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Hippocampus

作者 ImpKind · GitHub ↗ · v3.9.0
cross-platform ⚠ suspicious
3305
总下载
4
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6
当前安装
12
版本数
在 OpenClaw 中安装
/install hippocampus
功能描述
Persistent memory system for AI agents. Automatic encoding, decay, and semantic reinforcement — just like the hippocampus in your brain. Based on Stanford Generative Agents (Park et al., 2023).
使用说明 (SKILL.md)

Hippocampus - Memory System

"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.sh

Install 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 jobs

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

PREPROCESS → SCORE → SEMANTIC CHECK → REINFORCE or CREATE → DECAY

Key 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 RAG

Scripts

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
\x3C0.2 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

Event Logging

Track hippocampus activity over time for analytics and debugging:

# Log an encoding run
./scripts/log-event.sh encoding new=3 reinforced=2 total=157

# Log decay
./scripts/log-event.sh decay decayed=154 low_importance=5

# Log recall
./scripts/log-event.sh recall query="user preferences" results=3

Events append to ~/.openclaw/workspace/memory/brain-events.jsonl:

{"ts":"2026-02-11T10:00:00Z","type":"hippocampus","event":"encoding","new":3,"reinforced":2,"total":157}

Use this for:

  • Trend analysis (memory growth over time)
  • Debugging encoding issues
  • Building dashboards

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.

安全使用建议
What to consider before installing: - Review source first: the skill's homepage is unknown and owner is anonymous — inspect every script (already included) before running any installer. The code is local, so you can audit it first. - Don't add the gateway systemPrompt or enable the 'WITH_AGENT' path until you trust the code: the skill recommends modifying OpenClaw gateway config to create a background agent with a persistent systemPrompt — this is effectively a system-level prompt override and can persist arbitrary instructions. - Avoid enabling cron or automatic agent creation on first install. Run ./install.sh without --with-cron, and run encode/decay manually to test behavior. - Limit initial scope: use ./install.sh --signals N (small N) or run encode-pipeline.sh with --no-spawn to avoid spawning sub-agents, and verify what gets written to $WORKSPACE/memory before allowing periodic runs. - Sandbox the workspace: consider running in an isolated account or VM and point WORKSPACE to a temporary directory to observe what is captured and written. - Protect stored data: memory files will contain potentially sensitive user messages. Ensure proper filesystem permissions, add memory/ to .gitignore, and consider encrypting or routinely purging stored memories that contain PII. - Audit sub-agent invocation: encode-pipeline/summarize-pending spawn sub-agents (openclaw sessions/spawn). If you do not want autonomous model calls, avoid using the spawn paths or run summarization manually. - If you need persistent background processing, prefer adding a supervised cron that runs one-off scripts (no systemPrompt changes) and monitor logs; do not grant the skill unrestricted background agent privileges. Summary recommendation: the package is functionally coherent for a memory system but includes privileged persistence instructions and a prompt-override pattern; treat it as suspicious until you review and constrain the installation (no gateway/systemPrompt changes, no cron/agent auto-creation, sandboxed workspace).
功能分析
Type: OpenClaw Skill Name: hippocampus Version: 3.9.0 The skill is designed for AI agent memory management, involving extensive local file I/O and internal prompt injection for self-management. However, the `scripts/generate-dashboard.sh` script contains a Local File Disclosure vulnerability. It reads the `AVATAR_PATH` from `IDENTITY.md` and, if this path is manipulated (e.g., to `/etc/passwd` or `~/.ssh/id_rsa`), it will base64 encode the content of the specified file and embed it into the locally generated `brain-dashboard.html`. This allows for potential unauthorized access to sensitive local files if the `IDENTITY.md` file can be compromised.
能力评估
Purpose & Capability
Name/description (persistent memory/encoding/decay) align with the included scripts and files: python3 and jq are reasonable, scripts read/write a local workspace (~/.openclaw/workspace/memory), score signals, summarize and update an index.json. The only mismatch is the inclusion of guidance to add a background agent in the OpenClaw gateway (systemPrompt snippet) which elevates the skill from a local helper to a persistent, system-level actor — that is plausible for a 'background hippocampus' feature but is a privileged change and should be treated cautiously.
Instruction Scope
SKILL.md, agent instructions, and scripts explicitly instruct the agent to fetch main session history, preprocess all session files, score and summarize user messages, and write persistent memory files. They also instruct adding cron jobs that run encoding every few hours and propose a gateway config systemPrompt to create a separate hippocampus background agent. These steps are coherent with memory capture but broaden the skill's reach: it will persistently monitor conversation history (potentially all sessions) and write local files containing sensitive user content. The SKILL.md contains phrasing and a config snippet that amount to a 'system prompt override' (prompt-injection pattern), which is risky.
Install Mechanism
There is no network download/install of third-party binaries; install.sh and provided scripts operate locally and set up cron entries via openclaw commands (or print commands for manual run). No remote extract-from-URL or npm/go installs were found. That reduces supply-chain risk, but install.sh will make scripts executable, create directories, and (if run with --with-cron) register cron tasks — so inspect the scripts before running and avoid automatic cron/agent creation until reviewed.
Credentials
The skill declares no required environment variables or external credentials. The operational scope (reading session transcripts and local files under ~/.openclaw/workspace) matches the purpose. However, lack of auth does not remove risk: the skill will capture and store potentially sensitive user content locally without further safeguards.
Persistence & Privilege
Although always:false, the skill's install and docs encourage creating persistent cron jobs and (optionally) adding a dedicated background agent via gateway config with a systemPrompt. Adding a systemPrompt or a persistent sub-agent is a privileged change (it can persist instructions and run autonomously on schedule). This combination (automatic capture + persistent systemPrompt) increases blast radius if the skill is malicious or buggy.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install hippocampus
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /hippocampus 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v3.9.0
feat: add event logging for brain analytics
v3.8.4
- Updated skill metadata: changed `name` from `hippocampus-memory` to `hippocampus`. - Clarified description to emphasize background/organ role and separate process. - No functional or code changes; documentation and naming only. - Version bumped to 3.8.4.
v3.8.3
Version 3.8.3 - Updated metadata version in SKILL.md from 3.8.2 to 3.8.3. - No additional user-facing or functional changes documented.
v3.8.2
- Version updated to 3.8.2. - Metadata version number bumped in SKILL.md. - No functional or usage changes; documentation and schema remain the same.
v3.8.1
hippocampus v3.8.1 - Updated version metadata to 3.8.1. - No other functional or content changes.
v3.8.0
- Adds semantic encoding pipeline for memory signals, enabling automatic consolidation and reinforcement without manual scripts. - Introduces brain dashboard generation for visualizing agent memories and brain skills in HTML. - Replaces previous reinforcement script with semantic reinforcement during encoding; eliminates ‘capture.sh’ and ‘reinforce.sh’. - New scripts: `encode-pipeline.sh`, `generate-dashboard.sh`, and `summarize-pending.sh` for improved automation and visibility. - Updates install options, file structure (signals, pending-memories), and cron recommendations to support frequent, LLM-powered memory processing. - Documentation rewritten for new pipeline and dashboard; skill renamed to “hippocampus-memory” for clarity.
v3.2.0
Added AI Brain Series section with links to amygdala (live) and other brain parts
v3.1.1
Memory system with importance scoring, decay, reinforcement
v3.1.0
Clean release: GitHub repo, recall.sh fix, security audit passed
v3.0.2
- Documentation updated with new, more accurate example dates in `memory/index.json` schema. - Minor tweaks to clarify memory structure and importance formulas. - Improved instructions and integration notes for OpenClaw. - No changes to core functionality—this is a documentation and clarity update only.
v3.0.1
- New documentation: SKILL.md now provides detailed setup, usage, and conceptual guide for the hippocampus skill. - Clarifies memory lifecycle, structure, importance scoring, decay/reinforcement logic, and script usage. - Includes practical examples for integration with OpenClaw and agent routines. - Adds clear guidelines for memory capture, trigger phrases, and index schema. - References Stanford Generative Agents as foundational inspiration.
v3.0.0
Major update: Hippocampus 3.0.0 introduces a structured, reinforced memory system for agents. - Implements importance scoring, time-based decay, and reinforcement for all memories. - Defines clear memory lifecycle and folder structure for organization and persistence. - Adds scripts for scoring, decay, reinforcement, and recall; Cron integration for automation. - Documents precise scoring thresholds, formulas, and schema for transparency and configuration. - Direct RAG integration with OpenClaw through HIPPOCAMPUS_CORE.md and index.json export. - Improved usage documentation and capture guidelines for effective agent memory.
元数据
Slug hippocampus
版本 3.9.0
许可证
累计安装 6
当前安装数 6
历史版本数 12
常见问题

Hippocampus 是什么?

Persistent memory system for AI agents. Automatic encoding, decay, and semantic reinforcement — just like the hippocampus in your brain. Based on Stanford Generative Agents (Park et al., 2023). 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 3305 次。

如何安装 Hippocampus?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install hippocampus」即可一键安装,无需额外配置。

Hippocampus 是免费的吗?

是的,Hippocampus 完全免费(开源免费),可自由下载、安装和使用。

Hippocampus 支持哪些平台?

Hippocampus 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Hippocampus?

由 ImpKind(@impkind)开发并维护,当前版本 v3.9.0。

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