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Agent Skill · 开发

compound-eng-brainstorming(复合工程头脑风暴)

compound-eng-brainstorming 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

compound-eng-brainstorming 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 3,822。

总安装 10,012周安装 409GitHub Stars 公开资料未说明下载 3,207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
MIT-0
版本
3.0.5

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:compound-eng-brainstorming(复合工程头脑风暴)
来源仓库:https://github.com/iliaal/compound-eng-brainstorming
安装命令:
openclaw skills install compound-eng-brainstorming
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 compound-eng-brainstorming

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

compound-eng-brainstorming 实施前探索工具,支持深度访谈、方法比较与设计文档生成。适用于 OpenClaw 中澄清模糊功能想法、梳理需求背景或制定初步方案时使用。通过结构化提问与假设验证,帮助定位核心问题与潜在解决方案路径。安装使用 clawhub 命令,建议配合项目现有文档风格统一输出格式。

涉及用户调研时需注意隐私保护,避免在未授权情况下收集敏感信息。

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 OpenClaw;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 openclaw skills install compound-eng-brainstorming;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

compound-eng-brainstorming 怎么安装?

在终端执行 openclaw skills install compound-eng-brainstorming。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

compound-eng-brainstorming 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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。

compound-eng-brainstorming 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。

compound-eng-brainstorming 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

compound-eng-brainstorming 用的人多吗?

公开数据是累计安装 10,012 次,近一周安装 409 次,下载 3,207 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。

compound-eng-brainstorming 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

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 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

  • 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 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
compound-eng-brainstorming

复合工程头脑风暴 · 本页

10,012—需要联网MIT-0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

name
ia-brainstorming
class
workflow
description
>-

Brainstorming

Clarify WHAT to build before HOW to build it.

Hard Gate

No implementation until the design is approved. Brainstorming produces a design document, not code. Do not invoke implementation skills, write production code, or create files outside docs/brainstorms/ until the user explicitly approves the design and moves to planning.

Core Process

Phase 0: Assess and Ground

Before diving into questions, do two things:

Ground in the codebase (when applicable). If the brainstorm relates to existing code, read the relevant modules, patterns, and constraints before generating options. This prevents suggesting approaches that conflict with the actual architecture. Skip for purely abstract brainstorms (tech choices, product direction) where no codebase context applies.

Right-size the artifact. Match ceremony to problem size. If the brainstorm resolves in 3 messages, don't force a formal design doc -- a summary comment is enough. If it spans multiple sessions and touches architecture, write the full Phase 3 doc. No ceremony tax.

Assess whether brainstorming is needed:

Signals that requirements are clear:

  • User provided specific acceptance criteria
  • User referenced existing patterns to follow
  • User described exact behavior expected
  • Scope is constrained and well-defined

Signals that brainstorming is needed:

  • User used vague terms ("make it better", "add something like")
  • Multiple reasonable interpretations exist
  • Trade-offs haven't been discussed
  • User seems unsure about the approach
  • User described a solution ("build a dashboard") instead of a problem
  • Request spans multiple independent subsystems -- decompose first (see Scope Decomposition below)

If requirements are clear, suggest: "Your requirements seem clear. Consider proceeding directly to planning or implementation."

Scope Decomposition Gate

If the request describes multiple independent subsystems (e.g., "build a platform with chat, file storage, billing, and analytics"), flag this immediately. Don't spend questions refining details of a project that needs decomposition first.

  1. Identify the independent pieces and how they relate
  2. Determine build order (dependencies, shared infrastructure first)
  3. Brainstorm the first sub-project through the normal Phase 1-3 flow
  4. Each sub-project gets its own spec -> plan -> implementation cycle

Phase 1: Understand the Idea

User context calibration (before diving into the idea):

Read signals from the user's first message to calibrate communication register:

  • Vocabulary: Are they using technical terms (API, schema, migration) or describing experiences (it's slow, it breaks when...)?
  • Framing: Are they describing a solution ("build a dashboard") or a problem ("I can't see what's happening")?
  • References: Are they pointing to code, files, and patterns, or to analogies and comparisons ("something like Notion")?

Adjust question style accordingly. Technical users get architecture-level probing. Non-technical users get experience-level probing. Don't ask about this calibration -- just do it. If signals are ambiguous, default to the vocabulary the user is already using.

Explore project context first: Before asking questions, read existing files, docs, and recent commits related to the idea. Understanding what exists prevents asking questions the codebase already answers and grounds the conversation in reality.

Ask questions one at a time by default. When probing a single dimension (e.g., data model, auth flow), clustering 2-3 related questions together is acceptable.

Info-dump gate (when user offers rich context up-front): if the user's first message is substantial (>200 words, or dumps requirements in stream-of-consciousness), resist the urge to ask questions one-at-a-time. Instead, respond with 5-10 numbered clarifying questions the user can answer in shorthand (1: yes, 2: channel #ops, 3: no because backwards compat). Pick questions that remove ambiguity, not questions that show you read the dump. Exit this batched mode when the user's answers show they can be asked about edge cases without basics being explained back to them.

Example — after the user dumps a spec:

Before I propose approaches, 8 quick clarifications:

1. Auth — SSO (which provider?) or username/password?
2. Data retention — forever, or N-day rolling window?
3. Multi-tenant or single-tenant?
4. Sync or async for the webhook delivery?
5. Real users or service accounts allowed?
6. Target latency on the read path — P50? P99?
7. Which of the three integrations is P0?
8. "Fast enough" in the spec — what's the actual number?

Answer whichever you know; leave blanks for the rest.

Question Techniques:

  1. Prefer multiple choice when natural options exist

- Good: "Should the notification be: (a) email only, (b) in-app only, or (c) both?" - Avoid: "How should users be notified?"

  1. Start broad, then narrow

- First: What is the core purpose? - Then: Who are the users? - Finally: What constraints exist?

  1. Validate assumptions explicitly

- "I'm assuming users will be logged in. Is that correct?"

  1. Ask about success criteria early

- "How will you know this feature is working well?"

Key Topics to Explore:

TopicExample Questions
PurposeWhat problem does this solve? What's the motivation?
UsersWho uses this? What's their context?
ConstraintsAny technical limitations? Timeline? Dependencies?
SuccessHow will you measure success? What's the happy path?
Edge CasesWhat shouldn't happen? Any error states to consider?
Existing PatternsAre there similar features in the codebase to follow?
Non-goalsWhat is explicitly NOT in scope?

See deep-interview.md for deep interview techniques.

Exit Condition: Continue until the idea is clear OR user says "proceed". Before moving to Phase 2, summarize understanding in 3-5 bullets and confirm with the user.

Phase 2: Explore Approaches

After understanding the idea, propose 2-3 concrete approaches.

Structure for Each Approach:

### Approach A: [Name]

[2-3 sentence description]

**Pros:**
- [Benefit 1]
- [Benefit 2]

**Cons:**
- [Drawback 1]
- [Drawback 2]

**Best when:** [Circumstances where this approach shines]

Guidelines:

  • Lead with a recommendation and explain why
  • Be honest about trade-offs
  • Consider YAGNI--simpler is usually better
  • Reference codebase patterns when relevant
  • If no approach is accepted after 2 rounds, ask the user to describe their preferred direction directly

Ideation lenses (use 2-3 to stress-test approaches when the design space is wide):

  • Inversion: What if we solved the opposite problem?
  • Constraint removal: What would we build if [biggest constraint] didn't exist?
  • Audience shift: What if the primary user were [different persona]?
  • Combination: Can two weak approaches combine into a strong one?
  • Simplification: What's the version that ships in a day?
  • 10x version: What if this needed to handle 10x the scale?
  • Expert lens: How would [domain expert] approach this?

"Not Doing" list: Include an explicit list of what the chosen approach will NOT do. Focus is about saying no to good ideas. Make the trade-offs visible so they're a deliberate choice, not an oversight.

Assumptions with validation: For each key assumption in the chosen approach, state how to test it. Not just "we assume X" but "we assume X -- we'll know by [validation method]."

Phase 2.5: Pre-Write Scope Synthesis

Surface the scope interpretation so the user can correct it before Phase 3 writes the design doc. The synthesis is a chat-time scope checkpoint distinct from Phase 3b's post-draft self-review — 2.5 catches scope misalignment before the doc is written; 3b catches drafting issues after.

Present three labeled buckets plus a 1-3 line prose gloss:

Three buckets:

  • Stated — what the user said directly (original prompt, dialogue answers, approach selection). Each bullet has an explicit user-language anchor.
  • Inferred — gaps filled with assumptions. Scope boundaries the user never named, success criteria extrapolated from intent, technical assumptions the brief interview didn't probe. Most actionable bucket — bets the user can reject.
  • Out of scope — deliberately excluded items. Adjacent refactors, nice-to-haves, future-work items. Surfacing exclusions lets the user spot anything they wanted included.

Granularity rule: each bullet must be affirmable or rejectable on product/scope grounds without reading code or implementation details. File names, exact JSON shapes, schema fields, error wording are Phase 3 doc-body content — not synthesis content. If a bullet requires architectural evaluation to judge, re-cut it at scope level.

Prose gloss (required for all but truly-trivial cases): lead with a 1-3 line plain-language summary of *what's being proposed for the doc*. Forward-looking, not retrospective. The user may agree with each bullet but disagree with the framing — prose surfaces that gist. Skip only when the synthesis is ≤2 Stated bullets that just echo the prompt.

Anti-patterns:

  • Synthesis written as a proposal pitch ("Recommendation:", "Behavior when X:", file paths, JSON shapes) — that content belongs in Phase 3, not here.
  • Buckets padded to look thorough when one bucket would suffice.
  • Floating questions outside the three buckets. Every scope-shaping question must land in Stated, Inferred, or Out by synthesis time. If new ambiguities surface during synthesis composition, batch them in one round (per the Phase 1 info-dump pattern) and resolve them before presenting — never present a synthesis with adjacent unanswered questions.

Re-present after revision; write only on confirm. If the user revises any bullet (even trivially), integrate the change, re-present the revised synthesis, and wait for explicit confirmation before Phase 3. A revision is not a confirmation.

Headless mode (invoked via /ia-lfg or any disable-model-invocation context): compose the synthesis but skip the confirmation step. Route Inferred bets to a ## Assumptions section in the Phase 3 doc — explicitly labeled as un-validated bets — instead of into Key Decisions. Stated routes to Requirements; Out-of-scope routes to Non-Goals as usual.

Skip Phase 2.5 entirely on the trivial fast path (Phase 0 detected requirements were already clear and the flow went straight to a short summary).

Phase 3: Capture the Design

Summarize key decisions in a structured format. For each major component, verify isolation and clarity: it must answer "what does it do, how do you use it, what does it depend on?" and be independently understandable and testable. If working in an existing codebase, note which existing patterns to follow and where targeted improvements fit naturally.

Design Doc: Save to docs/brainstorms/YYYY-MM-DD-<topic>-brainstorm.md. Required sections: What We're Building, Why This Approach, Key Decisions (with rationale), Open Questions, Next Steps. Collapse the Q&A interview log in a <details> block. Include YAML frontmatter with date and topic. Commit to git -- design decisions are project history.

Phase 3b: Spec Self-Review

Before presenting the design doc, run this checklist against the draft. Any failure means return to Phase 2 or Phase 3, not Phase 4.

  • Placeholder scan: no "TBD", "figure out later", "appropriate error handling", bracketed gaps, or tasks without concrete criteria
  • Internal consistency: names, types, and verbs referenced in one section match every other section (no createOrder() in one place and placeOrder() in another)
  • Scope containment: every decision traces back to a stated goal. If a decision doesn't, cut it or surface it as an explicit scope expansion with rationale
  • Ambiguity sweep: read each Key Decision and ask "could a reasonable implementer interpret this two ways?" If yes, tighten the wording before handoff
  • Assumption validation: every assumption has a stated validation method (not just "we assume X" but "we assume X — we'll confirm by Y")
  • Non-goals list present: the explicit "Not Doing" list exists and is specific, not boilerplate

Silent pass is a valid outcome. If the draft is clean, say so and move to Phase 4.

Phase 4: Review and Handoff

Present the design doc to the user for approval. The user explicitly confirming the design is the gate to proceed. When invoked via /ia-brainstorm, the command handles spec review dispatch and next-step orchestration.

Headless mode (invoked via /ia-lfg or any disable-model-invocation context): skip the user approval step at Phase 4 — same carve-out as Phase 2.5. The doc-write completes; the artifact is the audit surface for downstream review (/ia-plan, PR review, the ia-document-review skill), not chat confirmation.

Anti-Patterns to Avoid

Anti-PatternBetter Approach
Asking 5 questions at onceAsk one at a time across dimensions; cluster 2-3 within a dimension
Jumping to implementation detailsStay focused on WHAT, not HOW
Proposing overly complex solutionsStart simple, add complexity only if needed
Ignoring existing codebase patternsResearch what exists first
Making assumptions without validatingState assumptions explicitly and confirm
Creating lengthy design documentsKeep it concise--details go in the plan

Success Criteria

  • Design doc saved to docs/brainstorms/YYYY-MM-DD-<topic>-brainstorm.md
  • User explicitly approves the spec before handoff to planning
  • All open questions resolved or explicitly deferred with rationale

Integration

Brainstorming answers WHAT to build. Planning answers HOW. When brainstorm output exists, /ia-plan detects it and skips idea refinement.

  • Next step: /ia-plan (always)
  • Threat modeling: when the brainstorm involves auth, payments, external API surfaces, or multi-tenant data, suggest a ia-security-sentinel threat model before moving to planning. Catching trust boundary issues at the design stage prevents costly rework.
  • Predecessor: user request or ambiguous feature description

平台分布

OpenClaw

85.37%
按下载量换算2,738

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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