Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis.
Facilitates technical decisions by building weighted comparison matrices and analyzing trade-offs between options.
/plugin marketplace add jmagly/aiwg/plugin install sdlc@aiwgThis skill inherits all available tools. When active, it can use any tool Claude has access to.
Facilitate data-driven technical decisions using embedded decision matrices and trade-off analysis.
This skill facilitates structured decision-making for technical and architectural choices by:
When triggered, this skill:
Identifies decision context:
Gathers alternatives:
Defines evaluation criteria:
Builds decision matrix:
Analyzes trade-offs:
Generates recommendation:
architectural:
examples:
- database_selection
- api_design_pattern
- microservices_vs_monolith
- authentication_approach
- caching_strategy
typical_criteria:
- scalability
- maintainability
- performance
- security
- team_expertise
- cost
- time_to_implement
technical:
examples:
- library_selection
- framework_choice
- language_selection
- testing_approach
- ci_cd_tooling
typical_criteria:
- maturity
- community_support
- documentation
- learning_curve
- integration_ease
- license_compatibility
process:
examples:
- branching_strategy
- release_cadence
- review_process
- documentation_approach
- communication_tools
typical_criteria:
- team_fit
- efficiency
- quality_impact
- adoption_effort
- tooling_support
# Decision Matrix: [Decision Title]
**Decision ID**: DEC-2025-001
**Date**: 2025-12-08
**Status**: Under Evaluation
**Decision Owner**: [Name]
**Stakeholders**: [List]
## Context
[Description of the problem or opportunity requiring a decision]
## Constraints
- [Constraint 1]
- [Constraint 2]
- [Constraint 3]
## Options Under Consideration
### Option A: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
### Option B: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
### Option C: [Name]
- **Description**: [Brief description]
- **Pros**: [Key advantages]
- **Cons**: [Key disadvantages]
- **Risk Level**: Low/Medium/High
## Evaluation Criteria
| Criterion | Weight | Description |
|-----------|--------|-------------|
| Scalability | 25% | Ability to handle growth |
| Maintainability | 20% | Ease of ongoing maintenance |
| Performance | 20% | Speed and efficiency |
| Security | 15% | Security posture |
| Team Expertise | 10% | Team familiarity |
| Cost | 10% | Total cost of ownership |
## Scoring Rubric
| Score | Meaning |
|-------|---------|
| 5 | Excellent - Exceeds requirements |
| 4 | Good - Meets all requirements |
| 3 | Adequate - Meets most requirements |
| 2 | Poor - Meets some requirements |
| 1 | Unacceptable - Does not meet requirements |
## Decision Matrix
| Criterion | Weight | Option A | Option B | Option C |
|-----------|--------|----------|----------|----------|
| Scalability | 25% | 4 (1.00) | 5 (1.25) | 3 (0.75) |
| Maintainability | 20% | 5 (1.00) | 3 (0.60) | 4 (0.80) |
| Performance | 20% | 4 (0.80) | 5 (1.00) | 3 (0.60) |
| Security | 15% | 4 (0.60) | 4 (0.60) | 5 (0.75) |
| Team Expertise | 10% | 5 (0.50) | 2 (0.20) | 4 (0.40) |
| Cost | 10% | 3 (0.30) | 4 (0.40) | 3 (0.30) |
| **Total** | 100% | **4.20** | **4.05** | **3.60** |
## Trade-off Analysis
### Option A vs Option B
- **A wins on**: Maintainability (+2), Team Expertise (+3)
- **B wins on**: Scalability (+1), Performance (+1), Cost (+1)
- **Key trade-off**: Immediate productivity vs long-term scale
### Option A vs Option C
- **A wins on**: Scalability (+1), Maintainability (+1), Performance (+1)
- **C wins on**: Security (+1)
- **Key trade-off**: Overall capability vs security focus
## Risk Assessment
| Option | Key Risks | Mitigation |
|--------|-----------|------------|
| A | May hit scale limits in 2 years | Plan migration path |
| B | Learning curve may slow initial dev | Training budget |
| C | Performance concerns at scale | Performance testing |
## Recommendation
**Recommended Option**: Option A
**Rationale**:
1. Highest weighted score (4.20)
2. Strong team expertise reduces implementation risk
3. Best maintainability for long-term ownership
4. Acceptable scalability with documented migration path
**Dissenting Views**:
- [Stakeholder X] prefers Option B for scalability headroom
- Noted for future re-evaluation if growth exceeds projections
## Decision Record
**Decision**: Adopt Option A
**Decided By**: [Decision Owner]
**Date**: 2025-12-08
**Review Date**: 2026-06-08 (6 months)
## Action Items
- [ ] Document implementation approach
- [ ] Create ADR
- [ ] Communicate decision to team
- [ ] Set up review milestone
When a decision is finalized, generate an ADR:
# ADR-XXX: [Decision Title]
## Status
Accepted
## Context
[Background and problem statement]
## Decision
We will use [Option A] because [rationale summary].
## Consequences
### Positive
- [Benefit 1]
- [Benefit 2]
### Negative
- [Trade-off 1]
- [Trade-off 2]
### Neutral
- [Observation 1]
## Alternatives Considered
### Option B: [Name]
Rejected because: [reason]
### Option C: [Name]
Rejected because: [reason]
## References
- Decision Matrix: .aiwg/decisions/DEC-2025-001.md
- Related ADRs: ADR-XXX
User: "Help me decide between PostgreSQL and MongoDB for our user service"
Skill executes:
1. Identify decision: Database selection for user service
2. Gather alternatives: PostgreSQL, MongoDB, (suggests DynamoDB)
3. Define criteria based on user service requirements
4. Build comparison matrix
5. Analyze trade-offs
6. Generate recommendation
Output:
"Decision Analysis: User Service Database
Options Evaluated:
1. PostgreSQL (Score: 4.35)
2. MongoDB (Score: 3.90)
3. DynamoDB (Score: 3.65)
Recommendation: PostgreSQL
Key Factors:
- Strong ACID compliance for user data
- Team has SQL expertise
- Proven scalability with proper indexing
- Better for relational user data patterns
Trade-off Accepted:
- Less flexibility for schema changes
- Mitigation: Use JSONB for extensible fields
Decision Matrix: .aiwg/decisions/database-selection.md
ADR: .aiwg/architecture/adr-015-user-db.md"
User: "Compare options for API gateway"
Skill generates:
- Kong vs AWS API Gateway vs Nginx
- Weighted criteria comparison
- Quick recommendation
Output:
"API Gateway Comparison:
| Criteria | Kong | AWS GW | Nginx |
|----------|------|--------|-------|
| Features | 5 | 4 | 3 |
| Cost | 3 | 4 | 5 |
| Ops Effort | 3 | 5 | 2 |
| Flexibility | 5 | 3 | 5 |
| Weighted | 4.1 | 4.0 | 3.8 |
Recommendation: Kong (slight edge)
Key: Best feature set with acceptable ops overhead
Want full analysis? Say 'full decision matrix'"
User: "What are the trade-offs between microservices and monolith?"
Skill analyzes:
- Key dimensions
- Specific trade-offs
- When each is preferred
Output:
"Microservices vs Monolith Trade-offs:
Microservices Wins:
✓ Independent scaling
✓ Technology flexibility
✓ Team autonomy
✓ Fault isolation
Monolith Wins:
✓ Simpler operations
✓ Easier debugging
✓ Lower latency (no network)
✓ Faster initial development
Decision Factors:
- Team size: <10 devs → monolith
- Scale needs: 10x+ growth → microservices
- Domain complexity: Clear boundaries → microservices
Want me to build a decision matrix for your specific context?"
This skill uses:
project-awareness: Context for decision constraintsartifact-metadata: Track decision lifecycletemplate-engine: Load ADR templatesagents:
research:
agent: technical-researcher
focus: Gather data on alternatives
architecture:
agent: architecture-designer
focus: Architectural implications
security:
agent: security-architect
focus: Security trade-offs
condition: security_relevant == true
cost:
agent: business-process-analyst
focus: Cost and resource implications
criteria_sets:
architectural:
- {name: scalability, weight: 20, default: true}
- {name: maintainability, weight: 20, default: true}
- {name: performance, weight: 15, default: true}
- {name: security, weight: 15, default: true}
- {name: team_expertise, weight: 10, default: true}
- {name: cost, weight: 10, default: true}
- {name: time_to_implement, weight: 10, default: true}
library_selection:
- {name: maturity, weight: 20}
- {name: community_support, weight: 20}
- {name: documentation, weight: 15}
- {name: learning_curve, weight: 15}
- {name: license, weight: 15}
- {name: performance, weight: 15}
thresholds:
clear_winner: 0.5 # Score gap for clear recommendation
close_call: 0.2 # Gap requiring stakeholder input
tie: 0.1 # Effectively equal, other factors decide
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