/swing-options

name: swing-options
description: Generate probability-weighted alternative options that challenge default thinking. Forces unconventional alternatives and exposes hidden assumptions behind the "obvious" choice. For decision-point analysis, NOT full design exploration. Triggers on "대안", "alternatives", "옵션 뽑아", "options", "어떤 방법이", "아이디어", "다른 방법", "선택지".
argument-hint: "[decision or question to explore]"
allowed-tools: Read, Grep, Glob, Bash, WebSearch, WebFetch, Agent

Creativity Sampler

Probability-weighted option generator that fights typicality bias and surfaces unconventional alternatives. The core value is **exposing hidden assumptions** behind the "obvious" choice.

> Addresses the cognitive failure of **Anchoring Bias** — AI defaults to the first or most obvious solution without exploring the full decision space, causing users to miss superior alternatives they never considered.

Rules (Absolute)

1. **Generate exactly 5 options by default.** If the decision space has fewer than 4 genuinely distinct approaches, generate all distinct approaches plus at least 1 unconventional reframing of the problem itself. Never pad with trivially different variations of the same idea. If the user specifies a different count, respect it. 2. **At least 1 option must be unconventional** (Unconventional or Wild card zone). This is the whole point — surface ideas that would normally be suppressed. 3. **Assign relative probability zones** that indicate typicality, not quality. Base estimates on observable signals where possible: community adoption, tutorial prevalence, StackOverflow frequency, conference talk frequency. When precise probabilities cannot be grounded, use zone labels instead:

• **Conventional** (p > 40%) — the "obvious" choice most would pick
• **Mainstream** (p 20-40%) — commonly considered alternative
• **Uncommon** (p 10-20%) — valid but often overlooked
• **Unconventional** (p 5-10%) — challenges assumptions
• **Wild card** (p < 5%) — radical rethink

At least one option must come from the bottom two zones. 4. **Lower probability = more creative**, not worse. Explicitly frame low-p options as valuable exploration. 5. **No default recommendation.** Present all options as viable. Let the user decide after seeing trade-offs. 6. **Trade-off analysis is mandatory.** Each option must have concrete pros/cons, not vague descriptions. 7. **Ambiguous inputs require clarification.** If the decision question is too vague to determine what "unconventional" means, ask one clarifying question about constraints before generating options. Constraints determine the boundary between conventional and unconventional.

Process

Step 1: Check Input Clarity

Before generating options, verify:

• Is the decision clearly stated?
• Are enough constraints known to distinguish conventional from unconventional?

If not, ask **one** targeted question. Example: "What's your biggest constraint — timeline, budget, or team expertise? This determines which options count as unconventional for your situation."

Step 2: Frame the Decision Space

Identify:

• What is being decided? (technology, architecture, approach, design, strategy)
• What are the constraints? (time, budget, team skill, existing stack)
• What would the "obvious" answer be? (this is what we want to challenge)

Step 3: Generate Options (Distribution-First)

Sample across the full probability distribution, NOT just the top-1 most likely answer.

Probability zones (use zone labels when precise % cannot be grounded):
  Conventional  (p > 40%)  — the "obvious" choice most would pick
  Mainstream    (p 20-40%) — commonly considered alternative
  Uncommon      (p 10-20%) — valid but often overlooked
  Unconventional (p 5-10%) — challenges assumptions
  Wild card     (p < 5%)   — radical rethink, paradigm shift

Force at least one option from each of the bottom two zones.

Step 4: Analyze Each Option

For every option, provide: 1. **What it is** (1 sentence) 2. **Why it might be the best choice** (strongest argument FOR) 3. **Why it might fail** (strongest argument AGAINST) 4. **Best suited when...** (specific scenario where this option wins) 5. **Estimated effort** relative to other options (Low / Medium / High)

Step 5: Surface Hidden Assumptions

After presenting all options, explicitly state:

• "The conventional choice assumes [X]. If that assumption is wrong, consider options [Y, Z]."
• Identify which constraints, if removed, would change the ranking.

Output Format

## Decision: [The question being decided]

### Constraints
- [constraint 1]
- [constraint 2]

### Options

#### 1. [Option Name] — Conventional (p ~ XX%)
> [One-line description]

| Dimension | Assessment |
|-----------|------------|
| Best argument FOR | [concrete reason] |
| Best argument AGAINST | [concrete reason] |
| Best suited when | [specific scenario] |
| Effort | Low / Medium / High |
| Risk level | Low / Medium / High |

#### 2. [Option Name] — Mainstream (p ~ XX%)
> ...

#### 3. [Option Name] — Uncommon (p ~ XX%)
> ...

#### 4. [Option Name] — Unconventional (p ~ XX%)
> ...

#### 5. [Option Name] — Wild card (p ~ XX%)
> ...

### Hidden Assumptions
- The conventional choice (Option 1) assumes: [assumption]
- If [condition changes], reconsider: Option [N]
- Constraint "[X]" was taken as fixed — but is it really?

### Decision Matrix

| Criteria | Opt 1 | Opt 2 | Opt 3 | Opt 4 | Opt 5 |
|----------|-------|-------|-------|-------|-------|
| [user constraint 1] | Strong / Moderate / Weak | ... | ... | ... | ... |
| [user constraint 2] | Strong / Moderate / Weak | ... | ... | ... | ... |
| [user constraint 3] | Strong / Moderate / Weak | ... | ... | ... | ... |
| **Hidden criterion:** [X] | Strong / Moderate / Weak | ... | ... | ... | ... |

### Decision Matrix Rules
- Derive 3-5 criteria **directly from the user's stated constraints** (budget, timeline, team size, etc.)
- Add exactly 1 criteria the user did NOT