AgentIndex icon
AgentIndex
hmem logo
hmem
★ 24
vs
agent-skill-memories-off logo
agent-skill-memories-off
★ 48

hmem vs agent-skill-memories-off

hmem: hmem is a memory system for AI agents that persists project context across sessions, devices, and AI providers. It uses a 5-level lazy loading architecture to minimize token usage while retaining full details. It supports auto-logging, background checkpoints, and cross-platform sync.; agent-skill-memories-off: memories-off provides a minimalist, structured local knowledge management solution that endows agents with long-term memory. It uses standardized Markdown entities and Git-driven workflows to maintain an auditable, rollbackable knowledge base. The project is designed for personal or small project use, with a focus on portability, readability, and flexibility.

01

TL;DR

hmem logo
hmemMemory & Context · ★ 24

AI coding assistants that need to maintain project context across sessions

Read hmem full review →
agent-skill-memories-off logo
agent-skill-memories-offMemory & Context · ★ 48

Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph

Read agent-skill-memories-off full review →
02

Side-by-Side Comparison

Field
hmem logohmem
agent-skill-memories-off logoagent-skill-memories-off
Category
Memory & Context
Memory & Context
Stars
★ 24
★ 48
License
MIT
Apache-2.0
Install Command
npm install -g hmem-mcp && npx hmem init
cd memories-off-skill && python3 scripts/install.py
Updated
3mo ago
4mo ago
Open Source
Yes
Yes
Website
↗ Visit
↗ Visit
GitHub
↗ GitHub
↗ GitHub
Tags
ai-agents, ai-tools, claude
agent-skills, cli, llm
03

Features

hmem logohmem
015-level lazy loading to minimize token usage
02Automatic session logging and background checkpoints via Haiku
03Cross-provider and cross-tool support
04Project-based memory organization
05Encrypted sync across devices
agent-skill-memories-off logoagent-skill-memories-off
01Lightweight and local-first, no dependency on cloud services
02Structured knowledge via LLM-extracted entities, relations, and observations
03Flexible search by entity name, type, or observation keywords
04Human-readable data with simple backup functionality
04

Use Cases

hmem logohmem
↳AI coding assistants that need to maintain project context across sessions
↳Multi-device workflow where different agents continue the same project
↳Knowledge management for personal AI assistants
agent-skill-memories-off logoagent-skill-memories-off
↳Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph
↳Personalized content generation: leverage the knowledge graph to generate style-consistent communications or documents
↳Project knowledge base: small teams can use it to accumulate project-level knowledge and optimize agent services
FAQ

FAQ

What is the difference between hmem and agent-skill-memories-off?
Both hmem and agent-skill-memories-off are in the Memory & Context category. hmem has 24 stars, while agent-skill-memories-off has 48 stars.
Which is better, hmem or agent-skill-memories-off?
The best choice depends on your use case. Choose hmem if AI coding assistants that need to maintain project context across sessions, and agent-skill-memories-off if Personal knowledge management: extract key points from documents and conversations, build a personal knowledge graph.
Is hmem free or open source?
Yes, hmem is open source on GitHub (MIT).
Is agent-skill-memories-off free or open source?
Yes, agent-skill-memories-off is open source on GitHub (Apache-2.0).
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