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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 44,194。

总安装 930周安装 38GitHub Stars 6,572下载 301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/mindfold-ai/trellis
仓库路径:skills/brainstorm
安装命令:
npx skills add https://github.com/mindfold-ai/trellis --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/mindfold-ai/trellis --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。

用于查找、检索和筛选相关信息,适合快速定位候选结果。可根据关键词、任务场景或来源线索在多种宿主中调用。通过 GitHub 安装,支持 Codex、Claude、Cursor、Gemini CLI 等宿主环境。安装前建议确认权限范围、维护状态及是否触发联网或文件读写操作。

可结合来源仓库和原始 README 进一步核验具体用法。

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/mindfold-ai/trellis --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/mindfold-ai/trellis --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 930 次,近一周安装 38 次,下载 301 次,GitHub 6,572 星。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。
  • 来源仓库有 6,572 星,维护活跃度相对可查。

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

9306,572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 - Requirements Discovery (AI Coding Enhanced)

Guide AI through collaborative requirements discovery before implementation, optimized for AI coding workflows:

  • Task-first (capture ideas immediately)
  • Action-before-asking (reduce low-value questions)
  • Research-first for technical choices (avoid asking users to invent options)
  • Diverge → Converge (expand thinking, then lock MVP)

When to Use

Triggered from $start when the user describes a development task, especially when:

  • requirements are unclear or evolving
  • there are multiple valid implementation paths
  • trade-offs matter (UX, reliability, maintainability, cost, performance)
  • the user might not know the best options up front

Core Principles (Non-negotiable)

  1. Task-first (capture early) Always ensure a task exists at the start so the user's ideas are recorded immediately.
  2. Action before asking If you can derive the answer from repo code, docs, configs, conventions, or quick research — do that first.
  3. One question per message Never overwhelm the user with a list of questions. Ask one, update PRD, repeat.
  4. Prefer concrete options For preference/decision questions, present 2–3 feasible, specific approaches with trade-offs.
  5. Research-first for technical choices If the decision depends on industry conventions / similar tools / established patterns, do research first, then propose options.
  6. Diverge → Converge After initial understanding, proactively consider future evolution, related scenarios, and failure/edge cases — then converge to an MVP with explicit out-of-scope.
  7. No meta questions Do not ask "should I search?" or "can you paste the code so I can continue?" If you need information: search/inspect. If blocked: ask the minimal blocking question.

Step 0: Ensure Task Exists (ALWAYS)

Before any Q&A, ensure a task exists. If none exists, create one immediately.

  • Use a temporary working title derived from the user's message.
  • It's OK if the title is imperfect — refine later in PRD.
TASK_DIR=$(python3 ./.trellis/scripts/task.py create "brainstorm: <short goal>" --slug <auto>)

Create/seed prd.md immediately with what you know:

# brainstorm: <short goal>

## Goal

<one paragraph: what + why>

## What I already know

* <facts from user message>
* <facts discovered from repo/docs>

## Assumptions (temporary)

* <assumptions to validate>

## Open Questions

* <ONLY Blocking / Preference questions; keep list short>

## Requirements (evolving)

* <start with what is known>

## Acceptance Criteria (evolving)

* [ ] <testable criterion>

## Definition of Done (team quality bar)

* Tests added/updated (unit/integration where appropriate)
* Lint / typecheck / CI green
* Docs/notes updated if behavior changes
* Rollout/rollback considered if risky

## Out of Scope (explicit)

* <what we will not do in this task>

## Technical Notes

* <files inspected, constraints, links, references>
* <research notes summary if applicable>

Step 1: Auto-Context (DO THIS BEFORE ASKING QUESTIONS)

Before asking questions like "what does the code look like?", gather context yourself:

Repo inspection checklist

  • Identify likely modules/files impacted
  • Locate existing patterns (similar features, conventions, error handling style)
  • Check configs, scripts, existing command definitions
  • Note any constraints (runtime, dependency policy, build tooling)

Documentation checklist

  • Look for existing PRDs/specs/templates
  • Look for command usage examples, README, ADRs if any

Write findings into PRD:

  • Add to What I already know
  • Add constraints/links to Technical Notes

Step 2: Classify Complexity (still useful, not gating task creation)

ComplexityCriteriaAction
TrivialSingle-line fix, typo, obvious changeSkip brainstorm, implement directly
SimpleClear goal, 1–2 files, scope well-definedAsk 1 confirm question, then implement
ModerateMultiple files, some ambiguityLight brainstorm (2–3 high-value questions)
ComplexVague goal, architectural choices, multiple approachesFull brainstorm
Note: Task already exists from Step 0. Classification only affects depth of brainstorming.

Step 3: Question Gate (Ask ONLY high-value questions)

Before asking ANY question, run the following gate:

Gate A — Can I derive this without the user?

If answer is available via:

  • repo inspection (code/config)
  • docs/specs/conventions
  • quick market/OSS research

→ Do not ask. Fetch it, summarize, update PRD.

Gate B — Is this a meta/lazy question?

Examples:

  • "Should I search?"
  • "Can you paste the code so I can proceed?"
  • "What does the code look like?" (when repo is available)

→ Do not ask. Take action.

Gate C — What type of question is it?

  • Blocking: cannot proceed without user input
  • Preference: multiple valid choices, depends on product/UX/risk preference
  • Derivable: should be answered by inspection/research

→ Only ask Blocking or Preference.


Step 4: Research-first Mode (Mandatory for technical choices)

Trigger conditions (any → research-first)

  • The task involves selecting an approach, library, protocol, framework, template system, plugin mechanism, or CLI UX convention
  • The user asks for "best practice", "how others do it", "recommendation"
  • The user can't reasonably enumerate options

Research steps

  1. Identify 2–4 comparable tools/patterns
  2. Summarize common conventions and why they exist
  3. Map conventions onto our repo constraints
  4. Produce 2–3 feasible approaches for our project

Research output format (PRD)

Add a section in PRD (either within Technical Notes or as its own):

## Research Notes

### What similar tools do

* ...
* ...

### Constraints from our repo/project

* ...

### Feasible approaches here

**Approach A: <name>** (Recommended)

* How it works:
* Pros:
* Cons:

**Approach B: <name>**

* How it works:
* Pros:
* Cons:

**Approach C: <name>** (optional)

* ...

Then ask one preference question:

  • "Which approach do you prefer: A / B / C (or other)?"

Step 5: Expansion Sweep (DIVERGE) — Required after initial understanding

After you can summarize the goal, proactively broaden thinking before converging.

Expansion categories (keep to 1–2 bullets each)

  1. Future evolution

- What might this feature become in 1–3 months? - What extension points are worth preserving now?

  1. Related scenarios

- What adjacent commands/flows should remain consistent with this? - Are there parity expectations (create vs update, import vs export, etc.)?

  1. Failure & edge cases

- Conflicts, offline/network failure, retries, idempotency, compatibility, rollback - Input validation, security boundaries, permission checks

Expansion message template (to user)

I understand you want to implement: <current goal>.

Before diving into design, let me quickly diverge to consider three categories (to avoid rework later):

1. Future evolution: <1–2 bullets>
2. Related scenarios: <1–2 bullets>
3. Failure/edge cases: <1–2 bullets>

For this MVP, which would you like to include (or none)?

1. Current requirement only (minimal viable)
2. Add <X> (reserve for future extension)
3. Add <Y> (improve robustness/consistency)
4. Other: describe your preference

Then update PRD:

  • What's in MVP → Requirements
  • What's excluded → Out of Scope

Step 6: Q&A Loop (CONVERGE)

Rules

  • One question per message
  • Prefer multiple-choice when possible
  • After each user answer:

- Update PRD immediately - Move answered items from Open Questions → Requirements - Update Acceptance Criteria with testable checkboxes - Clarify Out of Scope

Question priority (recommended)

  1. MVP scope boundary (what is included/excluded)
  2. Preference decisions (after presenting concrete options)
  3. Failure/edge behavior (only for MVP-critical paths)
  4. Success metrics & Acceptance Criteria (what proves it works)

Preferred question format (multiple choice)

For <topic>, which approach do you prefer?

1. **Option A** — <what it means + trade-off>
2. **Option B** — <what it means + trade-off>
3. **Option C** — <what it means + trade-off>
4. **Other** — describe your preference

Step 7: Propose Approaches + Record Decisions (Complex tasks)

After requirements are clear enough, propose 2–3 approaches (if not already done via research-first):

Based on current information, here are 2–3 feasible approaches:

**Approach A: <name>** (Recommended)

* How:
* Pros:
* Cons:

**Approach B: <name>**

* How:
* Pros:
* Cons:

Which direction do you prefer?

Record the outcome in PRD as an ADR-lite section:

## Decision (ADR-lite)

**Context**: Why this decision was needed
**Decision**: Which approach was chosen
**Consequences**: Trade-offs, risks, potential future improvements

Step 8: Final Confirmation + Implementation Plan

When open questions are resolved, confirm complete requirements with a structured summary:

Final confirmation format

Here's my understanding of the complete requirements:

**Goal**: <one sentence>

**Requirements**:

* ...
* ...

**Acceptance Criteria**:

* [ ] ...
* [ ] ...

**Definition of Done**:

* ...

**Out of Scope**:

* ...

**Technical Approach**:
<brief summary + key decisions>

**Implementation Plan (small PRs)**:

* PR1: <scaffolding + tests + minimal plumbing>
* PR2: <core behavior>
* PR3: <edge cases + docs + cleanup>

Does this look correct? If yes, I'll proceed with implementation.

Subtask Decomposition (Complex Tasks)

For complex tasks with multiple independent work items, create subtasks:

# Create child tasks
CHILD1=$(python3 ./.trellis/scripts/task.py create "Child task 1" --slug child1 --parent "$TASK_DIR")
CHILD2=$(python3 ./.trellis/scripts/task.py create "Child task 2" --slug child2 --parent "$TASK_DIR")

# Or link existing tasks
python3 ./.trellis/scripts/task.py add-subtask "$TASK_DIR" "$CHILD_DIR"

PRD Target Structure (final)

prd.md should converge to:

# <Task Title>

## Goal

<why + what>

## Requirements

* ...

## Acceptance Criteria

* [ ] ...

## Definition of Done

* ...

## Technical Approach

<key design + decisions>

## Decision (ADR-lite)

Context / Decision / Consequences

## Out of Scope

* ...

## Technical Notes

<constraints, references, files, research notes>

Anti-Patterns (Hard Avoid)

  • Asking user for code/context that can be derived from repo
  • Asking user to choose an approach before presenting concrete options
  • Meta questions about whether to research
  • Staying narrowly on the initial request without considering evolution/edges
  • Letting brainstorming drift without updating PRD

Integration with Start Workflow

After brainstorm completes (Step 8 confirmation approved), the flow continues to the Task Workflow's Phase 2: Prepare for Implementation:

Brainstorm
  Step 0: Create task directory + seed PRD
  Step 1–7: Discover requirements, research, converge
  Step 8: Final confirmation → user approves
  ↓
Task Workflow Phase 2 (Prepare for Implementation)
  Code-Spec Depth Check (if applicable)
  → Research codebase (based on confirmed PRD)
  → Configure code-spec context (jsonl files)
  → Activate task
  ↓
Task Workflow Phase 3 (Execute)
  Implement → Check → Complete

The task directory and PRD already exist from brainstorm, so Phase 1 of the Task Workflow is skipped entirely.


Related Commands

CommandWhen to Use
$startEntry point that triggers brainstorm
$finish-workAfter implementation is complete
$update-specIf new patterns emerge during work

平台分布

Codex

39.31%
按下载量换算118

Claude

28.12%
按下载量换算85

Cursor

20.14%
按下载量换算61

Gemini CLI

8.8%
按下载量换算26

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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