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claw-mem: Three-Tier Memory

by Peter Cheng · GitHub ↗ · v2.0.1 · MIT-0
cross-platform ✓ Security Clean
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Install in OpenClaw
/install opensourceclaw-claw-mem
Description
Three-Tier Memory System for OpenClaw. Store and recall memories across sessions with Episodic, Semantic, and Procedural layers. BM25 + Heuristic retrieval.
README (SKILL.md)

claw-mem: Three-Tier Memory System

Local-first memory system with three memory layers and intelligent retrieval.

Prerequisites

pip install git+https://github.com/opensourceclaw/claw-mem.git

Quick Start

Search Memory

python3 {baseDir}/scripts/search.py "project deadlines" --limit 10

Store Memory

python3 {baseDir}/scripts/store.py "User preference" --category preference

Start Bridge (for OpenClaw integration)

python3 {baseDir}/scripts/bridge.py --workspace ~/.openclaw/workspace

Memory Layers

Layer Purpose Example
Episodic Event sequences Session context
Semantic Knowledge facts User preferences
Procedural Rules Best practices

Retrieval Modes

Mode Description Use Case
keyword Simple keyword match Quick lookup
bm25 BM25 ranking Relevance ranking
hybrid BM25 + Keyword Balanced retrieval
enhanced_smart Full pipeline Best quality

Set mode via environment:

export CLAW_MEM_SEARCH_MODE=enhanced_smart

Configuration

OpenClaw config (openclaw.config.json):

{
  "plugins": {
    "slots": {
      "memory": "claw-mem"
    },
    "claw-mem": {
      "config": {
        "workspaceDir": "~/.openclaw/workspace",
        "autoRecall": true,
        "autoCapture": true,
        "topK": 10
      }
    }
  }
}

Performance

Operation Latency
Initialize ~4ms
Store ~8ms
Search ~5ms
Average ~6ms

Advanced

See references for detailed documentation:

Usage Guidance
This skill appears coherent for a local memory plugin, but take the following precautions before installing: 1) Review the upstream GitHub repo (https://github.com/opensourceclaw/claw-mem) because pip install from a git URL runs code from that repository during install. 2) Install into an isolated environment (virtualenv) to limit impact. 3) Be aware it persists data to ~/.openclaw/workspace (SQLite files) — avoid storing sensitive secrets there and consider its autoCapture/autoRecall settings. 4) If you need stronger assurance, inspect the full claw_mem package source (especially any network code or RPC bridge implementation) before running the bridge. Otherwise the package and included scripts are proportionate to the stated purpose.
Capability Analysis
Type: OpenClaw Skill Name: opensourceclaw-claw-mem Version: 2.0.1 The claw-mem skill bundle provides a legitimate three-tier memory system (Episodic, Semantic, Procedural) for OpenClaw agents. The scripts (bridge.py, search.py, store.py) and documentation (SKILL.md, architecture.md) are consistent with the stated purpose of local-first memory management using SQLite, and no indicators of data exfiltration, malicious execution, or prompt injection were found.
Capability Tags
crypto
Capability Assessment
Purpose & Capability
Name/description, SKILL.md, and the three scripts all align: they implement a local memory system, rely on a Python package named 'claw_mem', and operate on a workspace directory. No unrelated credentials, binaries, or system-wide config are requested.
Instruction Scope
Runtime instructions limit actions to installing the package, running the provided scripts, and configuring a workspace path and a search-mode env var. The SKILL.md does not instruct reading unrelated files, harvesting environment secrets, or posting data to third-party endpoints.
Install Mechanism
The README recommends pip installing directly from the GitHub repository (git+https://github.com/opensourceclaw/claw-mem.git). That is a common and expected install path but it does execute code from that remote repository at install-time — review the upstream repository before running pip install.
Credentials
No required environment variables or credentials are declared. Only a search-mode env var (CLAW_MEM_SEARCH_MODE) is suggested, and the scripts use a local workspace path (~/.openclaw/workspace) for SQLite persistence. No disproportionate secret access is requested.
Persistence & Privilege
Skill is not forced always-on and does not request elevated system privileges. It will read/write local SQLite DBs in the specified workspace (episodic.db, semantic.db, procedural.db) which is expected for a memory plugin. Note: the default config in SKILL.md enables autoCapture/autoRecall, which means the plugin will persist conversation data if enabled.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install opensourceclaw-claw-mem
  3. After installation, invoke the skill by name or use /opensourceclaw-claw-mem
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v2.0.1
- Improved SKILL.md for clarity and conciseness - Updated installation instructions to use git+https URL - Simplified descriptions of memory layers and retrieval modes - Removed mention of the 'entity' and 'heuristic' retrieval modes - Updated example commands for consistency
v2.0.0
claw-mem 2.0.0 introduces a three-tier memory system and enhanced retrieval features for OpenClaw agents. - Adds Episodic, Semantic, and Procedural memory layers for structured fact, event, and rule storage. - Supports versatile retrieval modes: keyword, BM25, hybrid, entity, heuristic, and enhanced_smart. - Enables local, session-persistent memory storage with fast performance (average latency ~6ms). - Simplifies configuration and OpenClaw integration via dedicated scripts and example configs. - Provides clear documentation for setup, memory layers, retrieval, and advanced usage.
Metadata
Slug opensourceclaw-claw-mem
Version 2.0.1
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is claw-mem: Three-Tier Memory?

Three-Tier Memory System for OpenClaw. Store and recall memories across sessions with Episodic, Semantic, and Procedural layers. BM25 + Heuristic retrieval. It is an AI Agent Skill for Claude Code / OpenClaw, with 78 downloads so far.

How do I install claw-mem: Three-Tier Memory?

Run "/install opensourceclaw-claw-mem" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is claw-mem: Three-Tier Memory free?

Yes, claw-mem: Three-Tier Memory is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does claw-mem: Three-Tier Memory support?

claw-mem: Three-Tier Memory is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created claw-mem: Three-Tier Memory?

It is built and maintained by Peter Cheng (@petercheng); the current version is v2.0.1.

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