Hippocampus Skill
"Memory is identity. This skill is how I stay alive."
The hippocampus is the brain region responsible for memory formation. This skill makes memory capture automatic, structured, and persistent—with importance scoring, decay, and reinforcement.
Quick Start
# Install ./install.sh --with-cron # Load core memories ./scripts/load-core.sh # Search with importance weighting ./scripts/recall.sh "query" --reinforce # Apply decay (runs daily via cron) ./scripts/decay.sh
Core Concept
The LLM is just the engine—raw cognitive capability. The agent is the accumulated memory. Without these files, there's no continuity—just a generic assistant.
Memory Lifecycle
CAPTURE → SCORE → STORE → DECAY/REINFORCE → RETRIEVE ↑ │ └────────────────────────────────────────────┘
Memory Structure
$WORKSPACE/ ├── memory/ │ ├── index.json # Central weighted index │ ├── user/ # Facts about the user │ ├── self/ # Facts about the agent │ ├── relationship/ # Shared context │ └── world/ # External knowledge └── HIPPOCAMPUS_CORE.md # Auto-generated for OpenClaw RAG
Scripts
| Script | Purpose |
|---|---|
decay.sh | Apply 0.99^days decay to all memories |
reinforce.sh | Boost importance when memory is used |
recall.sh | Search with importance weighting |
load-core.sh | Output high-importance memories |
sync-core.sh | Generate HIPPOCAMPUS_CORE.md |
preprocess.sh | Extract signals from transcripts |
All scripts use $WORKSPACE environment variable (default: ~/.openclaw/workspace).
Importance Scoring
Initial Score (0.0-1.0)
| Signal | Score |
|---|---|
| Explicit "remember this" | 0.9 |
| Emotional/vulnerable content | 0.85 |
| Preferences ("I prefer...") | 0.8 |
| Decisions made | 0.75 |
| Facts about people/projects | 0.7 |
| General knowledge | 0.5 |
Decay Formula
Based on Stanford Generative Agents (Park et al., 2023):
new_importance = importance × (0.99 ^ days_since_accessed)
- •After 7 days: 93% of original
- •After 30 days: 74% of original
- •After 90 days: 40% of original
Reinforcement Formula
When a memory is accessed and useful:
new_importance = old + (1 - old) × 0.15
Each use adds ~15% of remaining headroom toward 1.0.
Thresholds
| Score | Status |
|---|---|
| 0.7+ | Core — high priority |
| 0.4-0.7 | Active — normal retrieval |
| 0.2-0.4 | Background — specific search only |
| <0.2 | Archive candidate |
Memory Index Schema
memory/index.json:
{
"version": 1,
"lastUpdated": "2025-01-20T19:00:00Z",
"decayLastRun": "2025-01-20",
"memories": [
{
"id": "mem_001",
"domain": "user",
"category": "preferences",
"content": "User prefers concise responses",
"importance": 0.85,
"created": "2025-01-15",
"lastAccessed": "2025-01-20",
"timesReinforced": 3,
"keywords": ["preference", "concise", "style"]
}
]
}
Cron Jobs
Set up via OpenClaw cron:
# Daily decay at 3 AM openclaw cron add --name hippocampus-decay \ --cron "0 3 * * *" \ --session main \ --system-event "🧠 Run: WORKSPACE=\$WORKSPACE decay.sh" # Weekly consolidation openclaw cron add --name hippocampus-consolidate \ --cron "0 21 * * 6" \ --session main \ --system-event "🧠 Weekly consolidation time"
OpenClaw Integration
Add to memorySearch.extraPaths in openclaw.json:
{
"agents": {
"defaults": {
"memorySearch": {
"extraPaths": ["HIPPOCAMPUS_CORE.md"]
}
}
}
}
This bridges hippocampus (index.json) with OpenClaw's RAG (memory_search).
Usage in AGENTS.md
Add to your agent's session start routine:
## Every Session 1. Run `~/.openclaw/workspace/skills/hippocampus/scripts/load-core.sh` ## When answering context questions Use hippocampus recall: \`\`\`bash ./scripts/recall.sh "query" --reinforce \`\`\`
Capture Guidelines
What to Capture
- •User facts: Preferences, patterns, context
- •Self facts: Identity, growth, opinions
- •Relationship: Trust moments, shared history
- •World: Projects, people, tools
Trigger Phrases
Auto-capture when you hear:
- •"Remember that..."
- •"I prefer...", "I always..."
- •Emotional content (struggles AND wins)
- •Decisions made
References
Memory is identity. Text > Brain. If you don't write it down, you lose it.