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workflow-brainstorm工作流程头脑风暴

Agent Skill

workflow-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。

总安装

1,151

周安装

47

GitHub Stars

338

下载量

368
CodexClaudeCursorGemini CLI

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

unknown

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:workflow-brainstorm(工作流程头脑风暴)
来源仓库:https://github.com/heyvhuang/ship-faster
仓库路径:skills/workflow-brainstorm
安装命令:
npx skills add https://github.com/heyvhuang/ship-faster --skill workflow-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/heyvhuang/ship-faster --skill workflow-brainstorm

简介

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、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前建议确认权限范围和维护状态,注意可能触发联网、命令执行或文件读写操作。
  • workflow-brainstorm 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Brainstorming Ideas Into Designs

Goal

Transform "vague ideas/requirements" into actionable designs and specifications, producing reusable file artifacts (rather than just staying in chat).

Key requirement: Ask only one question at a time. If a topic is complex, break it into multiple rounds of Q&A—don't throw out a checklist all at once.

Core Process (Must Follow)

0) Check Project Context First (Required When Repo Exists)

Before asking questions, quickly check:

  • Key documentation: README.md, docs/, design-system.md (if exists)
  • Tech stack and constraints: package.json / Cargo.toml / pyproject.toml etc.
  • Structure overview: top-level directories, main modules
  • Recent changes: git log -n 10 --oneline (if it's a git repo)

Output a very brief context summary: what you observed + possible constraint points (don't start designing yet).

1) Understand the Idea (One Question at a Time)

Goal is to gather the minimum information set (purpose / constraints / success criteria).

Rules:

  • Each message asks 1 question only
  • Prefer multiple choice (reduce user's cognitive load), use open questions only when necessary
  • Ask direction-determining questions first (goals/success criteria/non-goals), then details

2) Explore Solutions (2-3 Options + Trade-offs)

After you understand the requirements:

  • Provide 2-3 options (A/B/C)
  • Explain trade-offs for each (complexity/risk/iteration speed/long-term cost)
  • Give your recommended option first, then explain why

3) Output Design (200-300 Word Segments + Confirm Each)

When you're confident you understand what needs to be done, start outputting the design spec.

Requirements:

  • Output in segments (~200-300 words each)
  • Ask for confirmation at the end of each segment: e.g., "Does this look good?"
  • Design should at least cover:

- Architecture and module boundaries - Core data flow (input → processing → output) - Error handling and edge cases - Testing and validation strategy (minimum viable set)

If user disagrees with a segment: go back to questioning/option phase to clarify—don't push forward.

Artifacts and Persistence (Strongly Recommended)

Write Design Document

Prefer writing to run directory (artifact-first):

  • run_dir/evidence/YYYY-MM-DD-<topic>-design.md

If there's no run_dir but there is a repo_root:

  • Create runs/brainstorm/active/<run_id>/, and write design to evidence/
Note: Writing files is a write operation; if this is the user's project repo, confirm "should I persist to the project?" before writing.

Enter Implementation (Optional)

After design is confirmed, ask one question to let user choose next step:

  1. Enter implementation directly (recommend workflow-ship-faster or workflow-feature-shipper)
  2. Write implementation plan first (persist as checklist items in run_dir/tasks.md, then wait for confirmation)
  3. Need research/code reading first (split to run_dir/evidence/parallel/<task-name>/ and do in parallel)

Key Principles

  • One question at a time: Never ask 5 questions in one message
  • Multiple choice preferred: Help user respond faster and more effectively
  • YAGNI: Actively remove "not needed yet" features from the design
  • Incremental validation: Output design in segments, confirm each one

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

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

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

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

Codex

37.69%
按下载量换算139

Claude

29.88%
按下载量换算110

Cursor

20.03%
按下载量换算74

Gemini CLI

8.94%
按下载量换算33

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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