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memory-management内存管理

Agent Skill

memory-management 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

194

周安装

8

GitHub Stars

267

下载量

63
CodexClaudeCursorGemini CLI

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

unknown

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:memory-management(内存管理)
来源仓库:https://github.com/ninehills/skills
仓库路径:skills/memory-management
安装命令:
npx skills add https://github.com/ninehills/skills --skill memory-management
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/ninehills/skills --skill memory-management

简介

memory-management 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中快速定位候选结果。

  • 适用于关键词搜索、任务场景匹配或来源线索筛选等研究检索场景。
  • 通过 npx skills add 命令从 GitHub 仓库安装,需结合原始 README 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或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

Memory Management Skill

Alma has a built-in memory system with semantic search. Use the alma CLI to interact with it.

Commands

# List all memories
alma memory list

# Semantic search
alma memory search <query>

# Add a memory
alma memory add <content>

# Delete a memory
alma memory delete <id>

# View memory stats
alma memory stats

When to Use

  • User asks anything about the past ("do you know what I like", "what did we discuss before", "what was that plan we talked about last time") → Search memories AND grep threads
  • User says "remember this"alma memory add "..."
  • User asks "do you remember..."alma memory search "..." + alma memory grep "..."
  • User says "forget about..." → Search and delete matching memories
  • Time-sensitive info (projects, deadlines) → Store with appropriate context

Search Strategy

When the user asks about past information, always try both layers:

  1. alma memory search "<query>" — semantic search for related concepts
  2. alma memory grep "<keyword>" — keyword search in conversation history

If one layer returns nothing, try the other. They complement each other.

Conversation History Search

Alma automatically archives all threads as markdown files. You can search through past conversations:

# Keyword search through all archived conversations
alma memory grep <keyword>

# Force re-archive all threads now
alma memory archive

Thread archives are stored in the workspace's threads/ directory as markdown files with YAML frontmatter (threadId, title, createdAt, updatedAt, model, messageCount). Archives are auto-updated every 5 minutes.

Two-Layer Memory

  1. Vector Memory (alma memory search) — semantic search, finds conceptually related memories
  2. Conversation Archives (alma memory grep) — keyword search, finds exact words/phrases in past conversations

Use vector search when the user asks vague questions ("what did we discuss about React?"). Use grep when looking for specific terms, names, or code snippets.

Group Chat History

Alma persists all group chat messages to log files. Search and browse them:

# List all known groups
alma group list

# View recent history (default 50 messages)
alma group history <chatId> [limit]

# Search across all group chats
alma group search <keyword>

Log files are stored at ~/.config/alma/groups/<chatId>_<date>.log. Use this when you need to recall what was discussed in a group chat.

People Profiles (Per-Person Memory)

For group chats, Alma maintains structured per-person profiles — more reliable than vector search for remembering who is who.

# List all known people
alma people list

# View someone's profile
alma people show <name>

# Set/overwrite profile
alma people set <name> <content>

# Append to profile
alma people append <name> <fact>

# Delete profile
alma people delete <name>

When to update profiles:

  • Someone shares personal info (job, hobbies, preferences)
  • You learn their communication style or language preference
  • They mention relationships with other people
  • Any fact you'd want to remember next time you talk to them

Profiles are stored at ~/.config/alma/people/<name>.md and automatically loaded into group chat context.

Tips

  • Always confirm what you stored/deleted with the user
  • Use alma memory search to find related memories before adding duplicates
  • Memories are automatically injected into conversations via semantic search — you don't need to manually recall them every time
  • Use alma memory grep to search through conversation history when vector search doesn't find what you need
  • For per-person facts, prefer alma people over alma memory — structured and won't get mixed up

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

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

Codex

39.17%
按下载量换算25

Claude

30%
按下载量换算19

Cursor

18.57%
按下载量换算12

Gemini CLI

10.04%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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