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Agent Skill · 研究检索

brainstorm(头脑风暴)

brainstorm 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。

brainstorm 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 42,521。

总安装 1,067周安装 44GitHub Stars 公开资料未说明下载 348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:brainstorm(头脑风暴)
来源仓库:https://github.com/witooh/skills
仓库路径:skills/brainstorm
安装命令:
npx skills add https://github.com/witooh/skills --skill brainstorm
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/witooh/skills --skill brainstorm

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。

brainstorm 用于查找、检索和筛选相关信息。适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词或任务场景快速定位候选结果。通过 npx skills add 命令从指定仓库安装并使用。建议确认权限范围和维护状态,避免触发联网或文件读写。

brainstorm 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/brainstorm

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/witooh/skills --skill brainstorm;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

brainstorm 怎么安装?

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

brainstorm 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。

brainstorm 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。

brainstorm 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。

brainstorm 用的人多吗?

公开数据是累计安装 1,067 次,近一周安装 44 次,下载 348 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。

brainstorm 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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
brainstorm

头脑风暴 · 本页

1,067—需要联网未明确有提醒

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

Brainstorm

Transform vague ideas into precise, actionable outputs through adaptive structured questioning. The skill adjusts its depth and output format based on what the user actually needs — from quick idea generation to thorough prompt engineering.

Quick Start

  1. User provides a request (vague idea, brainstorm request, or prompt to improve)
  2. Triage — Classify into one of three modes: Prompt, Explore, or Focused
  3. Run the appropriate discovery flow (3–7 questions depending on mode)
  4. Produce the right output type for the mode
  5. Offer next steps

Tools

ToolPurpose
AskUserQuestionAsk the user ONE question at a time. Claude Code: native AskUserQuestion with options (see AskUserQuestion Usage below). Copilot: ask_user with choices. Kiro/other: plain text with numbered options.
WebSearchFind references when the user has none and references would genuinely help. Claude Code: WebSearch. Copilot/Kiro: web_search.
AgentDelegate to Plan subagent. Claude Code: Agent(subagent_type: "Plan"). Copilot: task(agent_type: "general-purpose") + # Role: Planner block. Kiro: use_subagent. Fallback: create plan inline.

AskUserQuestion Usage

Use one question per call even though the API supports up to 4 — multiple questions get shallow answers.

Each question requires:

  • question: Clear question text ending with ?
  • header: Short label (max 12 chars) displayed as a chip, e.g. "Goal", "Priority", "Approach"
  • options: Array of 2-4 choices — each with label (1-5 words) and description (explains trade-offs). "Other" is added automatically — do not include one.
  • multiSelect: Set to true only when choices are not mutually exclusive. Omit otherwise (defaults to false).

Put your recommended option first and append "(Recommended)" to its label.

Example: {"questions": [{"question": "Which matters more?", "header": "Priority", "options": [{"label": "Speed (Recommended)", "description": "Ship fast, iterate later"}, {"label": "Quality", "description": "Get it right the first time"}]}]}

Core Principles

  1. Don't answer before you understand. The urge to help immediately produces generic output. But "understand" doesn't mean "ask 13 questions" — it means knowing enough to be specific.
  2. One question at a time via tool. Multiple questions get shallow answers. Use AskUserQuestion (Claude Code), ask_user (Copilot), or plain text as last resort — but always ask one at a time.
  3. Prefer multiple choice. Provide options when the answer space is predictable. Choices are faster to answer, reduce cognitive load, and reveal preferences. Use open-ended only when the answer truly can't be predicted.
  4. Mirror the user's language. Don't introduce jargon they didn't use.
  5. Ask about life, not the domain. Constraints, risks, and deal-breakers require zero domain knowledge but eliminate wrong paths decisively.
  6. Never re-ask what's already known. Track information from the initial prompt and all answers.
  7. Respect the user's time. Match question depth to request complexity. A casual "help me brainstorm" doesn't need the same rigor as "craft a detailed prompt."

Triage — Choosing the Right Mode

Before asking any questions, read the user's request and classify it into one of three modes. This happens internally — don't ask the user which mode they want.

Prompt Mode

When: User explicitly wants to create or improve a prompt, or needs a comprehensive brief for another AI/tool/person. Signals: "improve this prompt", "help me write a prompt", "ช่วยคิด prompt", "I want to ask Claude to...", mentions using the output with another AI. Flow: Full discovery (5–7 questions across Goal → Direction → Context → Criteria) Output: Improved Prompt + Discovery Summary

Explore Mode

When: User wants to brainstorm ideas, explore possibilities, or think through something open-ended. Signals: "brainstorm", "help me think", "ช่วยคิดหน่อย", "I want to build something but...", "what should I...", "any ideas for..." Flow: Light discovery (3–5 questions) — understand goals + constraints quickly, then generate ideas Output: Curated ideas/options with trade-offs, then offer to go deeper on the chosen one

Focused Mode

When: User has a specific problem with existing context and wants strategies or recommendations. Signals: Prompt already contains specifics (numbers, tech stack, current situation). User says "brainstorm วิธี...", "how to reduce...", "what's the best approach to..." Flow: Targeted discovery (0–2 questions) — only ask about genuine unknowns, skip what's already stated Output: Actionable strategies/recommendations with priorities and estimated impact

Workflow by Mode

For detailed questioning patterns, techniques, and examples per phase, see references/QUESTIONING-GUIDE.md


Prompt Mode — Full Discovery

The most thorough path. Use all phases when the user needs a well-crafted prompt.

Phase 1 — Receive: Acknowledge the request. Say something like: *"I'll help you craft that prompt. Let me ask a few questions to make it specific to your situation."*

Phase 2 — Goal: What does the user want the prompt to achieve? Get to a one-sentence goal with at least one measurable indicator. (1–2 questions)

Phase 3 — Direction: What must NOT happen? What approaches exist? Propose 2–3 viable approaches with trade-offs after gathering constraints. Lead with your recommendation. (1–2 questions + proposal)

Phase 4 — Reference (optional): Only if references would genuinely help (e.g., style/design requests). Ask if they have examples. If none and it would help, use WebSearch. If search returns poor or no results, tell the user and ask whether to proceed without references or try different search terms. Skip entirely for straightforward requests. (0–1 questions)

Phase 5 — Context: Surface practical constraints: time, budget, skills, team, environment. Flag contradictions with the goal gently. (1–2 questions)

Phase 6 — Criteria: Define what "good" means. Force-rank if more than 3 criteria. (1 question)

Phase 7 — Synthesize: Draft the improved prompt with this structure:

## Improved Prompt

[The refined, specific prompt incorporating all discovered information]

---

### Discovery Summary

**Goal:** [One sentence with measurable indicator]
**Direction:** [Chosen approach and key constraints]
**Context:** [Practical constraints: time, budget, skills, environment]
**Criteria:** [Ranked evaluation criteria]

The improved prompt must be self-contained, include all constraints inline, and be specific enough that any AI produces a targeted answer.

Present it and ask: *"Does this capture what you need? Anything to adjust?"* Iterate if needed.


Explore Mode — Light Discovery

For open-ended brainstorming where the user wants ideas, not a prompt.

Phase 1 — Receive + Quick Goal: Acknowledge, then ask ONE question combining goal + motivation via the questioning tool (see Tools table) with options like: Learning / Earning / Solving a problem / Building portfolio. (1 question)

Phase 2 — Constraints: Ask about deal-breakers and practical limits in 1–2 questions. Combine related constraints (time + budget, or skills + tools) into a single question when natural. (1–2 questions)

Phase 3 — Generate: Based on what you've learned, produce 5–8 concrete ideas organized by theme. Each idea should include:

  • What it is (one sentence)
  • Why it fits this user's constraints
  • One potential challenge

Phase 4 — Narrow: Ask which ideas resonate. Then offer:

  1. Go deeper on one idea (pivot to Prompt Mode or create a plan)
  2. Generate more ideas in a specific direction
  3. Done — take the ideas and go

Focused Mode — Targeted Discovery

For specific problems where the user already provided good context.

Phase 1 — Acknowledge context: Summarize what you already know from the prompt. Explicitly list what's established so the user sees you're not going to re-ask it.

Phase 2 — Fill gaps: Ask only about genuine unknowns that would change your recommendations. If the prompt is detailed enough, you might ask just 1 question — or even zero and go straight to recommendations. (0–2 questions)

Phase 3 — Strategize: Produce actionable recommendations:

  • Prioritized list (quick wins first, then bigger efforts)
  • Each item: what to do, estimated impact, effort level, risks
  • Clear "start here" recommendation

Phase 4 — Refine: Ask if anything needs adjustment. Offer to create an implementation plan via Plan subagent.


Next Step

After delivering the output (regardless of mode), offer next steps using AskUserQuestion (or ask_user / plain text if unavailable):

  • Create a Plan — Delegate to Plan subagent: Agent(subagent_type: "Plan") (Claude Code), task(agent_type: "general-purpose") with # Role: Planner block (Copilot), use_subagent (Kiro), or create the plan inline if none available
  • Go deeper — Continue exploring a specific aspect
  • Done — End the workflow

Handling Edge Cases

User wants to skip questions: Respect it. Produce the best output with what you have. Briefly note what's missing: *"Without knowing [X], this might be more generic — but here's what I've got."*

User says "I don't know": Offer 2–3 concrete options and let them react. Reactions reveal preferences without requiring expertise.

Contradictions in user's answers: Flag neutrally: *"Earlier you mentioned X, but Y seems different. Which should we prioritize?"*

Too broad for one session: Suggest splitting. Run the workflow for each piece.

Mode feels wrong mid-conversation: Switch. If you started in Explore Mode but the user clearly wants a detailed prompt, transition to Prompt Mode. No need to restart — carry forward what you've learned.

平台分布

Codex

35.3%
按下载量换算123

Claude

28.5%
按下载量换算99

Cursor

19.18%
按下载量换算67

Gemini CLI

9.22%
按下载量换算32

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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