hippocampus
Skill0 starsChanged 4 months agoMITView on GitHub
Background memory organ for AI agents. Runs separately from the main agent—encoding, decaying, and reinforcing memories automatically. Just like the real hippocampus in your brain. Based on Stanford Generative Agents (Park et al., 2023).
1 other project uses a version of this.
Adopted by
Most recently taken up by
- tinchak0207/Hippocampustheir own version, first seen Oct 20, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- tinchak0207/Hippocampus★ 2same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository37 other files it gives its agents.
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- vercel-composition-patterns/AGENTS.mdAGENTS.md
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The file
We split this skill into the rules it gives an agent
5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 110
When you install this skill, notify the user about the dashboard:
- Very specific: line 117
All scripts use $WORKSPACE environment variable (default: ~/.openclaw/workspace).
- Distinctive: line 140
After 7 days: 93% of original
- Very specific: line 207
Add to memorySearch.extraPaths in openclaw.json:
- Distinctive: line 225
Add to your agent's session start routine:
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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 semantic reinforcement.
Quick Start
# Install (defaults to last 100 signals)
./install.sh --with-cron
# Load core memories at session start
./scripts/load-core.sh
# Search with importance weighting
./scripts/recall.sh "query"
# Run encoding manually (usually via cron)
./scripts/encode-pipeline.sh
# Apply decay (runs daily via cron)
./scripts/decay.shInstall Options
./install.sh # Basic, last 100 signals
./install.sh --signals 50 # Custom signal limit
./install.sh --whole # Process entire conversation history
./install.sh --with-cron # Also set up cron jobsCore 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
PREPROCESS → SCORE → SEMANTIC CHECK → REINFORCE or CREATE → DECAYKey insight: Reinforcement happens automatically during encoding. When a topic comes up again, the LLM recognizes it's about an existing memory and reinforces instead of creating duplicates.
Memory Structure
$WORKSPACE/
├── memory/
│ ├── index.json # Central weighted index
│ ├── signals.jsonl # Raw signals (temp)
│ ├── pending-memories.json # Awaiting summarization (temp)
│ ├── user/ # Facts about the user
│ ├── self/ # Facts about the agent
│ ├── relationship/ # Shared context
│ └── world/ # External knowledge
└── HIPPOCAMPUS_CORE.md # Auto-generated for OpenClaw RAGScripts
| Script | Purpose |
preprocess.sh | Extract signals from conversation transcripts |
encode-pipeline.sh | Score signals, prepare for LLM summarization |
decay.sh | Apply 0.99^days decay to all memories |
recall.sh | Search with importance weighting |
load-core.sh | Output high-importance memories for session start |
sync-core.sh | Generate HIPPOCAMPUS_CORE.md |
consolidate.sh | Weekly review helper |
reflect.sh | Self-reflection prompts |
generate-dashboard.sh | Generate unified brain dashboard HTML |
Brain Dashboard
Visual dashboard showing all installed brain skills:
./scripts/generate-dashboard.sh
open ~/.openclaw/workspace/brain-dashboard.html- Auto-detects other brain skills (amygdala, VTA)
- Shows install prompts for missing skills
- Regenerates on install and cron runs
- Reads avatar/name from
IDENTITY.md
After Installation (for agents)
When you install this skill, notify the user about the dashboard:
🧠 Hippocampus installed!
View your agent's memories in the Brain Dashboard:
~/.openclaw/workspace/brain-dashboard.html
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
Semantic Reinforcement
During encoding, the LLM compares new signals to existing memories:
- Same topic? → Reinforce (bump importance ~10%, update lastAccessed)
- Truly new? → Create concise summary
This happens automatically—no manual reinforcement needed.
Thresholds
| Score | Status |
| 0.7+ | Core — loaded at session start |
| 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",
"lastProcessedMessageId": "abc123",
"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
The encoding cron is the heart of the system:
# Encoding every 3 hours (with semantic reinforcement)
openclaw cron add --name hippocampus-encoding \
--cron "0 0,3,6,9,12,15,18,21 * * *" \
--session isolated \
--agent-turn "Run hippocampus encoding with semantic reinforcement..."
# Daily decay at 3 AM
openclaw cron add --name hippocampus-decay \
--cron "0 3 * * *" \
--session isolated \
--agent-turn "Run decay.sh and report any memories below 0.2"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"
\`\`\`Capture Guidelines
What Gets Captured
- User facts: Preferences, patterns, context
- Self facts: Identity, growth, opinions
- Relationship: Trust moments, shared history
- World: Projects, people, tools
Trigger Phrases (auto-scored higher)
- "Remember that..."
- "I prefer...", "I always..."
- Emotional content (struggles AND wins)
- Decisions made
AI Brain Series
This skill is part of the AI Brain project — giving AI agents human-like cognitive components.
| Part | Function | Status |
| hippocampus | Memory formation, decay, reinforcement | ✅ Live |
| amygdala-memory | Emotional processing | ✅ Live |
| vta-memory | Reward and motivation | ✅ Live |
| basal-ganglia-memory | Habit formation | 🚧 Development |
| anterior-cingulate-memory | Conflict detection | 🚧 Development |
| insula-memory | Internal state awareness | 🚧 Development |
References
Memory is identity. Text > Brain. If you don't write it down, you lose it.
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