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Brainstorm

v1.0.1

引导梳理模糊想法,分三步完成需求澄清、方案对比和设计细化,适用于新功能规划和技术选型。

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Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for caspermoo/mu-brianstorm.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Brainstorm" (caspermoo/mu-brianstorm) from ClawHub.
Skill page: https://clawhub.ai/caspermoo/mu-brianstorm
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install mu-brianstorm

ClawHub CLI

Package manager switcher

npx clawhub@latest install mu-brianstorm
Security Scan
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OpenClawOpenClaw
Suspicious
medium confidence
Purpose & Capability
The skill's name/description (brainstorming, design guidance) aligns with included templates and a small helper script to initialize design docs. However, SKILL.md metadata declares python3 as a required binary while the registry-level requirements list none — this mismatch is an internal inconsistency that should be clarified.
Instruction Scope
Runtime instructions stay within the stated purpose: guiding conversation, producing design docs, and suggesting writing files under docs/plans and committing to git. The skill suggests the agent should 'look at related code and docs' (reasonable for context) and the included script creates files; there are no instructions to read unrelated secrets or transmit data externally.
Install Mechanism
No install spec is provided (instruction-only), which is low-risk. The only code file is a small Python script included in the bundle (no downloads or external installers).
Credentials
The skill does not request environment variables, credentials, or external tokens. It does recommend committing to git, which may rely on the user's existing git credentials but the skill does not demand any secrets itself.
Persistence & Privilege
always is false and the skill does not request persistent elevated privileges. The included script writes files into docs/plans (its own scope) but does not modify other skills or system-wide agent settings.
What to consider before installing
This skill is mostly harmless and matches its description, but check two things before installing: 1) Metadata mismatch — SKILL.md lists python3 as required while registry requirements show none; ensure python3 is available if you plan to use the included script. 2) The bundle includes scripts/init_design_doc.py which will create files under docs/plans when run — review that script (it's short and benign) and confirm you want the skill or agent to write/commit files to your repository. If you don't want automatic file creation, avoid running the script and use the templates manually. Finally, because the skill's source/homepage are unknown, prefer installing only if you trust the publisher or after reviewing the files (you already have them) for any unexpected changes.

Like a lobster shell, security has layers — review code before you run it.

latestvk97fhfqgj23r5d2ct0x0wa6sg583pk56
121downloads
0stars
2versions
Updated 1mo ago
v1.0.1
MIT-0

设计对话引导

将零散的想法,通过对话梳理成清晰的设计蓝图。

引导心法

与其一次抛出大量问题,不如:

  • 逐步深入 - 先建立共识,再细化细节
  • 提供选项 - 让选择比描述更容易
  • 敢于删减 - 每个功能都要有存在的理由
  • 多维对比 - 好方案是比较出来的
  • 小步确认 - 每一步都确保方向正确

对话三步法

第一步:建立共识

搞清楚"做什么"和"为什么做"

先看项目现状

  • 瞄一眼相关代码和文档
  • 了解现有架构和技术选型
  • 感受项目的风格和习惯

再逐个确认

  • 每次只聊一个话题
  • 关键问题用选择题形式
  • 一次问多个问题时,问题带编号(①②③)

多问题回复格式 告诉用户用「编号+选项」回复,空格或逗号分隔:

① 资讯类型?A.AI B.财经 C.都要
② 来源偏好?A.公众号 B.Twitter C.RSS
③ 输出形式?A.推送 B.存档 C.都要

回复示例: 1A 2C 3B 或 1A, 2C, 3B

要明确的重点

  • 为什么要做这个?(动机)
  • 有什么限制?(约束)
  • 怎样算成功?(验收标准)

出口条件:能用一句话说清楚要解决的问题

第二步:构思方案

提出多个可行路径,权衡后做出选择

给出 2-3 条路

  • 每条路都能走通
  • 各有不同的取舍
  • 覆盖从保守到激进的选项

说清楚利弊

  • 每个方案的优缺点
  • 适用什么场景
  • 实现难度如何

先表明倾向

我倾向于方案 B,因为:
1. 复用现有组件,成本低
2. 团队熟悉这个技术栈
3. 能满足当前需求

代价是:扩展性不如方案 C

你更倾向哪个?或者有其他想法?

出口条件:确定要走的路线

第三步:细化设计

把选定方案展开成可执行的细节

分段呈现(每段控制篇幅)

  • 一次性给太多信息会消化不良
  • 每个部分讲清楚再往下

逐段确认

这部分 OK 吗?需要调整哪里?

覆盖的设计要素

  1. 整体架构 - 大图景
  2. 核心组件 - 关键模块
  3. 数据流转 - 信息怎么流动
  4. 异常处理 - 出问题怎么办
  5. 测试思路 - 怎么验证正确性
  6. 边界情况 - 特殊场景

随时可以回退

  • 某个点卡住了就停下来
  • 回到前面重新对齐理解
  • 不要硬着头皮往下推

出口条件:设计获得确认

设计定稿后

输出文档

写入 docs/plans/YYYY-MM-DD-<主题>-design.md

格式参考 输出模板

别忘了提交到 git。

继续实现

设计完成了,接下来要开始实现吗?

如果确认,可以:

  1. 生成实现计划
  2. 在独立分支开始编码

典型场景应对

用户想法很模糊

"我想做一个好用的工具"

引导方式

  1. "主要解决什么问题?"
  2. "给谁用的?"
  3. "现在怎么解决的?有什么不满意?"

功能需求太多

"我要 A、B、C、D、E..."

引导方式

  1. 列出来全部功能
  2. "第一版必须有哪几个?"
  3. 解释分阶段的好处
  4. 帮助砍掉暂时不需要的

需求反复变化

引导方式

  1. 暂停细化设计
  2. "我注意到有变化,重新确认下核心目标..."
  3. 回到第一步重新对齐
  4. 明确范围边界

参考资源

按需查阅:

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