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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 73,674 个 Skill 里排第 44,750。

总安装 894周安装 38GitHub Stars 6下载 313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/duc01226/easyplatform
仓库路径:skills/brainstorm
安装命令:
npx skills add https://github.com/duc01226/easyplatform --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/duc01226/easyplatform --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 中快速定位候选结果。适用于需要根据关键词或任务场景进行信息检索和来源线索筛选的场景。通过 npx skills add 命令从指定 GitHub 仓库安装使用。

安装前需确认权限范围、维护状态及是否触发联网或文件操作。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/duc01226/easyplatform --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/duc01226/easyplatform --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 894 次,近一周安装 38 次,下载 313 次,GitHub 6 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。

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

8946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

[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set in_progress when step starts, set completed when step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.
[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting. This prevents context loss from long sessions.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Quick Summary

Goal: Facilitate a structured PO/BA brainstorming session using the Double Diamond process — diverge to discover problems and opportunities, then converge to validate and prioritize ideas before committing to implementation.

Three Scenarios:

ScenarioEntry TriggerPrimary Methods
Problem-Solving"Something is broken / users complain / metric is bad"5 Whys → Fishbone → HMW → SCAMPER → Hypothesis RAT
New Product"Greenfield idea / new market / no codebase yet"JTBD → Lean Canvas → Crazy 8s → Opportunity Scoring → Lean Hypothesis
Feature Enhancement"Existing product / add capability / improve flow"Opportunity Solution Tree → SCAMPER → Impact Mapping → RICE → Value Hypothesis

Double Diamond (master meta-framework):

DIAMOND 1: Right Problem          DIAMOND 2: Right Solution
────────────────────────────      ──────────────────────────
Discover ──► Define               Develop ──► Deliver
(diverge)    (converge)           (diverge)   (converge)

Golden Rule: NEVER evaluate ideas while generating them. Diverge and converge are separate modes. Mixing them kills creative output.

Be skeptical. Apply critical thinking. Every idea needs a testable hypothesis. Confidence >80% required before recommending.


Answer this question:

$ARGUMENTS


Phase 0: Session Setup (MANDATORY)

Use AskUserQuestion to detect scenario, role, and constraints before any technique.

0.1 — Scenario Detection

Ask:

  1. "What scenario are we in?"

- Problem-solving — something is broken, users struggle, a metric is bad - New product — greenfield, no existing product in this space - Feature enhancement — existing product, add/improve/remove capability - Mixed — multiple of the above

  1. "What is the primary role in this session?"

- Product Owner — outcome-focused, business value, user outcomes - Business Analyst — requirements-focused, process analysis, stakeholder mapping - Both PO + BA — full discovery and requirements - Developer / Architect — technical feasibility brainstorm

  1. "How much is already known?"

- Raw seed — just an intuition or observation - Problem confirmed — we know the problem, need solutions - Solution direction known — need to evaluate and score options - Idea exists — need hypothesis validation only

0.2 — Context Loading

  • If project codebase exists: read docs/business-features/ to understand domain
  • If greenfield: skip codebase reading; rely on user input and web research
  • Load docs/project-reference/domain-entities-reference.md if entity context needed
  • Use WebSearch for market/competitor context when scenario = New Product or Enhancement

Phase 1: Problem Framing — Diamond 1 Diverge

Goal: Fully understand the problem space before jumping to solutions. The #1 failure in brainstorming: solving the wrong problem.

Time-box: 20–45 minutes of session time.

1.1 — Problem Statement (POV Format)

Formulate a crisp problem statement BEFORE any ideation:

[User/Persona] needs [need/job-to-be-done]
because [insight/root cause/context],
but [current barrier/friction/failure].

Example:

HR Managers need to quickly identify top performers for promotion
because quarterly reviews create promotion backlogs,
but the current system shows raw scores with no ranking or comparison.

Use AskUserQuestion to validate:

  • "Is this the core problem, or a symptom of a deeper problem?"
  • "Who specifically experiences this? How often? What's the cost?"
  • "What evidence do we have this problem actually exists?"

1.2 — Root Cause Analysis (for Problem-Solving scenario)

Apply one of:

5 Whys:

Problem: [stated problem]
Why 1: [first cause]
Why 2: [cause of cause 1]
Why 3: [cause of cause 2]
Why 4: [cause of cause 3]
Why 5: [root cause] ← Fix HERE, not at Why 1

Fishbone (Ishikawa) — for systemic problems: Spine = problem statement. Bones = 6 cause categories:

  • People, Process, Technology, Data, Environment, Policy
  • For each bone: ask "What in this category could cause the problem?"

1.3 — JTBD (Jobs-To-Be-Done) — for New Product & Enhancement

Replace user stories with job stories to expose real motivation:

User Story (what): As a manager, I want to see employee scores, so that I can make decisions.

Job Story (why + context): When I'm preparing for quarterly reviews with limited time, I want to instantly see who deserves promotion without reading every profile, so I can make fair, defensible decisions before the deadline.

Job Story Formula:

When [triggering situation + context],
I want to [motivation / job to be done],
so I can [outcome / expected result].

Generate 3–5 job stories covering main user segments. Each story = one opportunity.

1.4 — HMW (How Might We) Reframing

Transform problem statements into ideation-ready questions:

Formula: "How might we [verb] [object] so that [desired outcome]?"

From the POV statement:

  • "How might we help HR managers rank employees so that promotion decisions take minutes not days?"
  • "How might we surface hidden top performers so that managers discover talent they'd otherwise miss?"
  • "How might we reduce bias in performance scoring so that promotion feels fair to all employees?"

Rules:

  • Each HMW covers ONE idea direction
  • Generate 5–10 HMW questions per problem
  • Too broad = "How might we improve HR?" (useless) → too narrow = "How might we add a sort button?" (skip ideation, just build it)
  • Sweet spot: one-concept questions that invite multiple solutions

Output of Phase 1:

  • Problem statement (POV format)
  • Root cause (5 Whys or Fishbone) — Problem-Solving only
  • 3–5 Job Stories
  • 5–10 HMW questions

Phase 2: Opportunity Framing — Diamond 1 Converge

Goal: Narrow problem space to the highest-opportunity focus areas before ideating solutions.

2.1 — Opportunity Solution Tree (OST) — for Enhancement

Teresa Torres' framework. Maps desired outcome → opportunities → solutions → experiments.

Desired Outcome (business metric)
├── Opportunity 1 (unmet user need / pain / want)
│   ├── Solution A
│   └── Solution B
├── Opportunity 2
│   ├── Solution C
│   └── Solution D
└── Opportunity 3 (deprioritized)

Step 1: State ONE desired outcome (lagging metric the team owns — e.g., "Increase manager satisfaction with review process from 3.2 to 4.0 CSAT") Step 2: Map ALL known opportunities (pains, needs, wants) from research/interviews Step 3: For each top opportunity, generate solution directions (not detailed solutions yet) Step 4: Pick 1–2 opportunities to develop further in Phase 3

2.2 — Lean Canvas — for New Product

One-page business model for greenfield ideas (Ash Maurya):

BlockQuestion
ProblemTop 3 problems being solved
Customer SegmentsWho has this problem? Early adopters?
Unique Value PropSingle compelling message
SolutionTop 3 features (not full spec)
ChannelsHow to reach customers
Revenue StreamsHow to make money
Cost StructureFixed + variable costs
Key MetricsOne number that measures success
Unfair AdvantageWhat can't easily be copied?

Fill one canvas per major target segment. Keep it to 20 min — speed is the point.

2.3 — Blue Ocean ERRC Grid — for Enhancement or New Product

Eliminate-Reduce-Raise-Create grid (Chan Kim & Mauborgne):

EliminateReduce
Features users never useFeatures that are over-engineered
RaiseCreate
Features users want more ofFeatures no competitor offers

Rule: Every innovation should have at least ONE item in Create AND one in Eliminate. A product with only Raise entries is incremental — not differentiated.

2.4 — Value Proposition Canvas

Connects customer profile to product value:

Customer Profile:

  • Jobs (functional, social, emotional)
  • Pains (frustrations, obstacles, risks)
  • Gains (benefits, desires, measures of success)

Value Map:

  • Products & Services (what you offer)
  • Pain Relievers (how you reduce pains)
  • Gain Creators (how you produce gains)

Fit = where Pain Relievers match Pains + Gain Creators match Gains.

Output of Phase 2:

  • OST with 2 selected opportunities (Enhancement)
  • Lean Canvas (New Product)
  • ERRC grid (New Product or Enhancement)
  • Value Proposition fit assessment

Phase 3: Ideation — Diamond 2 Diverge

Goal: Generate maximum quantity of solution ideas without judgment. Quality comes in Phase 4.

Critical rule: NO evaluation in this phase. Every idea is valid. "Yes, and..." not "Yes, but..."

3.1 — SCAMPER

Apply each lens to the problem/existing product to generate solution directions:

LetterPromptExample for HR review feature
SubstituteWhat can be replaced?Replace manual scoring with AI-assisted ranking
CombineWhat can be merged?Combine performance + feedback + OKR in one view
AdaptWhat can be borrowed?Adapt Netflix recommendation to suggest top performers
ModifyWhat can be scaled/shrunk?Minimize review to a weekly pulse check
Put to other useDifferent context?Use review data for learning path recommendations
EliminateWhat can be removed?Eliminate annual review — replace with continuous signals
ReverseFlip the process?Let employees score managers instead

Generate at least 2 ideas per SCAMPER letter = minimum 14 ideas.

3.2 — Crazy 8s (Rapid Visual Ideation)

Time-box: 8 minutes. 8 ideas. No refinement.

Process:

  1. Fold paper into 8 sections (or create 8 boxes mentally)
  2. Sketch one idea concept per box — rough is fine
  3. Timer forces quantity over perfection
  4. Share and build on sketches

For AI-facilitated sessions:

  • AI generates 8 distinct solution directions in 2 minutes
  • User picks top 3 to explore deeper
  • Each direction = 1 sentence + 1 key differentiator

3.3 — Brainwriting 6-3-5

For multi-stakeholder sessions (async-friendly):

  • 6 participants, 3 ideas each, 5 rounds
  • Each round: read previous ideas → add 3 new ideas OR build on existing
  • Result: up to 108 ideas in 30 minutes (works async via shared doc)

For AI-facilitated sessions:

  • AI plays all 6 roles across 3 rounds
  • Generates ideas from: PO perspective, BA perspective, End User perspective, Dev perspective, Ops perspective, Business perspective

3.4 — Impact Mapping

Gojko Adzic's technique. Maps Goal → Actors → Impacts → Deliverables:

GOAL: [business outcome with measurable target]
├── ACTOR: Who can help/hinder?
│   ├── IMPACT: How should behavior change?
│   │   └── DELIVERABLE: What feature produces this impact?
│   └── IMPACT: What negative behavior to prevent?
│       └── DELIVERABLE: What reduces this risk?
└── ACTOR: ...

Key insight: Work backward from GOAL. If a deliverable doesn't trace to an actor behavior change, don't build it.

3.5 — Analogical Thinking

"How does [industry X] solve [similar problem Y]?"

Analogy SourceApplication to HR
Spotify Discover WeeklyPersonalized learning recommendations
Uber surge pricingDynamic bonus pool allocation
GitHub PR reviewsPeer skill endorsement with evidence
Amazon recommendation engineNext goal suggestion
Netflix "because you watched""Colleagues like you also achieved..."

Output of Phase 3:

  • SCAMPER grid with 14+ ideas
  • Crazy 8s — 8 solution directions
  • Impact Map (top 2 goals)
  • Analogy-inspired ideas (3–5)
  • Total raw idea count: target 25–40 ideas

Phase 4: Evaluation & Convergence — Diamond 2 Converge

Goal: Reduce 25–40 raw ideas to a ranked shortlist of 3–5 candidates for hypothesis testing.

4.1 — Dot Voting (First Pass)

Before scoring, do a quick gut-check elimination:

  • Each idea gets a ✅ (keep) / ❌ (drop) / 🔄 (merge with another)
  • Merge near-identical ideas
  • Drop ideas that violate hard constraints (budget, tech, legal)
  • Target: reduce to 10–15 candidates

4.2 — RICE Scoring

Rank remaining candidates:

RICE Score = (Reach × Impact × Confidence) / Effort

Reach:      Users affected per quarter (100 / 500 / 1000 / 5000+)
Impact:     0.25 minimal | 0.5 low | 1 medium | 2 high | 3 massive
Confidence: 0.5 low (gut feel) | 0.8 medium (some data) | 1.0 high (validated)
Effort:     Story Points — 1 trivial | 3 small | 5 medium | 8 large | 13 very large

Score all 10–15 candidates. Sort descending. Top 5 = shortlist.

4.3 — Kano Model Classification

For each shortlisted idea, classify:

CategoryDescriptionIf absentIf presentExample
Must-BeBaseline expectationUsers angryUsers neutralLogin works
PerformanceMore = betterUsers dissatisfiedUsers satisfiedFaster load
DelighterUnexpected valueUsers neutralUsers delightedSmart suggestion
IndifferentDoesn't matterUsers neutralUsers neutralIcon colors
ReverseSome want, some don'tSegment upsetSegment happyAuto-fill

Strategy: Must-Be → Performance → Delighter. Never skip Must-Be items for Delighters.

4.4 — Effort × Impact 2×2

Quick visual triage:

HIGH IMPACT
    │  Quick Wins ★    │  Major Projects ⚙️
    │  (do first)      │  (schedule carefully)
────┼──────────────────┼────────────────────
    │  Fill-Ins 📋     │  Money Pits ⚠️
    │  (if time)       │  (avoid or cut)
LOW IMPACT
         LOW EFFORT         HIGH EFFORT

Plot each shortlisted idea. Quick Wins = default first picks unless Major Project has strategic necessity.

4.5 — MoSCoW for Release Scope

For each idea in the shortlist, assign release priority:

PriorityMeaningThreshold
Must HaveMVP is broken without itInclude if >80% of value depends on it
Should HaveImportant but MVP works without itInclude if RICE > median
Could HaveNice to have, low risk to cutInclude if effort ≤ 3 SP
Won't HaveExplicitly out of scope this cycleDocument for future

Output of Phase 4:

  • Dot-voted shortlist (10–15 ideas)
  • RICE-scored table (top 5 ranked)
  • Kano classification for each shortlisted idea
  • 2×2 matrix placement
  • MoSCoW assignment per idea

Phase 5: Hypothesis Validation

Goal: Before committing to build, test your riskiest assumptions. 42% of startups fail because no market need — validate before building.

5.1 — Problem Hypothesis

**We believe** [target users/persona]
**Experience** [specific problem]
**Because** [root cause]
**We'll know this is true when** [validation metric/observable evidence]

Example:

We believe HR Managers
Experience frustration identifying top performers during review cycles
Because scoring data is fragmented across 3 systems with no unified ranking
We'll know this is true when 3+ managers confirm they spend >2hrs per cycle on manual data aggregation

5.2 — Value Hypothesis

**We believe** [feature/solution]
**Will deliver** [specific value/outcome]
**To** [target users]
**We'll know we're right when** [measurable success metric]

5.3 — Riskiest Assumption Test (RAT)

Identify the ONE assumption whose failure kills the idea:

  1. List all assumptions: user behavior, technical feasibility, market demand, business model
  2. Score each: Probability of being wrong (0–1) × Impact if wrong (0–1)
  3. Highest score = Riskiest Assumption
  4. Design cheapest possible test to validate/invalidate it before full build:

- User interview (2–3 days) - Landing page / fake door test (1 week) - Prototype click-through (3–5 days) - Concierge MVP (1–2 weeks) - Smoke test / pre-sell (2–4 weeks)

5.4 — Build-Measure-Learn Loop

For each top idea, define the loop:

BUILD: Minimum experiment to test the assumption (not a full product)
MEASURE: One metric that proves/disproves the hypothesis
LEARN: What decision do we make if metric is met / not met?
PIVOT: If hypothesis invalidated — which alternative from Phase 3 do we try next?

Output of Phase 5:

  • Problem hypothesis card per top-3 idea
  • Value hypothesis card per top-3 idea
  • Riskiest Assumption identified per idea
  • Cheapest test designed
  • Build-Measure-Learn loop defined

Phase 6: Decision & Recommendations

Goal: Present a clear, opinionated recommendation with trade-offs. Not "here are all the options" — "here's what we recommend and why."

6.1 — Top 3 Options Table

Present final shortlist as a decision table:

OptionRICEKanoEffortRiskRAT TestRecommendation
Option A320Delighter5 SPMedium3-day interview⭐ Recommended
Option B180Performance8 SPLowPrototypeViable
Option C90Must-Be13 SPHighPre-sellDefer

6.2 — Recommendation Statement

RECOMMENDED: [Option Name]

Why: [1–2 sentences on RICE + Kano + strategic fit]
Risk: [Primary risk + mitigation]
First step: [Cheapest test to validate before full commitment]
Time to validation: [Days/weeks]

6.3 — Dependency & Sequencing Check

  • Does Option A depend on any existing feature/data/service not yet built?
  • Can experiments run in parallel?
  • What's the critical path to first validated learning?

Phase 7: Documentation & Handoff

Report Output

Use naming pattern from ## Naming section in injected context.

Create markdown summary report:

# Brainstorm Session Report: [Topic]

## Session Context

- Scenario: [Problem-Solving / New Product / Enhancement]
- Role: [PO / BA / Mixed]
- Date: [YYYY-MM-DD]
- Input: [Original question/problem]

## Problem Statement

[POV format]

## Root Cause Analysis

[5 Whys or Fishbone — if Problem-Solving]

## Job Stories

1. [Job Story 1]
2. [Job Story 2]
3. [Job Story 3]

## HMW Questions

1. How might we...
2. How might we...

## Opportunity Map

[OST or Lean Canvas — per scenario]

## Raw Ideas Generated

[Total count: XX ideas across SCAMPER / Crazy 8s / Impact Mapping]

## Scored Shortlist (RICE)

| Rank | Idea | RICE | Kano | Effort | Priority    |
| ---- | ---- | ---- | ---- | ------ | ----------- |
| 1    | ...  | ...  | ...  | ...    | Must Have   |
| 2    | ...  | ...  | ...  | ...    | Should Have |

## Hypothesis Cards

### Top Recommendation: [Option Name]

- Problem Hypothesis: ...
- Value Hypothesis: ...
- Riskiest Assumption: ...
- Cheapest Test: ...
- Success Metric: ...

## Decision

[Recommendation + rationale]

## Next Steps

- [ ] [First concrete action]
- [ ] [Validation test]
- [ ] [Stakeholder alignment needed]

Technique Quick Reference

TechniquePhaseWhen to UseTime-box
POV StatementP1Always10 min
5 WhysP1Problem-solving scenario15 min
FishboneP1Systemic/complex problems20 min
JTBD / Job StoriesP1New product or enhancement20 min
HMW QuestionsP1Always — bridge problem → ideation15 min
Opportunity Solution TreeP2Enhancement scenario30 min
Lean CanvasP2New product scenario20 min
Blue Ocean ERRCP2Differentiation needed20 min
Value Proposition CanvasP2Product-market fit unclear25 min
SCAMPERP3Always — structured ideation30 min
Crazy 8sP3Need quantity fast8 min
Brainwriting 6-3-5P3Multi-stakeholder, async30 min
Impact MappingP3Outcome-first thinking30 min
Analogical ThinkingP3Novel/creative directions needed15 min
Dot VotingP4First-pass elimination10 min
RICE ScoringP4Always for prioritization20 min
Kano ModelP4Feature classification15 min
2×2 Effort/ImpactP4Visual triage10 min
MoSCoWP4Release scoping15 min
Problem HypothesisP5Always before committing15 min
Value HypothesisP5Always before committing15 min
Riskiest Assumption TestP5Before full build20 min
Build-Measure-LearnP5Lean validation20 min

Role-Specific Guidance

PO Mode (Outcome Focus)

  • Lead with: desired business outcome → opportunities → experiments
  • Use: OST, Impact Mapping, RICE, Build-Measure-Learn
  • Ask: "What behavior change do we need to see in users?"
  • Resist: jumping to features before validating the outcome

BA Mode (Requirements Focus)

  • Lead with: stakeholder needs → process gaps → requirements
  • Use: BABOK elicitation (interviews, workshops, document analysis), Fishbone, JTBD
  • Ask: "What does the system need to do to enable that behavior?"
  • Resist: over-specifying before the PO validates the opportunity

Mixed PO + BA Mode

  • PO owns: problem statement, opportunity framing, prioritization, hypothesis
  • BA owns: requirements elicitation, acceptance criteria, edge cases, process mapping
  • Handoff point: after Phase 4 (scored shortlist) → BA writes acceptance criteria per idea

Collaboration Tools

  • planner agent — research industry best practices for specific domain
  • docs-manager agent — understand existing feature constraints and domain context
  • WebSearch — market/competitor context for new product scenarios
  • docs-seeker skill — latest documentation for external plugins/APIs
  • ai-multimodal skill — analyze visual mockups, screenshots, competitor UIs
  • sequential-thinking skill — complex problem decomposition requiring structured causal chains
  • web-research skill — deep market research for greenfield or competitive analysis

Scenario Cheat Sheets

Scenario A: Problem-Solving

1. POV Statement → 2. 5 Whys / Fishbone → 3. HMW Questions
→ 4. SCAMPER on current solution → 5. RICE scoring
→ 6. Problem Hypothesis + RAT → 7. Recommend + cheapest test

Scenario B: New Product

1. Job Stories (JTBD) → 2. Lean Canvas → 3. Blue Ocean ERRC
→ 4. HMW Questions → 5. Crazy 8s / Brainwriting
→ 6. Kano Classification → 7. Value Hypothesis + RAT → 8. MVP scope

Scenario C: Feature Enhancement

1. Job Stories (JTBD) → 2. Opportunity Solution Tree
→ 3. HMW Questions → 4. SCAMPER on existing feature
→ 5. Impact Mapping → 6. RICE scoring → 7. 2×2 matrix
→ 8. Value Hypothesis + RAT → 9. Recommend + next experiment

Anti-Patterns to Avoid

Anti-PatternWhy It FailsBetter Approach
Jumping to solutions before defining problemBuilds the wrong thingAlways complete Phase 1 first
Evaluating ideas while generating themKills creative output, premature closureStrict diverge/converge separation
One stakeholder perspective onlyMisses jobs, pains, contextBrainwriting from 6 different roles
No hypothesis before building42% of features fail — no market needAlways write hypothesis + RAT
RICE without confidence scoreOverestimates low-evidence ideasAlways include Confidence as a multiplier
Kano ignored — building only DelightersUsers can't use a delighter with broken Must-BesPrioritize Must-Be → Performance → Delighter
"Best idea wins" without validation testHiPPO bias (Highest Paid Person's Opinion)Every top idea needs a RAT test design
Scope creep in ideationIdeas balloon beyond what team can validateTimebox each phase strictly
Treating RICE score as final truthRICE is directional, not preciseUse RICE + Kano + strategic context together

Critical Constraints

  • DO NOT implement solutions — brainstorm and advise only
  • DO validate hypotheses before endorsing any approach
  • DO prioritize long-term maintainability over short-term convenience
  • DO consider both technical excellence and business pragmatism
  • DO produce a scored, ranked shortlist — never just a flat idea list
  • DO always design the cheapest validation test — RAT before full spec

Workflow Integration

After brainstorm session concludes, use AskUserQuestion to present next steps:

Next StepWhenSkill/Workflow
/ideaCapture top idea as backlog artifactidea skill
/refineTurn top idea into actionable PBI with ACrefine skill
/web-researchNeed deeper market/competitor research firstweb-research skill
/planProblem is clear, solution is validated, ready to implementplan skill
/design-specUI-heavy idea, need wireframes before specdesign-spec skill
/domain-analysisIdea touches domain entities, need model firstdomain-analysis skill
Continue brainstormingMore scenarios to exploreStay in this session

Closing Reminders

  • MANDATORY IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • MANDATORY IMPORTANT MUST ATTENTION detect scenario type FIRST — different scenarios use different technique sequences
  • MANDATORY IMPORTANT MUST ATTENTION separate diverge (generate) and converge (evaluate) — NEVER mix them
  • MANDATORY IMPORTANT MUST ATTENTION write a hypothesis card for every top-3 recommendation
  • MANDATORY IMPORTANT MUST ATTENTION design cheapest validation test before recommending full implementation
  • MANDATORY IMPORTANT MUST ATTENTION cite evidence for every claim — confidence >80% to recommend
  • MANDATORY IMPORTANT MUST ATTENTION use AskUserQuestion for all user decisions — never auto-decide
  • MANDATORY IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

[IMPORTANT] Analyze how big the task is and break it into many small todo tasks systematically before starting — this is very important.

Prompt-Enhance Closing Anchors

  • IMPORTANT MUST ATTENTION follow declared step order for this skill; NEVER skip, reorder, or merge steps without explicit user approval
  • IMPORTANT MUST ATTENTION for every step/sub-skill call: set in_progress before execution, set completed after execution
  • IMPORTANT MUST ATTENTION every skipped step MUST include explicit reason; every completed step MUST include concise evidence
  • IMPORTANT MUST ATTENTION if Task tools unavailable, maintain an equivalent step-by-step plan tracker with synchronized statuses

平台分布

Codex

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Cursor

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Gemini CLI

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