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Memory Tiering
作者
SarielWang93
· GitHub ↗
· v1.0.0
16085
总下载
9
收藏
148
当前安装
1
版本数
在 OpenClaw 中安装
/install memory-tiering
功能描述
Automated multi-tiered memory management (HOT, WARM, COLD). Use this skill to organize, prune, and archive context during memory operations or compactions.
安全使用建议
Install this if you want automated memory cleanup. Before relying on it, consider asking the agent to preview or back up memory changes before pruning, and avoid keeping raw secrets in memory files.
功能分析
Type: OpenClaw Skill
Name: memory-tiering
Version: 1.0.0
The skill bundle is benign. It defines a memory tiering system for an AI agent, instructing it to read and write to internal memory files (`memory/hot/HOT_MEMORY.md`, `memory/warm/WARM_MEMORY.md`, `MEMORY.md`, `memory/YYYY-MM-DD.md`). The instructions in `SKILL.md` are clear, directly related to the stated purpose, and do not contain any prompt injection attempts, malicious execution patterns, data exfiltration, or persistence mechanisms. Notably, an instruction regarding 'credentials in HOT' advises the agent to point to root files rather than storing raw secrets, which is a security-positive directive.
能力评估
Purpose & Capability
The stated purpose is automated HOT/WARM/COLD memory tiering, and the artifact instructions directly match that purpose by reading memory tiers, redistributing context, summarizing, pruning, and archiving.
Instruction Scope
The scope is disclosed in SKILL.md, including all three memory tiers and recent daily logs, but it also triggers automatically after /compact and can remove granular COLD-memory details.
Install Mechanism
The bundle contains only SKILL.md; no executable scripts, install hooks, package dependencies, binaries, or hidden setup behavior were found.
Credentials
Reading memory files and daily logs is proportionate for memory tiering. The credential instruction is security-positive because it advises pointing to root files instead of storing raw secrets.
Persistence & Privilege
The skill intentionally changes durable memory by moving, summarizing, and pruning content. That is expected for the purpose, but it may affect what future sessions remember.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install memory-tiering - 安装完成后，直接呼叫该 Skill 的名称或使用
/memory-tiering触发 - 根据 Skill 的参数说明提供必要输入，即可获得结构化输出
版本历史
v1.0.0
memory-tiering 1.0.0
- Introduces dynamic, three-tiered memory management: HOT, WARM, and COLD.
- Automates context organization, pruning, and archival using a structured workflow.
- Supports both manual and automatic triggers (e.g., after compaction).
- Enhances retrieval efficiency and context relevance by enforcing tier redistribution and summarization steps.
元数据
常见问题
Memory Tiering 是什么？
Automated multi-tiered memory management (HOT, WARM, COLD). Use this skill to organize, prune, and archive context during memory operations or compactions. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 16085 次。
如何安装 Memory Tiering？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install memory-tiering」即可一键安装，无需额外配置。
Memory Tiering 是免费的吗？
是的，Memory Tiering 完全免费（开源免费），可自由下载、安装和使用。
Memory Tiering 支持哪些平台？
Memory Tiering 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 Memory Tiering？
由 SarielWang93（@sarielwang93）开发并维护，当前版本 v1.0.0。
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