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Meshmorize

Name: Meshmorize
Author: mozz0

by mozz0 · GitHub ↗ · v3.1.0 · MIT-0

cross-platform ✓ Security Clean

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Install in OpenClaw

/install meshmorize

Description

🧠 Multi-layer memory system: fresh layer, mesh graph, auto-log, cross-layer search, compliance check

README (SKILL.md)

MeshMorize 🧠

Multi-layer memory system for LLM agents. Fresh daily layer, mesh graph indexing, auto-logging, cross-layer search, and full compliance checks.

Built for OpenClaw. Works with any agent that can run Python.

Layers

Layer	File	Purpose
Fresh	`memory/fresh/today.md`	Daily notes, 5-day rotation
Mesh	`memory/mesh.json`	Graph nodes + search index
Log	`scripts/auto_log`	Auto-log every interaction
Search	`scripts/memory_search`	Cross-layer search (fresh → daily → mesh → raw → long-term)
Check	`scripts/memory_check`	10-point compliance check (`memcheck`)

Quick start

mem-bridge init          # Rotate fresh layer, create today.md
auto_log "msg" "reply"   # Log an interaction
memory_search "query"    # Search all memory layers
memcheck                 # Full 10-point compliance check

Tools

Tool	Source
`mem-bridge`	`memory/bridge.py` — fresh-layer rotation + checkpoint management
`auto_log`	`scripts/auto_log.py` — interaction logger
`memory_search`	`scripts/memory_search.py` — multi-layer search across all memory stores
`memcheck`	`scripts/memory_check.py` — 10-point compliance check runner

Install

Put bridge.py in memory/ and scripts in scripts/ of your agent workspace. Symlink or add to PATH:

ln -s $(pwd)/scripts/* ~/.local/bin/
ln -s $(pwd)/memory/bridge.py ~/.local/bin/mem-bridge

On session start, run:

mem-bridge init

Source

https://github.com/mozz0/MeshMorize

Made by mozz0 · Released under MIT

Usage Guidance

Install only if you want an agent memory system that can retain interaction logs across sessions. Review what the missing companion scripts do before running them, avoid logging secrets or regulated data, and remove the ~/.local/bin symlinks and workspace memory files if you later uninstall it.

Capability Tags

crypto

Capability Assessment

✓ Purpose & Capability

The skill is explicitly about multi-layer agent memory, auto-logging, fresh-layer rotation, graph indexing, and search; these capabilities are coherent with the advertised purpose.

ℹ Instruction Scope

The instructions tell the agent to log interactions and run initialization at session start, which is broad but plainly stated and tied to the memory workflow.

ℹ Install Mechanism

Install steps create symlinks in ~/.local/bin and expect memory/scripts directories in the agent workspace; this modifies the local filesystem but is visible and limited to making the tools runnable.

✓ Credentials

The artifact is a single SKILL.md with no bundled executable scripts, no credential collection, no network automation, and no hidden install behavior.

ℹ Persistence & Privilege

Persistent storage is central to the skill, with files such as memory/fresh/today.md and memory/mesh.json documented, though users should understand that logged prompts and replies may persist beyond a session.

How to Use

Make sure OpenClaw is installed (local or Docker)
Run the install command in chat: /install meshmorize
After installation, invoke the skill by name or use /meshmorize
Provide required inputs per the skill's parameter spec and get structured output

Version History

v3.1.0

Major update: MeshMorize 3.1.0 introduces a new multi-layer memory system, replacing the previous self-improvement logging workflow. - Fully rewrote documentation and workflow in SKILL.md for the "MeshMorize" system. - Added support for a daily "fresh" memory layer, mesh graph indexing, auto-logging, and cross-layer search. - Introduced 10-point compliance checks and streamlined tool usage (mem-bridge, auto_log, memory_search, memcheck). - Removed legacy docs, templates, hooks, scripts, and references related to self-improvement logging and OpenClaw integration. - Simplified installation and setup instructions for agent-agnostic deployment.

v1.0.0

MeshMorize 1.0.0 – Initial release - Introduces a multi-layer memory system with daily (fresh), mesh graph, and auto-log layers. - Supports cross-layer memory search (from fresh to long-term storage). - Includes a 10-point compliance check for memory operations. - Provides command-line tools for initialization, logging, searching, and compliance checks. - Compatible with OpenClaw and any Python-based agent architecture.

Metadata

Slug meshmorize

Version 3.1.0

License MIT-0

All-time Installs 0

Active Installs 0

Total Versions 2

Frequently Asked Questions

What is Meshmorize?

🧠 Multi-layer memory system: fresh layer, mesh graph, auto-log, cross-layer search, compliance check. It is an AI Agent Skill for Claude Code / OpenClaw, with 40 downloads so far.

How do I install Meshmorize?

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

Is Meshmorize free?

Yes, Meshmorize is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Meshmorize support?

Meshmorize is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Meshmorize?

It is built and maintained by mozz0 (@mozz0); the current version is v3.1.0.

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