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Local Agent Memory v1

作者 lupinweng · GitHub ↗ · v1.0.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install local-agent-memory-v1
功能描述
Build, maintain, or improve a layered local memory system for OpenClaw-style agents using markdown files instead of database-backed memory. Use when creating...
使用说明 (SKILL.md)

Local Agent Memory v1

Build or refine a reliable file-based memory system for an agent.

Core workflow

  1. Create or inspect these layers:
    • memory/YYYY-MM-DD.md
    • memory/semantic/
    • memory/procedural/
    • MEMORY.md
  2. Keep MEMORY.md lightweight and routing-oriented.
  3. Put stable facts in semantic files.
  4. Put repeatable methods in procedural files.
  5. Treat memory as a hint/index layer, not unquestionable truth.
  6. Re-verify current facts before taking real actions based on remembered information.
  7. Write destination files first, then update MEMORY.md only if the change deserves long-term indexing.

Decision rules

Use daily memory for

  • new events
  • one-off attempts
  • temporary troubleshooting detail
  • anything not yet proven reusable

Use semantic memory for

  • stable user preferences
  • durable environment facts
  • platform constraints
  • lasting architecture or governance decisions

Use procedural memory for

  • repeatable workflows
  • checklists
  • maintenance routines
  • methods likely to be reused across sessions

Maintenance pattern

Run a lightweight dream/consolidation pass when memory starts to sprawl:

  • read MEMORY.md
  • read recent daily logs
  • identify repeated facts or workflows
  • extract stable facts into semantic memory
  • extract repeatable methods into procedural memory
  • prune low-value or duplicated summary lines from MEMORY.md

Run a deeper pass for large daily logs or when the topic tree needs restructuring.

Guardrails

  • Do not let MEMORY.md become a diary.
  • Do not promote everything that looks interesting.
  • Do not rely on stale remembered facts for real actions.
  • Do not mix memory maintenance with unrelated code changes unless the user asked for both.
  • Prefer a few clear topic files over many overlapping files.

References

Read these only as needed:

  • references/architecture.md for the memory model and core disciplines
  • references/setup.md for minimum structure and topic layout
  • references/maintenance.md for governance and consolidation rules
安全使用建议
This skill is an instruction-only guide for organizing agent memory as markdown files and appears coherent with that purpose. Before installing or using it, be aware that: the agent following these instructions will read and write files in your workspace (MEMORY.md, memory/*); if you want to limit scope, run the agent in a sandboxed directory or under version control and require explicit permission before any large migrations or bulk edits; ensure backups of important files; and confirm the agent asks for confirmation before making sweeping changes. If you need the agent to avoid reading environment variables or other repositories on disk, state that restriction explicitly in the prompt or workspace policy.
功能分析
Type: OpenClaw Skill Name: local-agent-memory-v1 Version: 1.0.0 The skill bundle provides a structured framework for an AI agent to manage its own long-term memory using local Markdown files (e.g., MEMORY.md, semantic/ and procedural/ directories). It includes clear organizational rules, maintenance workflows, and safety guardrails—such as 'skeptical memory' and 'strict write discipline'—to ensure the agent re-verifies facts before acting. No malicious code, data exfiltration, or harmful prompt injection attempts were found.
能力评估
Purpose & Capability
Name, description, and included reference files describe a local, file-based memory system and the skill does not request unrelated binaries, environment variables, or network access. The requested capabilities align with the stated purpose.
Instruction Scope
SKILL.md and references only instruct reading and writing workspace markdown files (daily, semantic, procedural, and an index). The docs also advise re-verifying facts (e.g., files, paths, versions, environment) before taking actions — this gives the agent discretionary scope to read local files or environment state when verifying, which is reasonable for the task but worth being explicit about and limiting to the agent's workspace unless the user consents.
Install Mechanism
No install spec or code files are present; the skill is instruction-only so nothing is downloaded or written to disk by an installer.
Credentials
The skill declares no required environment variables, credentials, or config paths. The guidance to re-check environment state is contextual and does not imply hidden credential access.
Persistence & Privilege
always is false and the skill does not request persistent system privileges or attempt to modify other skills or global agent configuration. It will rely on the agent executing file I/O when invoked, which is expected for a local memory workflow.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install local-agent-memory-v1
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /local-agent-memory-v1 触发
  4. 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
Initial release: layered local memory, skeptical memory, strict write discipline, governance, and consolidation workflow
元数据
Slug local-agent-memory-v1
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Local Agent Memory v1 是什么?

Build, maintain, or improve a layered local memory system for OpenClaw-style agents using markdown files instead of database-backed memory. Use when creating... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 104 次。

如何安装 Local Agent Memory v1?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install local-agent-memory-v1」即可一键安装,无需额外配置。

Local Agent Memory v1 是免费的吗?

是的,Local Agent Memory v1 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Local Agent Memory v1 支持哪些平台?

Local Agent Memory v1 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 Local Agent Memory v1?

由 lupinweng(@lupinweng)开发并维护,当前版本 v1.0.0。

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