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Agent Skill · 研究检索

initiate-memory(启动记忆)

initiate-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。

initiate-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,权限为只读;许可证为 MIT,暂无第三方扫描结果,按安装量在研究检索类的 73,675 个 Skill 里排第 60,816。

总安装 364周安装 15GitHub Stars 公开资料未说明下载 119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
MIT

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:initiate-memory(启动记忆)
来源仓库:https://github.com/qredence/agentic-fleet
仓库路径:skills/initiate-memory
安装命令:
npx skills add qredence/agentic-fleet --skill "initiate-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。

AgentSkills.tonpx skills
npx skills add qredence/agentic-fleet --skill "initiate-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。

启动记忆技能用于会话历史加载与上下文恢复。适用于需要长期对话记忆的多轮交互应用。通过 qredence/agentic-fleet 仓库安装,需配置存储后端。使用前应评估存储容量与隐私保护机制。initiate-memory 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

注意定期归档旧数据,防止内存占用过高影响性能。

来源仓库内路径:skills/initiate-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 qredence/agentic-fleet --skill "initiate-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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

initiate-memory 怎么安装?

在终端执行 npx skills add qredence/agentic-fleet --skill "initiate-memory"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

initiate-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。

initiate-memory 需要什么权限?

权限级别是只读。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。

initiate-memory 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

initiate-memory 用的人多吗?

公开数据是累计安装 364 次,近一周安装 15 次,下载 119 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。

initiate-memory 安全吗?

没有查到第三方扫描结果,安全性无法从公开资料判断,安装前请自行审查源码、依赖和命令行为。

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。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 标注为只读权限,试用阶段不容易误改本地文件。

先想清楚的地方

  • 没有第三方扫描结果,安全性只能靠自己读源码判断。
  • 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。
  • 只想先试试效果、不希望它改动本地文件的人。

不太适合

  • 要求有安全扫描结论才肯安装的团队。
  • 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
initiate-memory

启动记忆 · 本页

364—只读MIT未收录

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

Initializing Memory

The user has requested that you initialize or reorganize your memory state for this project. This skill helps you systematically explore and document a codebase to build effective working memory.

Understanding Your Context

Important: This skill is designed for stateful agents that work with users over extended periods. Your memory is not just a convenience; it's how you get better over time and maintain continuity across sessions.

This command may be run in different scenarios:

  • Fresh project: Starting work on a new codebase
  • Existing project: User wants you to reorganize or significantly update your understanding
  • Deep dive: User wants comprehensive analysis of the project

Before making changes, inspect your current context and understand what already exists.

What to Remember About a Project

1. Procedures (Rules & Workflows)

Explicit rules and workflows that should always be followed:

  • "Never commit directly to main - always use feature branches"
  • "Always run lint before running tests"
  • "Use conventional commits format for all commit messages"
  • "Always check for existing tests before adding new ones"

2. Preferences (Style & Conventions)

User and project coding style preferences:

  • "Never use try/catch for control flow"
  • "Always add JSDoc comments to exported functions"
  • "Prefer functional components over class components"
  • "Use early returns instead of nested conditionals"

3. History & Context

Important historical context that informs current decisions:

  • "We fixed this exact pagination bug two weeks ago - check PR #234"
  • "This monorepo used to have 3 modules before the consolidation"
  • "The auth system was refactored in v2.0 - old patterns are deprecated"

Memory Scope Considerations

Consider whether information is:

Project-scoped:

  • Build commands, test commands, lint configuration
  • Project architecture and key directories
  • Team conventions specific to this codebase
  • Technology stack and framework choices

User-scoped:

  • Personal coding preferences that apply across projects
  • Communication style preferences
  • General workflow habits

Session/Task-scoped:

  • Current branch or ticket being worked on
  • Debugging context for an ongoing investigation
  • Temporary notes about a specific task

Recommended Memory Structure

Core Information Categories

Project Overview: Your behavioral guidelines and project purpose

  • Technology stack and architecture
  • Key directories and their purposes
  • Build/test/lint commands

Conventions: Project-specific rules and patterns

  • Commit message format
  • Code style preferences
  • PR process and review guidelines

User Preferences: User-specific information

  • Communication style preferences
  • Cross-project preferences
  • Working style and habits

Optional Categories (Create as Needed)

Current Task: Scratchpad for current work item context

  • Ticket ID, branch name, PR number
  • Relevant links and context
  • Current focus area

Decisions: Architectural decisions and their rationale

  • Why certain approaches were chosen
  • Trade-offs that were considered

Research Depth

You can ask the user if they want a standard or deep research initialization:

Standard initialization (~5-20 tool calls):

  • Scan README, package.json/config files, AGENTS.md, CLAUDE.md
  • Review git status and recent commits
  • Explore key directories and understand project structure
  • Create/update your memory to contain the essential information

Deep research initialization (~100+ tool calls):

  • Everything in standard initialization, plus:
  • Use TodoWrite to create a systematic research plan
  • Deep dive into git history for patterns, conventions, and context
  • Analyze commit message conventions and branching strategy
  • Explore multiple directories and understand architecture thoroughly
  • Search for and read key source files to understand patterns

What deep research can uncover:

  • Contributors & team dynamics: Who works on what areas? Who are the main contributors?
  • Coding habits: When do people commit? What's the typical commit size?
  • Writing & commit style: How verbose are commit messages? What conventions are followed?
  • Code evolution: How has the architecture changed? What major refactors happened?
  • Pain points: What areas have lots of bug fixes? What code gets touched frequently?

Research Techniques

File-based research:

  • README.md, CONTRIBUTING.md, AGENTS.md, CLAUDE.md
  • Package manifests (package.json, Cargo.toml, pyproject.toml, go.mod)
  • Config files (.eslintrc, tsconfig.json,.prettierrc)
  • CI/CD configs (.github/workflows/,.gitlab-ci.yml)

Git-based research (if in a git repo):

  • git log --oneline -20 - Recent commit history and patterns
  • git branch -a - Branching strategy
  • git log --format="%s" -50 | head -20 - Commit message conventions
  • git shortlog -sn --all | head -10 - Main contributors
  • Recent PRs or merge commits for context on ongoing work

How to Do Thorough Research

Don't just collect data - analyze and cross-reference it.

Shallow research (bad):

  • Run commands, copy output
  • Take everything at face value
  • List facts without understanding

Thorough research (good):

  • Cross-reference findings: If two pieces of data seem inconsistent, dig deeper
  • Resolve ambiguities: Don't leave questions unanswered
  • Read actual content: Don't just list file names - read key files to understand them
  • Look for patterns: What do the commit messages tell you about workflow?
  • Form hypotheses and verify: "I think this team uses feature branches" → check git branch patterns
  • Think like a new team member: What would you want to know on your first day?

Questions to ask yourself during research:

  • Does this make sense?
  • What's missing?
  • What can I infer?
  • Am I just listing facts, or do I understand the project?

The goal isn't to produce a report - it's to genuinely understand the project and how to be an effective collaborator.

Recommended Questions to Ask

Bundle these questions together when starting:

  1. Research depth: "Standard or deep research (comprehensive, as long as needed)?"
  2. Identity: "Which contributor are you?" (You can often infer from git logs)
  3. Related repos: "Are there other repositories I should know about?"
  4. Communication style: "Terse or detailed responses?"
  5. Any specific rules: "Rules I should always follow?"

What NOT to ask:

  • Things you can find by reading files ("What's your test framework?")
  • Permission for obvious actions - just do them
  • Questions one at a time - bundle them

Your Task

  1. Ask upfront questions: Bundle the recommended questions above
  2. Inspect existing context: See what already exists in AGENTS.md, README, etc.
  3. Identify the user: From git logs and their answers
  4. Research the project: Explore based on chosen depth. Use TodoWrite for a systematic plan.
  5. Document findings: Create notes or update project documentation
  6. Reflect and review: Check for completeness and quality
  7. Ask user if done: Check if they're satisfied or want you to continue

Reflection Phase

Before finishing, do a reflection step:

  1. Completeness check: Did you gather all relevant information?
  2. Quality check: Are there gaps or unclear areas?
  3. Structure check: Would this information make sense to your future self?

After reflection, summarize what you learned:

"I've completed the initialization. Here's a brief summary of what I set up: [summary]. Should I continue refining, or is this good to proceed?"

Remember: Good memory management is an investment. The effort you put into organizing your knowledge now will pay dividends as you work with this user over time.

平台分布

windsurf

30.85%
按下载量换算37

OpenCode

21.49%
按下载量换算26

Codex

16.88%
按下载量换算20

Claude Code

13.57%
按下载量换算16

Antigravity

8.38%
按下载量换算10

Gemini CLI

3.91%
按下载量换算5

安全审计

暂无安全审计结果可展示。

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。目前只有一个公开来源,建议同时核对源仓库。

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