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openclaw-memoriaOpenClaw memoria 搜索

Agent Skill

openclaw-memoria 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

9,792

周安装

368

GitHub Stars

2

下载量

3,136
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:openclaw-memoria(OpenClaw memoria 搜索)
来源仓库:https://github.com/nieto42/openclaw-memoria
安装命令:
openclaw skills install openclaw-memoria
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install openclaw-memoria

简介

openclaw-memoria 是基于先进认知层的 AI 代理记忆系统。

  • 适合复杂知识管理和自我学习优化的长期任务。
  • 包含知识图谱、程序学习和辩证查询等高级功能。
  • 安装命令为 openclaw skills install openclaw-memoria,需远程 LLM API 支持。
  • 注意 API 调用成本和响应延迟对任务效率的影响。

SKILL.md

name
Memoria for OpenClaw
version
3.34.0
description
The most advanced memory system for AI agents. 24 cognitive layers, knowledge graph, procedural learning, dialectic queries, AI self-observation, auto skill creation, crash-safe WAL, async prefetch. Works with Claude, Cursor, Copilot, ChatGPT & any OpenClaw agent. 100% local-first (SQLite + Ollama), zero cloud cost, zero API keys required.
author
Primo Studio (@Nieto42)
license
Apache-2.0
homepage
https://github.com/Primo-Studio/openclaw-memoria
repository
https://github.com/Primo-Studio/openclaw-memoria
feedback
https://x.com/Nitix_
keywords
tags
env
required
false
description
Optional — used as fallback for LLM extraction and embeddings when local models are unavailable. Never required for default operation.
required
false
description
Optional — used as fallback for remote LLM provider. Never required for default operation.
required
false
description
Auto-set by OpenClaw runtime — workspace path for memory files. Do not set manually.
security
|
entrypoint
index.ts

🧠 Memoria — Multi-Layer Persistent Memory for OpenClaw

The most complete memory system for OpenClaw. 20 layers of memory that work together, powered by YOUR choice of LLM.

Why Memoria?

🏗️ 20 Memory Layers (not just a fact store)

  1. Facts — Durable knowledge extracted from every conversation
  2. Procedures — HOW to do things, improves with repetition, learns from failures
  3. Knowledge Graph — Entities + relations connecting your facts
  4. Topics & Expertise — Tracks what you talk about most, specializes over time
  5. Observations — Short-term working memory for active context
  6. Error Detection 🔥 — Touch fire once, remember forever. Dangers captured on first occurrence
  7. Lifecycle — Fresh → Settled → Dormant. Nothing deleted, priority shifts naturally

🔌 Bring Your Own LLM

Configure each layer independently. Mix and match:

  • Ollama — Run gemma3, qwen3.5, llama, or any model locally (recommended)
  • LM Studio — Use any GGUF model from your local server
  • Remote APIs — OpenAI, Anthropic, OpenRouter as primary or fallback
  • Fallback chains — Ollama → LM Studio → API. If one fails, the next takes over automatically

🏠 100% Local-First

  • SQLite + FTS5 — No external database needed
  • Local embeddings — nomic-embed-text via Ollama (zero API cost)
  • Zero cloud dependency — Works offline, your data stays on your machine
  • Fallback chain — Degrades gracefully if a provider goes down

🧬 What Makes Memoria Different

FeatureMemoriaBasic memory plugins
Memory layers20 specialized layersSingle fact store
LLM choiceAny local or remote modelUsually hardcoded
Per-layer LLM config✅ Different model per layer
Procedural learning✅ Learns HOW, not just WHAT
Error detection✅ Auto-captures dangers
Knowledge graph✅ Entities + relations
Lifecycle management✅ Smart aging, never forgets❌ or simple TTL
Cost$0 with local modelsVaries

Installation

As Plugin (recommended — one command)

openclaw plugins install clawhub:memoria-plugin

This installs Memoria from the ClawHub registry. No manual steps needed.

From source (for contributors / advanced users)

If you prefer to inspect the code first:

  1. Browse the repository: github.com/Primo-Studio/openclaw-memoria
  2. Review the source code, especially index.ts (main entrypoint) and openclaw.plugin.json (config schema)
  3. Clone and install:
cd ~/.openclaw/extensions
git clone https://github.com/Primo-Studio/openclaw-memoria.git memoria
cd memoria && npm install

Then add to your openclaw.json under plugins.entries:

{
  "memoria": { "enabled": true },
  "memory-convex": { "enabled": false }
}

Configuration

Minimal (works out of the box with Ollama)

Just install and restart. Defaults: Ollama + gemma3:4b for extraction, nomic for embeddings.

Custom LLM per layer

"memoria": {
  "enabled": true,
  "config": {
    "llm": {
      "default": { "provider": "ollama", "model": "qwen3.5:4b" },
      "procedural": { "provider": "lmstudio", "model": "your-model" },
      "graph": { "provider": "openai", "model": "gpt-4o-mini" }
    }
  }
}

Source Code

The full source is available on GitHub: Primo-Studio/openclaw-memoria

Key files:

  • index.ts — Main plugin entrypoint (hooks, extraction, recall pipeline)
  • procedural.ts — Procedural memory (how-to learning)
  • lifecycle.ts — Lifecycle management (fresh/settled/dormant)
  • scoring.ts — Temporal scoring and relevance ranking
  • selective.ts — Dedup, contradiction detection, fact quality
  • openclaw.plugin.json — Configuration schema

Feedback & Community

We'd love your feedback! Tell us how Memoria works for you:

Built with ❤️ by Primo Studio 🇬🇫 — AI tooling from French Guiana.

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

95.04%
按下载量换算2,980

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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