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adam-framework亚当框架

Agent Skill

adam-framework 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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

6,915

周安装

294

GitHub Stars

公开资料未说明

下载量

2,423
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:adam-framework(亚当框架)
来源仓库:https://github.com/strangeadvancedmarketing/adam-framework
安装命令:
openclaw skills install adam-framework
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 adam-framework

简介

构建 OpenClaw 代理的持久内存架构,解决健忘与漂移问题。

  • 适用于需要跨会话一致性与记忆保持的场景。
  • 采用五层存储模型,支持长期上下文维护与验证。
  • 需评估存储成本与数据同步机制可靠性。
  • 建议在小规模会话中先行测试稳定性。adam-framework 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
adam-framework
description
5-layer persistent memory and coherence architecture for OpenClaw agents. Solves AI amnesia and within-session drift. Built and validated over 353 sessions on a live business. No CS degree required.
tags
[memory, persistence, identity, coherence, vault, neural-graph, local-first]

Adam Framework

AI Amnesia — Solved. Within-Session Coherence Degradation — Solved.

The Adam Framework is a 5-layer persistent memory architecture for OpenClaw agents, developed over 8 months across 353 sessions on a live business by a non-coder running consumer hardware.

OpenClaw just got acquired by OpenAI. Your memory layer shouldn't be.

What It Solves

  • AI Amnesia — your agent wakes up blank every session, forcing you to re-explain context, projects, and goals that should already be known
  • Within-Session Drift — as a session accumulates context, the model's reasoning consistency quietly degrades before compaction triggers

The 5 Layers

LayerComponentWhat It Does
1Vault injection via SENTINELIdentity files loaded at every boot. Agent wakes up knowing who it is.
2memory-core pluginLive memory search mid-session via memory_search / memory_get tools
3Neural graph (nmem_context)Associative recall — 12,393 neurons, 40,532 synapses. Concepts link to concepts.
4Nightly reconciliationGemini merges daily logs into CORE_MEMORY.md while you sleep. Nothing lost.
5Coherence monitorScratchpad dropout detector — fires re-anchor before drift causes damage. 33 tests passing.

The Key Insight

The memory is in the files. The model is just the reader.

When the system was completely wiped and rebuilt from scratch, the agent came back online with full continuity — because the identity files survived. Swap the LLM, keep the Vault. Memory persists.

Setup

Two paths — pick one:

Path 1 — You do it yourself (30–60 min) Read SETUP_HUMAN.md. Plain English, no technical background assumed.

Path 2 — Let your agent handle it Paste SETUP_AI.md into your OpenClaw chat. It asks 8 questions and does the install itself.

Prerequisites

  • OpenClaw running with any model
  • Python 3.10+
  • npm install -g mcporter
  • NVIDIA Developer free tier API key (Kimi K2.5, 131K context, free)
  • Gemini API key (free) for nightly reconciliation

Links

  • Repo: https://github.com/strangeadvancedmarketing/Adam
  • Live proof (353 sessions): https://strangeadvancedmarketing.github.io/Adam/showcase/ai-amnesia-solved.html
  • Full setup guide: https://github.com/strangeadvancedmarketing/Adam/blob/master/SETUP_HUMAN.md

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

91.48%
按下载量换算2,217

安全审计

VirusTotal

可疑

ClawScan

可疑

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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