微信扫一扫MAGI - Consensus-Based Decision Support System
MAGI provides multi-perspective analysis for complex decisions by consulting three specialized agents in parallel.
When to Use This Skill
Automatically invoke MAGI when the user:
- Asks "should I..." or "which is better..."
- Faces trade-offs (performance vs maintainability, consistency vs availability, etc.)
- Compares multiple approaches or architectures
- Needs to choose between options with different pros/cons
- Expresses uncertainty about a technical decision
- Asks about normalization vs denormalization, microservices vs monolith, or similar architectural choices
The Three Perspectives
| Agent | Role | Focus | | ------------- | --------- | ----------------------------------------------------------------- | | MELCHIOR | Scientist | Technical accuracy, best practices, performance, scalability | | BALTHASAR | Mother | Developer experience, team health, sustainability, ethics | | CASPER | Realist | Implementation feasibility, cost, timeline, practical constraints |
How to Invoke
Use the /magi command with the decision question:
/magi Should we normalize this database table or keep it denormalized?
/magi ↑ Is this the right architectural approach?
/magi Microservices vs monolith for our scale?
Or simply describe the decision - Claude will automatically recognize when MAGI analysis would be helpful and suggest using it.
Output Format
MAGI produces a structured analysis report:
- Individual Agent Analysis: Each agent provides their perspective and verdict (APPROVE/REJECT/CONDITIONAL)
- Consensus: UNANIMOUS APPROVAL, MAJORITY APPROVAL, SPLIT DECISION, or MAJORITY REJECTION
- Key Trade-offs: Areas where perspectives differ
- Final Recommendation: Synthesized recommendation with reasoning
Best Practices
- Provide sufficient context (code, requirements, constraints) before invoking
- Use
↑to reference previous messages or code blocks - Consider all three verdicts, not just the majority
- Pay special attention to dissenting opinions - they often reveal blind spots