Token导航 LogoToken导航TokenDH.com
效率敏感数据clawhub未标认证来源可访问clear审计通过

agent-local-memoryAgent 本地内存

Agent Skill

agent-local-memory 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

13,332

周安装

550

GitHub Stars

2

下载量

4,356
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:agent-local-memory(Agent 本地内存)
来源仓库:https://github.com/siyu-hu/agent-local-memory
安装命令:
openclaw skills install agent-local-memory
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 agent-local-memory

简介

为跨对话提供基于文件的持久本地存储。agent-local-memory 属于效率类 Skill,可作为该场景下的辅助能力补充。

  • 零外部依赖,适合轻量级记忆增强需求。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 自动响应“记住”类指令并归档关键信息。
  • 注意文件读写权限与并发访问冲突风险。
  • 建议定期清理过期条目以控制存储空间。

SKILL.md

name
agent-local-memory
description
>
metadata
version
1.0
tags
label
Memory Management
label
Cross-Session Persistence
label
Claude Code / OpenClaw

Agent Local Memory

Persistent local memory across conversations — store user preferences, project context, and behavioral feedback as plain files. No external services, no network calls, no credentials required.

Storage Paths

PlatformDefault Memory Path
Claude Code~/.claude/memory/
OpenClaw~/.openclaw/memory/
Cross-platform~/.agent-memory/

MEMORY.md Index

Maintain a MEMORY.md file in the memory directory as a persistent index:

  • Each memory = one .md file with YAML frontmatter (name / description / type)
  • MEMORY.md stores only links to memory files + one-line descriptions, never full content
  • Trim and merge old entries when the index exceeds 200 lines

At conversation start: Check whether MEMORY.md exists. If it does, read the index and surface relevant memories to the user.

Before context limit: Proactively write important content from the current session into memory files and update MEMORY.md, so the next session can resume seamlessly.

Memory File Format

---
name: memory-name
description: One-line summary (used to assess relevance from the index)
type: user | feedback | project | reference
---

Memory content here.

Four Memory Types

user — User Profile

Stores the user's role, goals, preferences, and knowledge background.

When to write: When you learn about the user's role, tech stack, or communication style.

---
name: user_profile
description: Senior Go engineer, new to React frontend
type: user
---

- 10 years of Go experience, strong backend background
- Just getting started with React — frame frontend concepts as backend analogues
- Communication style: concise and direct, dislikes verbose explanations

feedback — Behavior Correction

Records behaviors the user has corrected. Highest priority — always follow these rules in future sessions.

When to write: When the user says "don't do that", "stop doing…", or any explicit correction.

Lead with the rule, then **Why:** (reason given) and **How to apply:** (scope).

---
name: feedback_no_db_mock
description: Integration tests must use a real database, never mocks
type: feedback
---

Integration tests must connect to a real database — mocking is not allowed.

**Why:** A prior incident where mocked tests passed but the prod migration failed.

**How to apply:** Any test involving database operations must connect to the test database directly.

project — Project Context

Records goals, key decisions, owners, and deadlines that cannot be inferred from the codebase.

When to write: When you learn the motivation behind a decision, a milestone, or a constraint.

Always convert relative dates ("next Friday") to absolute dates before writing.

---
name: project_auth_rewrite
description: Auth middleware rewrite is compliance-driven, not tech debt
type: project
---

Auth middleware rewrite. Target completion: 2026-04-01.

**Why:** Legal flagged session token storage as non-compliant with new regulations.

**How to apply:** Scope decisions should prioritize compliance over engineering elegance.

reference — External Resources

Records locations and purposes of external systems for quick lookup.

When to write: When you learn about a Linear project, Slack channel, dashboard, or any external resource.

---
name: ref_linear_bugs
description: Pipeline bugs tracked in Linear project INGEST
type: reference
---

Pipeline bugs are tracked in Linear project "INGEST". Check there before investigating data pipeline issues.

Write Rules

Before writing, scan MEMORY.md — update an existing entry if one applies, do not create duplicates.

Never write to memory:

  • Passwords, API keys, tokens, or any credentials
  • Secrets, private keys, or sensitive authentication data
  • Code structure, file paths, or architecture conventions (derivable from the codebase)
  • Temporary state from the current conversation
  • Anything already in project documentation or git history

Conversation Start Prompt

If MEMORY.md exists, output at conversation start:

Local memory detected (N entries). Relevant memories: [list]

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

83.31%
按下载量换算3,629

安全审计

VirusTotal

通过

ClawScan

通过

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。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

继续浏览同类 Skills