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Agent Skill · 研究检索

agent-memory(Agent 记忆)

agent-memory 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。

agent-memory 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 48,933。

总安装 673周安装 8GitHub Stars 公开资料未说明下载 65核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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-memory(Agent 记忆)
来源仓库:https://github.com/dimkinv/favorite-skills
仓库路径:skills/agent-memory
安装命令:
npx skills add https://github.com/dimkinv/favorite-skills --skill agent-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 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/dimkinv/favorite-skills --skill agent-memory

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

为 Agent 提供跨会话持久化记忆空间, 以人类可读 Markdown 格式存储知识。适用于记录决策 rationale、研究发现与复杂问题解决方案, 支持双向查阅。agent-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

默认存放于 memories/ 目录,需定期归档与摘要更新以保持知识新鲜度。

来源仓库内路径:skills/agent-memory

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/dimkinv/favorite-skills --skill agent-memory;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agent-memory 怎么安装?

在终端执行 npx skills add https://github.com/dimkinv/favorite-skills --skill agent-memory。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-memory 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agent-memory 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

agent-memory 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

agent-memory 用的人多吗?

公开数据是累计安装 673 次,近一周安装 8 次,下载 65 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agent-memory 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agent-memory

Agent 记忆 · 本页

673—需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Agent Memory

An agent-first persistent memory space for storing knowledge that survives across conversations. Memories are human-readable markdown files so that both the agent and humans can inspect and edit them.

Location

Store memories under:

  • memories/

(If your runtime expects a specific root, keep memories/ inside the skill folder and reference it relative to the skill directory.)

When to Use

Agent-first usage

Use this skill as a default tool for the agent to record and retrieve knowledge:

  • Capture important decisions, rationale, and work completed
  • Preserve research findings, tricky fixes, and important commands
  • Record in-progress work that should be resumable later
  • Check existing memories before starting related work

Explicit user requests

Use this skill when the user asks to:

  • Remember or save information
  • Recall prior decisions, context, or investigation results
  • Resume a workstream after a break
  • Review notes, history, or “what we decided”
  • Consolidate / clean up / organize memories

Proactive usage

Save memories at your own initiative when you discover something worth preserving, such as:

  • Research findings that took effort to uncover
  • Non-obvious patterns, sharp edges, or gotchas
  • Solutions to tricky problems (including commands, files, and the “why”)
  • Architectural decisions and rationale
  • Important decisions and work completed
  • In-progress work that may be resumed later

After completing any task or job, you must use this skill to record a brief memory of the work completed (even if no issues were found). Keep it concise and focused on resumption value.

Check memories when starting related work:

  • Before investigating a known problem area
  • When working on a feature you’ve touched before
  • When resuming work after a conversation break

What to Store

Focus on resumption value:

  • Decision + rationale
  • Current state (done / in-progress / blocked)
  • Key artifacts (files, links, commands, configs)
  • Next steps and open questions

Avoid storing:

  • Secrets (API keys, passwords, tokens)
  • Personal data not required for the user’s goals
  • Large verbatim logs unless essential (prefer summaries + pointer to where to find the log)

Folder Structure

Organize memories into category folders. There is no fixed taxonomy; create categories that match the content.

Guidelines:

  • Use kebab-case for folder and file names
  • Consolidate or reorganize as the knowledge base evolves

Example:

memories/
├── project-context/
│   └── january-2026-focus.md
├── dependencies/
│   └── iconv-esm-problem.md
└── performance/
    └── large-file-worker-leak.md

Memory File Format

Every memory must start with YAML frontmatter including a concise summary field.

Required frontmatter

---
summary: "1–2 lines describing what this memory contains (decisive + searchable)"
created: 2026-01-22
---

Optional frontmatter

---
summary: "Worker thread leak during large file processing — cause and fix"
created: 2026-01-15
updated: 2026-01-20
status: in-progress   # in-progress | resolved | blocked | abandoned
tags: [performance, worker, memory-leak]
related: [src/core/file/fileProcessor.ts]
---

Body guidelines

Use markdown headings when helpful. Keep content self-contained.

Recommended sections (use what’s relevant):

  • Context
  • Decision / Findings
  • Evidence (commands, snippets, links)
  • Impact
  • Next steps

Search Workflow (Summary-first)

Use a summary-first approach to find relevant memories efficiently.

  1. List categories
ls memories/
  1. View all summaries
rg "^summary:" memories/ --no-ignore --hidden
  1. Search summaries for a keyword
rg "^summary:.*KEYWORD" memories/ --no-ignore --hidden -i
  1. Search by tag
rg "^tags:.*KEYWORD" memories/ --no-ignore --hidden -i
  1. Full-text search (when summary search isn’t enough)
rg "KEYWORD" memories/ --no-ignore --hidden -i
  1. Read the specific memory file(s) that appear relevant.
Note: if memories/ is gitignored, use --no-ignore and --hidden.

Operations

Save a memory

  1. Determine an appropriate category folder
  2. Check if an existing category fits; otherwise create a new one
  3. Create a new file (avoid overwriting existing files)
  4. Write required frontmatter + a clear title and content

Example:

mkdir -p memories/category-name/

# Ensure the target file does not already exist
test -e memories/category-name/filename.md && echo "File exists" && exit 1

cat > memories/category-name/filename.md << 'EOF'
---
summary: "Brief description of this memory"
created: 2026-01-22
status: in-progress
tags: [tag1, tag2]
---

# Title

## Context

## Findings / Decision

## Next steps
EOF

Recall / remind

  1. Search summaries for relevant terms
  2. Read only the most promising files
  3. Summarize back to the user (include the decision + the actionable next step)

Maintain

  • Update: when information changes, update the content and add updated:
  • Consolidate: merge related memories as they grow
  • Delete: remove memories that are no longer relevant
  • Reorganize: move memories into better categories over time

Example delete:

rm -f memories/category-name/filename.md
rmdir memories/category-name/ 2>/dev/null || true

Quality Rules

  1. Write for resumption: a future reader should be able to continue without prior context
  2. Keep summaries decisive: reading the summary should indicate whether the full file is worth opening
  3. Prefer clarity over completeness: store what is useful, not everything
  4. Keep the memory base current: update or delete stale content

Examples (User Prompts That Should Trigger This Skill)

  • “Remember this: we decided to migrate to X because …”
  • “Save these investigation notes for later.”
  • “Remind me what we concluded about the caching bug.”
  • “What did we decide about the API pagination approach?”
  • “Check your notes about the deployment process.”
  • “Clean up our notes and consolidate duplicates.”

平台分布

Codex

31.43%
按下载量换算20

Claude

30.61%
按下载量换算20

Cursor

18.96%
按下载量换算12

Gemini CLI

9.1%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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