Token导航 LogoToken导航TokenDH.com
研究检索只读github未标认证来源可访问许可证需确认审计通过

memory-defrag内存碎片整理

Agent Skill

memory-defrag 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

6,115

周安装

245

GitHub Stars

18

下载量

1,980
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-defrag(内存碎片整理)
来源仓库:https://github.com/basicmachines-co/basic-memory-skills
仓库路径:skills/memory-defrag
安装命令:
npx skills add https://github.com/basicmachines-co/basic-memory-skills --skill memory-defrag
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/basicmachines-co/basic-memory-skills --skill memory-defrag

简介

memory-defrag 用于重组记忆文件,提升知识管理的清晰度和效率。

  • 类似文件系统碎片整理,但针对知识库进行结构优化。
  • 支持定期自动运行或按需手动触发,适用于大规模记忆库维护。
  • 当 MEMORY.md 超过 500 行或日常笔记积累过多时建议执行。
  • 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 Defrag

Reorganize memory files for clarity, efficiency, and relevance. Like filesystem defragmentation but for knowledge.

When to Run

  • Periodic: Weekly or biweekly via cron (recommended)
  • On demand: User asks to clean up, reorganize, or defrag memory
  • Threshold: When MEMORY.md exceeds ~500 lines or daily notes accumulate without consolidation

Process

1. Audit Current State

Inventory all memory files:

MEMORY.md           — long-term memory
memory/             — daily notes, tasks, topical files
memory/tasks/       — active and completed tasks

For each file, note: line count, last modified, topic coverage, staleness.

2. Identify Problems

Look for these common issues:

ProblemSignalFix
Bloated file>300 lines, covers many topicsSplit into focused files
Duplicate infoSame fact in multiple placesConsolidate to one location
Stale entriesReferences to completed work, old dates, resolved issuesRemove or archive
Orphan filesFiles in memory/ never referenced or updatedReview, merge, or remove
InconsistenciesContradictory information across filesResolve to ground truth
Poor organizationRelated info scattered across filesRestructure by topic
Recursive nestingmemory/memory/memory/... directoriesDelete nested dirs (indexer bug artifact)

3. Plan Changes

Before making edits, write a brief plan:

## Defrag Plan
- [ ] Split MEMORY.md "Key People" section → memory/people.md
- [ ] Remove completed tasks older than 30 days from memory/tasks/
- [ ] Merge memory/bm-marketing-ideas.md into memory/competitive/
- [ ] Update stale project status entries in MEMORY.md

4. Execute

Apply changes one at a time:

  • Split: Extract sections from large files into focused topical files
  • Merge: Combine related small files into coherent documents
  • Prune: Remove information that is no longer relevant or accurate
  • Restructure: Move files to appropriate directories, rename for clarity
  • Update: Fix outdated facts, dates, statuses

5. Verify & Log

After changes:

  • Verify no information was lost (compare before/after)
  • Update any cross-references between files
  • Log what was done in today's daily note:
## Memory Defrag (HH:MM)
- Files reviewed: N
- Split: [list]
- Merged: [list]
- Pruned: [list]
- Net result: X files, Y total lines (was Z lines)

Guidelines

  • Preserve raw daily notes. Don't delete or modify memory/YYYY-MM-DD.md files — they're the audit trail.
  • Target 15-25 focused files. Too few means bloated files; too many means fragmentation. Aim for the sweet spot.
  • File names should be scannable. Use descriptive names: people.md, project-status.md, competitive-landscape.md — not notes-2.md.
  • Don't over-organize. One level of directories is usually enough. memory/tasks/ and memory/competitive/ are fine; memory/work/projects/active/basic-memory/notes/ is not.
  • Completed tasks: Tasks with status: done older than 14 days can be removed. Their insights should already be in MEMORY.md via reflection.
  • Ask before destructive changes. If uncertain whether information is still relevant, keep it with a (review needed) tag rather than deleting.

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

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

35.42%
按下载量换算701

Claude

29.55%
按下载量换算585

Cursor

18.82%
按下载量换算373

Gemini CLI

8.7%
按下载量换算172

安全审计

Gen Agent Trust Hub

通过

Socket

通过

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。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