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Agent Skill · 研究检索

questions-methodology(问题方法论)

questions-methodology 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。

questions-methodology 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,权限为调用外部服务;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 60,316。

总安装 371周安装 15GitHub Stars 公开资料未说明下载 116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:questions-methodology(问题方法论)
来源仓库:https://github.com/pentaxis93/aiandi
仓库路径:skills/questions-methodology
安装命令:
npx skills add pentaxis93/aiandi --skill "questions-methodology"
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 pentaxis93/aiandi --skill "questions-methodology"

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。

提供结构化方法论指导,帮助用户体系化构建问题与解决方案。适用于项目管理、科研设计或产品开发等需要严谨流程的场景。可在 Gemini CLI、Cursor 中调用以生成标准化提问模板与评估框架。使用前应适配具体项目类型,避免生搬硬套导致形式主义。建议定期复盘方法适用性,持续优化提问策略与执行效率。

来源仓库内路径:skills/questions-methodology

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 pentaxis93/aiandi --skill "questions-methodology";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

    它需要调用外部服务,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

questions-methodology 怎么安装?

在终端执行 npx skills add pentaxis93/aiandi --skill "questions-methodology"。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

questions-methodology 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。

questions-methodology 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

questions-methodology 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。

questions-methodology 用的人多吗?

公开数据是累计安装 371 次,近一周安装 15 次,下载 116 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。

questions-methodology 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。

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。

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
questions-methodology

问题方法论 · 本页

371—调用外部服务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

name
questions-methodology
description
Question template for Methodology stories ('Here's how to do X'). Arc: Problem → Experimentation → Discovery → Refinement → Teaching. Use with question-design skill.

Methodology Story Questions

Story type: "Here's how to do X" Arc: Problem → Experimentation → Discovery → Refinement → Teaching


The Shape

Methodology stories share a way of doing things that works. But they're not manuals - they're stories of how the method was discovered and refined. The reader learns both WHAT to do and WHY it works.

What makes it work: Earned authority. The method came from real problems, real failures, real refinement. It's not theory - it's practice that's been tested.


Question Sequence

Opening: The Problem

*What drove the search for a method.*

  • "What problem were you trying to solve?"
  • "What was frustrating you?"
  • "What wasn't working with existing approaches?"
  • "How long did you struggle before you found something that worked?"

Experimentation: What You Tried

*The search process - including failures.*

  • "What did you try first?"
  • "What didn't work? What did you learn from that?"
  • "Where did you look for ideas?"
  • "What assumptions did you have to abandon?"

Discovery: Finding What Works

*The core of the method emerging.*

  • "When did you find something that actually worked?"
  • "What was different about this approach?"
  • "How did you know it was working?"
  • "Was it a sudden breakthrough or gradual improvement?"

Refinement: Making It Reliable

*From "it worked once" to "it works consistently."*

  • "How did you test it? How did you break it?"
  • "What edge cases did you discover?"
  • "How has the method evolved since you first found it?"
  • "What's the simplest version that still works?"
  • "What's essential vs. what's optional?"

Teaching: Transmission

*How to help others learn it.*

  • "How do you explain this to someone new?"
  • "What do people usually get wrong at first?"
  • "What's the first thing someone should try?"
  • "What prerequisites does this require?"
  • "How do you know when someone has really got it?"

Tacit Knowledge Triggers (Methodology-Specific)

  • "What's the thing you do that you don't even think about anymore?"
  • "What would break if you stopped doing [specific step]?"
  • "What variation have you developed that nobody else does?"
  • "What's the 'feel' of doing this right vs. wrong?"
  • "What can't be written down - what has to be experienced?"

Walking Adaptation

First quarter: Problem + early Experimentation (establish stakes) Second quarter: Experimentation failures + Discovery (the search) Third quarter: Refinement (the craft of making it work) Final quarter: Teaching (how to transmit it)

The Refinement section often surfaces tacit knowledge - they may not know what they know until they try to explain it.


Example: AI Collaboration Method

Opening: "What wasn't working in your early attempts to use AI for coding?" Experimentation: "What approaches did you try that failed?" Discovery: "When did you find something that actually worked? What was different?" Refinement: "How has your method evolved? What did you add, what did you drop?" Teaching: "If you were teaching someone your approach, what's the first thing you'd have them try?"


*The methodology story earns its authority through honest experimentation.*

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3.37%
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安全审计

暂无安全审计结果可展示。

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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