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Simplemem

Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval

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Efficient Lifelong Memory for LLM Agents - semantic compression, cross-session memory, and intent-aware retrieval

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Install for OpenClaw

Quick setup

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Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: data/memories.json, simplemem.py, SKILL.md

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Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.1

Provenance

Publisher: nantes
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 9 sections Open source page

SimpleMem Skill

Integrates SimpleMem: Efficient Lifelong Memory for LLM Agents into OpenClaw.

What it does

SimpleMem provides semantic memory compression and retrieval for agents: Store: Compresses interactions into compact memory units Synthesize: Merges related memories on-the-fly Retrieve: Intent-aware planning for efficient context retrieval

Installation

# Install Python dependency pip install simplemem # Or via repo git clone https://github.com/aiming-lab/SimpleMem.git cd SimpleMem pip install -r requirements.txt

Configuration (Optional - Full Features)

For full SimpleMem features, set your OpenAI API key: $env:OPENAI_API_KEY = "your-openai-key" Without API key: Uses JSON fallback (basic keyword search) With API key: Uses full SimpleMem with semantic embeddings

PowerShell Script

# Agregar memoria .\simplemem.ps1 -Action add -Content "El usuario prefiere cafe con leche de avena" # Buscar memorias .\simplemem.ps1 -Action search -Query "cafe" # Ver estadisticas .\simplemem.ps1 -Action stats

Python API

from simplemem import SimpleMemSystem, set_config, SimpleMemConfig # With API key (full features) config = SimpleMemConfig() config.openai_api_key = "your-key" set_config(config) system = SimpleMemSystem() # Add memory system.add("User preference: coffee with oat milk", user_id="user1") # Retrieve results = system.retrieve("What does user like?", user_id="user1")

Key Features

Cross-session memory: Persistent across conversations (64% better than Claude-Mem) Semantic compression: 43.24% F1 on LoCoMo benchmark Fast retrieval: 388ms average retrieval time Multi-index: Semantic + Lexical + Symbolic layers Fallback: JSON-based storage when no API key available

Files

simplemem.py - Main Python wrapper simplemem.ps1 - PowerShell CLI script data/ - Storage directory (created on first use)

Credits

Repo: https://github.com/aiming-lab/SimpleMem Paper: https://arxiv.org/abs/2601.02553 Discord: https://discord.gg/KA2zC32M

Category context

Agent frameworks, memory systems, reasoning layers, and model-native orchestration.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package

1 Docs1 Scripts1 Config

SKILL.md Primary doc
simplemem.py Scripts
data/memories.json Config