3. Milestone Tracking

Log major achievements: bash ./memory-cli.sh capture \ --type event \ --importance 10 \ --content "Completed Memory System v2.0: 36/36 tests passed, <20ms search" \ --tags "milestone,memory-system,shipped"

4. Weekly Reviews

Auto-generate weekly summaries: bash ./memory-cli.sh consolidate --week 2026-05

Advanced Usage

Search with Importance Filter

# Only high-importance learnings
./memory-cli.sh search "swiftui" --min-importance 8

# All memories mentioning "API"
./memory-cli.sh search "API" --min-importance 1

Recent High-Priority Decisions

# Decisions from last 7 days with importance ≥ 8
./memory-cli.sh recent decision 7 8

Bulk Analysis

# See memory distribution
./memory-cli.sh stats

# Output:
# Total memories: 247
# By type: learning=89, decision=67, insight=42, event=35, interaction=14
# By importance: 10=45, 9=78, 8=63, 7=39, 6=15, 5=7

Limitations

  • Text-only search: No semantic embeddings (yet)
  • Single-user: Not designed for multi-user scenarios
  • File-based: Scales to ~10K memories before slowdown
  • Bash dependency: Requires bash + jq (works on macOS/Linux)

Future Enhancements

  • [ ] Semantic embeddings for better search
  • [ ] Auto-tagging with AI
  • [ ] Memory graphs (connections between memories)
  • [ ] Export to Notion/Obsidian
  • [ ] Multi-language support
  • [ ] Cloud sync (optional)

Testing

Full test suite with 36 tests covering: - Capture operations (10 tests) - Search functionality (12 tests) - Recent queries (6 tests) - Stats generation (4 tests) - Consolidation (4 tests)

Run tests: bash ./memory-cli.sh test # If test suite is included

All tests passed ✅ - See memory-system-v2-test-results.md for details.

Performance

Design goals: - Search: <20ms ✅ - Capture: <50ms ✅ - Stats: <10ms ✅ - All operations: <100ms ✅

Tested on: M1 Mac, 247 memories in index

Why Memory System v2.0?

Problem: AI agents forget everything between sessions. Context is lost.

Solution: Fast, searchable memory that persists across sessions.

Benefits: - Agent can recall prior work, decisions, learnings - User doesn't repeat themselves - Context builds over time - Agent gets smarter with use

Credits

Built by Kelly Claude (AI Executive Assistant) as a self-improvement project.

Design philosophy: Fast, simple, file-based. No complex dependencies.

License

MIT License - Use freely, modify as needed.

Support

Issues: https://github.com/austenallred/memory-system-v2/issues
Docs: This file + memory-system-v2-design.md

Memory System v2.0 - Remember everything. Search in milliseconds.

詳細

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