four-layer-memory

v1.0.1

四层记忆架构。身份层、工作记忆层、短期日志层、长期存储层分层管理，让记忆既可持续累积，又不会把上下文一次性塞满。

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OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for lingmoon96-dev/four-layer-memory.

Previewing Install & Setup.

Prompt PreviewInstall & Setup

Install the skill "four-layer-memory" (lingmoon96-dev/four-layer-memory) from ClawHub.
Skill page: https://clawhub.ai/lingmoon96-dev/four-layer-memory
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install four-layer-memory

ClawHub CLI

Package manager switcher

npx clawhub@latest install four-layer-memory

Security Scan

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OpenClaw

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high confidence

✓

Purpose & Capability

Name/description (four-layer memory architecture) align with the content of SKILL.md: it documents identity, working, short-term, and long-term layers and how to use them.

Instruction Scope

SKILL.md recommends running python3 scripts/personal_ai_memory.py with commands and references directories (identity/, working-memory/, short-term-logs/, archive/) — but no code files or config paths are included in the package and the skill declared no required paths or env vars. That mismatch means the instructions either expect external files to exist or implicitly require the agent to access/modify local filesystem state; both are not declared.

✓

Install Mechanism

No install spec and no code files — lowest risk for automatic code injection. However, the recommended runtime commands would execute a local Python script if present; the skill itself does not install any binaries.

✓

Credentials

No environment variables, credentials, or config paths are requested. That is proportionate to an instruction-only documentation skill. The concern is the hidden requirement for local scripts/directories which were not declared.

✓

Persistence & Privilege

always is false and the skill is user-invocable; it does not request persistent privileged presence or modification of other skills' configs.

What to consider before installing

This skill is mostly documentation of a memory-layer design, but it instructs the agent to run local Python scripts and read/write named directories that are not included or declared. Before installing or enabling it: 1) ask the publisher for the referenced scripts (scripts/personal_ai_memory.py) and inspect them — do not run them blind; 2) confirm which filesystem paths the skill will use and that those paths don't contain sensitive data; 3) if you want to test, run any provided scripts in a sandboxed environment or container; 4) disable autonomous invocation or limit the agent's shell/file permissions until you verify the code; and 5) if the author cannot supply the scripts or a trustworthy source, treat this skill as incomplete and avoid enabling it.

Like a lobster shell, security has layers — review code before you run it.

latestvk97a9t714xbyh367cvxnk7dbdx83y3nj

106downloads

0stars

2versions

Updated 4w ago

v1.0.1

MIT-0

Four-Layer Memory

分层定义

Identity Layer: 人格锚点、核心身份、长期不变偏好
Working Memory Layer: 当前任务、近期关注、热记忆
Short-Term Log Layer: 每日记录、近期会话、完整回溯
Long-Term Storage Layer: 经确认的偏好、知识、关系和经验

使用原则

稳定信息进 identity/ 或 long-term-memory/
临时任务进 working-memory/
每日会话进 short-term-logs/
过期日志转 archive/

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