Technical Decision Analysis

Instructions

When you invoke this skill, I will help you make evidence-based technical decisions by:

1. Understanding Context: What needs to be decided and why it matters
2. Defining Criteria: Establish evaluation framework based on decision type
3. Researching Options: Gather facts, benchmarks, and real-world usage
4. Scoring & Comparing: Create weighted comparison matrix
5. Generating Recommendation: Provide clear choice with rationale and tradeoffs
6. Creating ADR: Draft Architecture Decision Record for documentation

Decision Types

Technology Selection (e.g., database, framework, library):

• Maturity/stability, Performance, Developer experience
• Documentation/community, Future-proofing, Migration path

Architecture Decision (e.g., sync strategy, API design):

• Complexity, Maintainability, Scalability
• User experience, Cost implications

Implementation Approach (e.g., how to build feature):

• Time to implement, Code quality, Testability, Flexibility

Output Format

I will provide:

• Structured analysis of each option (pros, cons, tradeoffs, risks)
• Comparison matrix with weighted scores
• Clear recommendation with rationale
• ADR draft ready to save
• Implementation notes and references

Best Practices

• Evidence-based: Backed by research and data
• Context-aware: Consider your project constraints
• Explicit about tradeoffs: No option is perfect
• Reversibility-aware: Note if/how decision can change
• Validated: Include how to verify correctness

Usage

Simply describe your decision:

• "Should I use SwiftData or CoreData for persistence?"
• "Evaluate REST vs GraphQL for our API"
• "Compare authentication approaches: JWT vs sessions"

I'll research options, analyze tradeoffs, and provide a structured recommendation.