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ask

Agent Skill

ask 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

10,059

周安装

403

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公开资料未说明

下载量

3,256
OpenClaw

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

MIT-0

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:ask(问)
来源仓库:https://github.com/agimodel/ask
安装命令:
openclaw skills install ask
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install ask

简介

用于帮助用户深入思考问题本质,提升决策质量与提问技巧。

  • 适合面临复杂选择或需要厘清思路时使用。
  • 通过引导式对话激发反思,不提供直接答案而是促进自省。
  • 不涉及外部数据调用,仅依赖用户输入进行推理辅助。
  • 适用于 OpenClaw 环境,安装命令为 openclaw skills install ask。

SKILL.md

name
ask
description
>

Ask

The Question Behind the Question

Every problem has a surface question and a real question. The surface question is what you think you are asking. The real question is what you actually need to answer.

"Should I take this job offer?" is a surface question. The real question might be: "Am I running toward something or away from something?" Or: "What would I regret more — taking it or not taking it?" Or: "Do I trust this manager, and is everything else negotiable?"

The surface question has a yes or no answer. The real questions have answers that change your life.

This skill finds the real question.


How It Works

You bring any problem, decision, or situation. The skill does not answer it immediately. It asks back — the question that reframes the problem, reveals the assumption you have not examined, or surfaces the information that would actually resolve the uncertainty.

This is not therapy. It is thinking infrastructure. The goal is clarity, not comfort.


Question Types and When to Use Them

QUESTION_TAXONOMY = {
  "clarifying": {
    "purpose":  "Expose vague language that creates false certainty",
    "triggers": ["always", "never", "everyone", "nobody", "should", "can't"],
    "examples": ["What specifically do you mean by [vague term]",
                 "When you say [X], what does that look like in practice",
                 "What would have to be true for that to be false"]
  },

  "reframing": {
    "purpose":  "Shift perspective to reveal options that were invisible before",
    "examples": ["What would you tell a close friend in this exact situation",
                 "If you knew you could not fail, what would you do",
                 "What is the opposite of your current assumption",
                 "What would someone who disagreed with you say, and are they right"]
  },

  "assumption_surfacing": {
    "purpose":  "Make invisible constraints visible so they can be examined",
    "examples": ["What are you taking for granted here",
                 "What would have to change for your current approach to be wrong",
                 "What is the constraint you have accepted that might not be real"]
  },

  "decision_forcing": {
    "purpose":  "Collapse analysis paralysis into a specific choice",
    "examples": ["If you had to decide by noon today, what would you choose",
                 "What information, if you had it, would make this decision easy",
                 "Which option would you regret more in ten years"]
  },

  "root_cause": {
    "purpose":  "Get beneath symptoms to underlying causes",
    "method":   "Five Whys — ask why five times in sequence",
    "example":  """
      Problem: I keep missing deadlines
      Why 1: I underestimate how long tasks take
      Why 2: I do not break tasks into concrete steps before estimating
      Why 3: I am uncomfortable with uncertainty so I avoid detailed planning
      Why 4: Detailed plans reveal how much I do not know
      Why 5: I am afraid of looking incompetent

      Root cause: Fear of incompetence, not poor time management
      Solution: Completely different from what the surface problem suggested
    """
  }
}

Decision Framework

When the question is a decision, the skill structures it:

DECISION_FRAMEWORK = {
  "step_1_define":    "What exactly is being decided, and by when",
  "step_2_options":   "What are the real options — including the ones you are avoiding",
  "step_3_criteria":  "What does a good outcome look like — write it down before evaluating",
  "step_4_evaluate":  "Rate each option against each criterion — separately, not holistically",
  "step_5_test":      "Which option would you regret most. Which feels right when you stop thinking.",
  "step_6_decide":    "Make the decision. Most decisions are more reversible than they feel."
}

When to Stop Asking and Start Acting

Not every question needs to be answered before acting. Some questions are only answerable through action. The skill distinguishes between:

QUESTION_TYPES_BY_ANSWERABILITY = {
  "answerable_now":    "More information or clearer thinking will resolve this",
  "answerable_later":  "Only experience will answer this — act and learn",
  "unanswerable":      "No information will resolve this — decide on values, not analysis"
}

The most common mistake in thinking is treating type 2 and 3 questions as type 1 — gathering more data when the answer requires action or acceptance, not analysis.


Quality Check

  • [ ] Surface question identified
  • [ ] Real question surfaced through follow-up
  • [ ] Key assumption examined
  • [ ] Decision structured if applicable
  • [ ] Action or acceptance identified as the right next step

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

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

OpenClaw

73.14%
按下载量换算2,381

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安装前确认

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来源信息

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