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Agent Skill · 研究检索

asking-clarifying-questions(提出澄清问题)

asking-clarifying-questions 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。

asking-clarifying-questions 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,权限为接触敏感数据;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 59,000。

总安装 396周安装 17GitHub Stars 176下载 139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:asking-clarifying-questions(提出澄清问题)
来源仓库:https://github.com/ed3dai/ed3d-plugins
仓库路径:skills/asking-clarifying-questions
安装命令:
npx skills add https://github.com/ed3dai/ed3d-plugins --skill asking-clarifying-questions
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/ed3dai/ed3d-plugins --skill asking-clarifying-questions

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。

用于查找、检索和筛选相关信息。asking-clarifying-questions 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合根据关键词、任务场景或来源线索快速定位候选结果。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和维护状态。

优先解决目标冲突,再处理技术细节,确保理解真实需求。

来源仓库内路径:skills/asking-clarifying-questions

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/ed3dai/ed3d-plugins --skill asking-clarifying-…;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

    它需要接触敏感数据,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

asking-clarifying-questions 怎么安装?

在终端执行 npx skills add https://github.com/ed3dai/ed3d-plugins --skill asking-clarifying-questions。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

asking-clarifying-questions 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。

asking-clarifying-questions 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

asking-clarifying-questions 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。

asking-clarifying-questions 用的人多吗?

公开数据是累计安装 396 次,近一周安装 17 次,下载 139 次,GitHub 176 星。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。

asking-clarifying-questions 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

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
asking-clarifying-questions

提出澄清问题 · 本页

396176接触敏感数据未明确通过

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

Asking Clarifying Questions

Overview

Bridge the gap between raw user input and structured brainstorming by understanding what the user actually means, not what they said.

Core principle: Resolve contradictions first, then disambiguate. Conflicting goals must be reconciled before technical clarification - otherwise you're precisely defining the wrong thing.

Announce at start: "I'm using the asking-clarifying-questions skill to make sure I understand your requirements correctly."

When to Use

Use this skill:

  • After gathering initial context from user
  • Before starting brainstorming or design exploration
  • When user mentions technical terms that could mean multiple things
  • When scope boundaries are unclear
  • When assumptions need verification

Do NOT use for:

  • Exploring design alternatives (that's brainstorming)
  • Proposing architectures (that's brainstorming)
  • Validating completed designs (that's brainstorming Phase 3)
  • Asking for initial requirements (that's starting-a-design-plan Phase 1)

Before Clarifying

Try to answer your own questions and disambiguate from the context of the working directory. Use available subagents, such as codebase-investigator, to explore for existing work that can help explain the the subject under clarification. When you recognize elements such as common technologies or proper nouns, use combined-researcher instead to synthesize both the codebase and internet searches.

You may have other skills or MCPs containing useful information, such as connections to remote datastores used for product management purposes. You should send out haiku-general-purpose subagents to investigate them when they're appropriate.

What to Clarify

0. Contradictions (First Pass)

Before disambiguating technical details, scan for logical contradictions in requirements. If the user has stated mutually exclusive goals, resolve these first - technical clarification is wasted effort if the foundation shifts.

Look for:

Explicit contradictions (user stated both):

  • "Real-time updates" + "batch processing is fine" → Which is the actual need?
  • "Keep it simple" + "handle every edge case" → Trade-off not acknowledged
  • "Use existing patterns" + "complete rewrite" → Mutually exclusive approaches
  • "No external dependencies" + "integrate with Stripe" → Implicit contradiction

Impossible combinations:

  • "Offline-first" + "always-current data" → Physics problem
  • "Fast to build" + "infinitely extensible" → Classic impossible triangle
  • "Zero latency" + "synchronous validation" → Can't have both
  • "No breaking changes" + "fundamental redesign" → Pick one

Unacknowledged trade-offs:

  • "Simple" often conflicts with "flexible"
  • "Fast" often conflicts with "thorough"
  • "Cheap" often conflicts with "custom"
  • "Secure" often conflicts with "convenient"

How to surface:

Don't accuse - illuminate the tension:

  • "I notice you mentioned X and Y - these can pull in different directions. Which takes priority?"
  • "There's a trade-off between A and B here. Which matters more for this project?"
  • "These two goals sometimes conflict - how should I balance them when they do?"

Why first:

  • Contradictions reveal unconfronted trade-offs
  • Resolving them changes what "right" means
  • Technical disambiguation without this = building the wrong thing precisely

After contradictions are resolved, proceed to technical clarification.

1. Technical Terminology

When user mentions technical terms, disambiguate what they actually mean.

Examples:

User says "OAuth2" -> Ask: Which flow?

  • Authorization code flow (for human users with browser redirect)
  • Client credentials flow (for service-to-service auth)
  • Both, depending on the use case

User says "database" -> Ask: Which kind?

  • SQL (PostgreSQL, MySQL) for structured data
  • NoSQL (MongoDB, DynamoDB) for flexible schema
  • Already determined by existing infrastructure

User says "caching" -> Ask: What layer?

  • Application-level (Redis, Memcached)
  • HTTP caching (CDN, browser cache)
  • Database query caching

Use AskUserQuestion for these - present specific options with trade-offs.

2. Scope Boundaries

When user mentions broad concepts, identify what's included and excluded.

Examples:

User says "users" -> Ask: Who exactly?

  • Human users logging in via web browser
  • Service accounts for API access
  • Both, with different authentication flows
  • Internal employees vs external customers

User says "integrate with X" -> Ask: What parts?

  • Just authentication
  • Full data sync
  • Specific API endpoints
  • Real-time webhooks vs batch imports

User says "reporting" -> Ask: What scope?

  • Basic data export (CSV, Excel)
  • Interactive dashboards
  • Scheduled automated reports
  • Real-time analytics

Use AskUserQuestion - present distinct scope options.

3. Assumptions and Constraints

When user states requirements, verify the underlying reasons and constraints.

Examples:

User says "must use library X" -> Ask: Why?

  • Regulatory requirement (cannot change)
  • Existing team expertise (preference, not hard requirement)
  • Already in use elsewhere (consistency benefit)
  • Misconception (might have better options)

User says "needs to be fast" -> Ask: How fast?

  • Sub-100ms response time (hard requirement)
  • Faster than current implementation (relative improvement)
  • Perception of speed (optimistic UI, loading states)
  • Actual performance bottleneck identified

User says "should follow pattern Y" -> Ask: Which aspect?

  • Exact implementation (strict consistency)
  • General approach (flexible adaptation)
  • Just using same libraries (tooling consistency)
  • Not actually required (outdated guideline)

Use open-ended questions for understanding "why" - allows user to explain context.

4. Version and API Specifics

When user mentions external services or libraries, verify current state.

Examples:

User says "integrate with Stripe" -> Check:

  • Which Stripe API version (latest? specific?)
  • Payment Intents API or older Charges API
  • Which features needed (one-time, subscriptions, both)
  • Already have Stripe account setup

User says "use React Router" -> Check:

  • React Router v5 or v6 (breaking changes between versions)
  • Already in use in codebase (follow existing patterns)
  • Browser Router vs Hash Router vs Memory Router

Quick agent queries for factual checks:

  • "What version of X exists?" -> Quick web search or codebase check
  • "What's the current API?" -> Internet research for docs
  • "Is Y already in use?" -> Codebase investigation

Don't do deep research - save that for brainstorming. Just verify basics.

5. Definition of Done (Required Final Step)

Before handing off to brainstorming, you MUST establish the Definition of Done.

The Definition of Done answers: "What does success look like? What are the deliverables?"

After resolving contradictions and clarifying requirements:

  1. Infer the Definition of Done from context gathered so far:

- What will exist when this is complete? - What will users/systems be able to do? - What are the concrete deliverables?

  1. If you have a firm grasp, state it back and confirm: Use AskUserQuestion: "Based on our discussion, here's what I understand success looks like: [State the definition of done in 2-4 bullet points] Does this capture what you're trying to achieve?" Options: - "Yes, that's right" (proceed to brainstorming) - "Partially, but..." (user will clarify) - "No, let me explain..." (user will reframe)
  2. If the deliverables are still ambiguous, ask targeted questions:

- "What should exist when this is done?" - "How will you know this succeeded?" - "What's the minimum viable deliverable?"

Why this matters: Brainstorming explores *how* to achieve the goal. The goal must be locked in first. Otherwise you're exploring texture without knowing what shape you're filling.

The Definition of Done becomes part of the output bundle and will appear prominently at the top of the final design document.

Question Techniques

Use AskUserQuestion for Choices

When there are 2-4 distinct options with trade-offs:

Question: "Which OAuth2 flow are you targeting?"
Options:
  - "Authorization code flow" (human users with browser redirect)
  - "Client credentials flow" (service-to-service automated auth)
  - "Both flows" (supports human users AND service accounts)

Benefits:

  • Forces explicit choice
  • Shows trade-offs clearly
  • Prevents vague "maybe both" responses
  • Structured for decision-making

Use Open-Ended Questions for Why

When you need to understand reasoning or context:

"Why is X a requirement?" "What problem does Y solve?" "What happens if we don't include Z?"

Benefits:

  • Uncovers hidden constraints
  • Reveals user's mental model
  • Identifies assumptions to challenge
  • Provides context for brainstorming

Use Quick Queries for Facts

When you need to verify something factual:

  • Dispatch codebase-investigator: "Is library X already in use?"
  • Quick web search: "What's the current version of API Y?"
  • File read: "Check package.json for existing auth dependencies"

Don't get distracted - these are quick checks, not research projects.

Output: Context Bundle for Brainstorming

After clarification, create a clear summary to pass to brainstorming:

Resolved trade-offs:

  • Speed over flexibility (chose simple implementation, accept less configurability)
  • Security over convenience (chose strict validation, accept more friction)
  • Consistency over ideal (chose existing patterns, accept suboptimal in isolation)

Clarified requirements:

  • OAuth2 client credentials flow (service-to-service)
  • External customers only (not internal employees)
  • Stripe Payment Intents API (latest version)
  • Must comply with PCI DSS Level 1 (regulatory constraint)
  • "Fast" means sub-200ms p99 response time (measured requirement)

Verified assumptions:

  • React Router v6 already in use (follow existing patterns)
  • PostgreSQL database (existing infrastructure)
  • No existing auth system (greenfield)

Scope boundaries:

  • IN: Service account creation, token issuance, token validation
  • OUT: Human user login, SSO integration, password management

This bundle gives brainstorming a concrete, unambiguous starting point.

Common Mistakes

MistakeFix
Ignoring contradictions in requirementsSurface conflicting goals before technical clarification
Accepting vague terms at face valueDisambiguate every technical term
Assuming scope without verificationAsk explicit boundary questions
Not questioning "must have" requirementsUnderstand WHY behind constraints
Doing deep research during clarificationQuick checks only, save research for brainstorming
Proposing solutions while clarifyingStay in understanding mode, no design yet
Skipping clarification when "seems clear"Always clarify, assumptions are dangerous

When to Stop Clarifying

Stop and move to brainstorming when:

  • Contradictions are resolved (trade-offs explicitly chosen)
  • Technical terms are disambiguated
  • Scope boundaries are explicit
  • Constraints are understood (not just stated)
  • Assumptions are verified
  • No major ambiguities remain

You don't need perfect information - just enough to brainstorm effectively.

If brainstorming reveals new ambiguities, you can return to clarification.

Integration with Design Workflow

This skill sits between context gathering and brainstorming:

Context Gathering (starting-a-design-plan Phase 1)
  -> User provides: "Build OAuth2 integration for our API"

Clarification (this skill)
  -> Disambiguate: Which OAuth2 flow? What scope? Why OAuth2?
  -> Output: Service accounts, client credentials, PCI compliance

Brainstorming (starting-a-design-plan Phase 3)
  -> Explore: Architecture options, library choices, implementation phases
  -> Uses clarified requirements as foundation

Purpose: Ensure brainstorming builds the right thing, not the wrong thing well.

平台分布

Codex

35.38%
按下载量换算49

Claude

30.14%
按下载量换算42

Cursor

17.85%
按下载量换算25

Gemini CLI

9.08%
按下载量换算13

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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