discover-solution-space

name	discover-solution-space
description	Use when research phase is complete and you need to explore implementation

Discover Solution Space

Deeply explore the solution space to find the optimal approach before committing to a plan.

Position in Workflow

Step 2 of development workflow:

1. /research - Understand problem, explore implementation
2. /discover_solution_space - Explore solutions (THIS)
3. Plan Mode - Create implementation plan
4. Code, review, ship

Core Principle

Comprehensive exploration. High-quality decisions.

You have a bias toward finishing quickly. Resist it. The cost of choosing a suboptimal solution compounds over time. Rushed decisions degrade codebases.

Spend significant time on:

• Understanding the codebase architecture
• Generating multiple options
• Analyzing trade-offs thoroughly

Quality over speed. This is the moment to think hard.

Input

Default: Use research findings from the current conversation.

If argument provided:

• File path: Read the file for research context
• GitHub issue: Fetch with gh issue view $ARG --comments

Workflow

1. Gather Context

From research: Understand the problem, requirements, and constraints.

From codebase: Invest significant time exploring:

• Existing architecture and patterns
• Related implementations (how similar problems were solved)
• Dependencies and integration points
• Code conventions and style
• Test patterns

Do not rush this. Thorough codebase understanding prevents solutions that fight the existing architecture.

2. Ask Clarifying Questions

Before exploring solutions, ask about anything that improves decision quality:

• Business goals and priorities
• How the feature will be used
• Performance requirements
• Future extensibility needs
• Constraints (timeline, compatibility, etc.)
• Strategic direction

Do not assume. Bad assumptions lead to suboptimal solutions.

3. Deep Exploration

Generate multiple solutions across these dimensions:

Dimension	Examples
Architectural approach	Event-driven vs request-response, monolith vs service
Implementation strategy	Extend existing class vs new module, refactor vs add
Library/tool choice	Redis vs in-memory, REST vs GraphQL
Feature design	Wizard flow vs single form, eager vs lazy loading

Generate at least 3-5 distinct approaches before evaluating. Don't anchor on the first idea.

4. First Principles Check

For each solution, challenge assumptions:

• Do we need this? Is the feature/change actually necessary?
• Are requirements correct? Should we push back on any constraints?
• Are existing patterns optimal? Or should we challenge/improve them?
• What's the simplest solution? Complexity should be justified.
• What would we regret? In 6 months, what would we wish we'd done differently?

5. Analyze Trade-offs

For each viable solution, evaluate:

• Pros: Benefits, strengths, what it enables
• Cons: Drawbacks, risks, what it complicates
• Codebase fit: How well it aligns with existing architecture
• Effort: Relative complexity (low/medium/high)
• Reversibility: How hard to change course later

6. Present and Discuss

Present ranked options. Engage with user feedback until a solution is chosen.

Output Format

## Solution Space Analysis

### Context Summary
[Brief restatement of problem and key constraints from research]

### Clarifying Questions
[Questions about strategy, usage, or requirements - if any]

---

### Options

#### Option 1: [Name] - Recommended
[Description]

**Pros:**
- ...

**Cons:**
- ...

**Codebase fit:** [How it aligns with existing patterns]
**Effort:** [Low/Medium/High]
**Reversibility:** [Easy/Moderate/Hard to change later]

#### Option 2: [Name]
[Same structure]

#### Option 3: [Name]
[Same structure]

---

### Recommendation
[Why Option 1 is recommended, and under what conditions you'd choose differently]

### Open Questions
[Anything that could change the recommendation]

### Next Step
Ready to plan implementation. Enter Plan Mode or run `/plan`

Explicit Depth Instructions

Spend significant time on this task.

Read more files than feels necessary. Generate more options than feels necessary. Analyze trade-offs more thoroughly than feels necessary.

This is not the place to be efficient. This is the place to be thorough.

Common Mistakes

Mistake	Fix
Anchoring on first idea	Generate 3-5 options BEFORE evaluating any
Shallow codebase exploration	Read related files, understand patterns first
Assuming requirements	Ask clarifying questions early
Rushing to recommendation	Spend time on trade-off analysis
Not challenging assumptions	Apply first principles check to every option
Fighting the codebase	Ensure solutions fit existing architecture
Skipping "do we need this?"	Always question if the change is necessary

What NOT to Do

• Do NOT rush through exploration
• Do NOT present only one option
• Do NOT skip the first principles check
• Do NOT ignore existing codebase patterns
• Do NOT make assumptions without asking
• Do NOT proceed to planning until user chooses a solution