本文へ移動
cccskills
無料GitHub で公開

nw-brainstorming

Structured divergent thinking techniques — HMW framing, SCAMPER, Crazy 8s mechanics, and option diversity guarantees. Enforces strict separation of generation and evaluation phases.

インストール方法を見る

含まれるファイル(1)

  • SKILL.md5.3 KB

SKILL.md(原文)

インストールする前に、エージェントに与えられる指示の中身を確認できます。

Structured Brainstorming

The Separation Principle — Foundational Rule

Generation and evaluation CANNOT happen simultaneously. Osborn (1953): "You cannot get hot and cold water from the same faucet at the same time — you only get tepid water."

Consequence for the agent: All options must be generated before any option is scored. Never filter or rank during generation. Self-censorship during generation degrades both the quality of ideas and the quality of evaluation.


Phase 1: HMW Framing — Set Up the Ideation Space

Before generating any options, reframe the problem as a "How Might We" question.

Rules for valid HMW questions:

  • No embedded solutions: "How might we make onboarding faster?" ✓ vs "How might we add tooltips?" ✗
  • Outcome-oriented, not feature-oriented
  • Broad enough for genuinely different approaches
  • Positive framing (not "How might we avoid X?")

Example transformation:

  • Feature request: "Add a dashboard to show workflow status"
  • Bad HMW: "How might we build a better dashboard?"
  • Good HMW: "How might we give teams confidence that their workflow is progressing correctly?"

The good HMW opens the solution space: the answer isn't necessarily a dashboard.


Phase 2: SCAMPER — 7 Structurally Different Lenses

Apply each SCAMPER lens to the validated job to generate one option per letter. This guarantees structural diversity — each letter produces a categorically different type of option.

LetterLensQuestionWhat it produces
SSubstituteWhat if the core mechanism were replaced entirely?Alternative technology/approach
CCombineWhat if this job were merged with an adjacent job?Integrated solution
AAdaptWhat works well in a different domain? Could we borrow it?Cross-domain transfer
MModify/MagnifyWhat if the most important dimension were amplified?Focused excellence
PPut to other useWho else has this job? Could the solution serve them too?Market extension
EEliminateWhat if we removed the most complex part?Radical simplification
RReverseWhat if the workflow ran backwards? User and system switched roles?Inversion

Required output: At minimum, one option per SCAMPER letter. Name each option clearly. Do not evaluate during generation.


Phase 3: Crazy 8s Supplement — Volume and Self-Censorship Removal

After SCAMPER, generate 2-4 additional options by imagining you have only 1 minute per idea. The time pressure mechanic prevents evaluation creep.

Constraint: Each additional option must differ structurally from all SCAMPER options. Not a variation — a different type of approach.


Phase 4: Option Curation — Converge to 6

Before handing off to taste evaluation:

  1. List all generated options (7+ from SCAMPER + supplements)
  2. Remove exact duplicates only — not similar ones, exact
  3. Group options that are genuine variations of the same approach → keep the strongest representative
  4. Target: 6 options for evaluation (evidence-backed sweet spot: enough diversity, evaluable without overload)

Diversity test — each of the 6 options should answer yes to:

  • Different mechanism? (not just variation in degree)
  • Different assumption about user behavior?
  • Different cost/effort profile?

If two options share all three, they are variations — merge them.


Option Format

Each option in options-raw.md must follow:

### Option N: [Name]

**Core idea**: One sentence — what would a user actually experience?
**Key mechanism**: What makes this work?
**Key assumption**: What must be true for this to succeed?
**SCAMPER origin**: Which lens generated this? (or "Crazy 8s supplement")
**Closest competitor**: What existing product does this most?

Anti-Patterns to Avoid

Anti-patternWhy it failsCorrection
Generating one good idea and elaborating itConfirmation bias — narrows too earlyApply all SCAMPER letters before stopping
"Improved version of the existing approach"Not divergent — variation, not optionApply E (Eliminate) or R (Reverse)
Filtering during generation ("that won't work")Destroys divergent thinkingGenerate everything, filter in taste phase
Options that share the same core mechanismFalse diversityApply diversity test before curating
Skipping HMW framingSolution space collapses prematurelyHMW must precede any generation

DIVERGE Output for Brainstorming Phase

Produce docs/feature/{feature-id}/diverge/options-raw.md with:

  1. HMW question — the validated framing
  2. SCAMPER options — one per letter, named and described
  3. Crazy 8s supplements — 2-4 additional structurally distinct options
  4. Curated 6 — with diversity test results
  5. Eliminated options — brief note on why merged/removed

Gate: 6 curated options, each passing the 3-point diversity test, before taste evaluation begins.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

同じリポジトリのスキル

概要と使いどころ

Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

Review dimensions for acceptance test quality - happy path bias, GWT compliance, business language purity, coverage completeness, walking skeleton user-centricity, priority validation, observable behavior assertions, traceability coverage, and walking skeleton boundary proof

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

Detailed 5-phase workflow for creating agents - from requirements analysis through validation and iterative refinement

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

5-layer testing approach for agent validation including adversarial testing, security validation, and prompt injection resistance

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

Architectural style selection decision matrices, trade-off analysis, structural enforcement rules, and combination patterns. Load when choosing or evaluating architecture styles.

日本語の概要は準備中です。原文の説明を表示しています。

nWave-ai/nWave6162026年9月16日 更新

nWave-ai のスキルをすべて見る

このスキルの問題を報告する