Analyzing Options
When to use
- Facing multiple viable approaches to a task or problem
- Making strategic decisions or architecture choices
- Needing structured comparison with effort estimates
- Evaluating trade-offs between competing solutions
Skip when
- There's an obvious single approach
- The decision is already made
- The task is trivial and doesn't warrant analysis
Related
Similar: ring:writing-plans — use writing-plans when the approach is decided and you need phased execution
For the given task or problem, provide a structured analysis following this format:
Instructions
1. Problem Understanding
- Clearly restate the problem/goal
- Identify key requirements and constraints
- List any assumptions being made
2. Approach Options
For each viable approach (aim for 3-5 options):
Option [N]: [Descriptive Name]
Overview: Brief description of the approach
Benefits:
- List 3-5 key advantages
- Focus on technical and business value
Trade-offs:
- List 2-4 potential drawbacks or limitations
- Be honest about complexity or risks
Implementation Details:
- High-level steps required
- Key technologies or patterns involved
- Integration points or dependencies
Effort Estimate:
- Complexity: Low/Medium/High
- Time: Rough estimate (hours/days/weeks)
- Team Size: Solo developer / Small team / Large team
- Maintenance: Ongoing effort required
Best For: Describe scenarios where this approach excels
3. Recommendation Matrix
Create a comparison table:
| Approach | Complexity | Time | Risk | Scalability | Maintainability | Overall Score |
|---|---|---|---|---|---|---|
| Option 1 | Low | 2d | Low | Medium | High | 7/10 |
| Option 2 | High | 2w | Med | High | Medium | 6/10 |
| etc... |
4. Recommended Approach
- State your primary recommendation with rationale
- Suggest a fallback option if the primary fails
- Highlight any critical decision points
5. Next Steps
- List immediate actions for the chosen approach
- Identify what additional information might be needed
- Suggest proof-of-concept or validation steps
Guidelines
- Be objective and data-driven in analysis
- Consider both short-term and long-term implications
- Include non-technical factors (team skills, deadlines, budget)
- Provide actionable insights, not just theoretical comparisons
- When possible, reference similar successful implementations