Options Scoring Calculator
SkillDev toolsMulti-criteria decision analysis for solution options with weighted scoring and sensitivity analysis
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Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Options Scoring Calculator skill
What this skill tells your AI
The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/domains/business/business-analysis/skills/options-scoring/SKILL.md and read by ahel’s review.
Overview
The Options Scoring Calculator skill provides specialized capabilities for multi-criteria decision analysis when evaluating solution options. This skill enables objective comparison of alternatives through weighted scoring, sensitivity analysis, and comprehensive recommendation development.
Capabilities
Weighted Evaluation Criteria Definition
- Define evaluation criteria with weights
- Validate weight allocation (sum to 100%)
- Group criteria by category
- Apply hierarchical weighting
Weighted Score Calculation
- Calculate weighted scores across options
- Normalize scores to common scale
- Handle missing data appropriately
- Generate score breakdowns
Sensitivity Analysis
- Perform sensitivity analysis on weights
- Identify critical criteria affecting outcomes
- Test robustness of rankings
- Generate sensitivity charts
Comparison Matrix Heat Maps
- Generate comparison matrices with heat maps
- Visualize strengths and weaknesses
- Highlight differentiating factors
- Create spider/radar charts
Pros/Cons Summaries
- Create structured pros/cons summaries
- Weight significance of each factor
- Generate balanced assessments
- Develop risk-adjusted views
Feasibility Score Calculation
- Calculate feasibility scores by dimension
- Assess technical feasibility
- Assess operational feasibility
- Assess economic feasibility
Recommendation Confidence Levels
- Generate recommendation confidence levels
- Factor in analysis limitations
- Consider uncertainty in inputs
- Provide confidence intervals
Usage
Define Evaluation Criteria
Define evaluation criteria for comparing these options:
[Options description]
Include criteria categories and recommended weights.
Calculate Option Scores
Calculate weighted scores for these options:
Criteria and Weights: [Criteria list with weights]
Options: [Option details with ratings]
Generate ranking and score breakdown.
Perform Sensitivity Analysis
Perform sensitivity analysis on this evaluation:
[Evaluation results]
Vary weights by +/- 20% and show impact on ranking.
Generate Recommendation
Generate a recommendation from this analysis:
[Scored options with analysis]
Include confidence level and key considerations.
Process Integration
This skill integrates with the following business analysis processes:
- solution-options-analysis.js - Core options evaluation
- business-case-development.js - Option comparison for business cases
- requirements-elicitation-workshop.js - Prioritization activities
Dependencies
- Decision analysis algorithms
- Statistical functions for sensitivity
- Visualization libraries
- Recommendation templates
Multi-Criteria Decision Analysis Reference
Weighted Scoring Matrix Template
| Criteria | Weight | Option A | Option B | Option C |
|---|---|---|---|---|
| Cost | 30% | 4 (1.2) | 3 (0.9) | 5 (1.5) |
| Quality | 25% | 5 (1.25) | 4 (1.0) | 3 (0.75) |
| Speed | 20% | 3 (0.6) | 5 (1.0) | 4 (0.8) |
| Risk | 15% | 4 (0.6) | 3 (0.45) | 4 (0.6) |
| Fit | 10% | 3 (0.3) | 4 (0.4) | 5 (0.5) |
| Total | 100% | 3.95 | 3.75 | 4.15 |
Rating Scale
| Score | Description | Guidelines |
|---|---|---|
| 5 | Excellent | Exceeds all requirements |
| 4 | Good | Meets all requirements well |
| 3 | Acceptable | Meets minimum requirements |
| 2 | Poor | Partially meets requirements |
| 1 | Unacceptable | Does not meet requirements |
Common Evaluation Criteria Categories
| Category | Example Criteria |
|---|---|
| Financial | Cost, ROI, TCO, Payback period |
| Technical | Performance, Scalability, Security |
| Operational | Ease of use, Maintenance, Support |
| Strategic | Alignment, Future-proofing, Innovation |
| Risk | Implementation risk, Vendor risk, Technology risk |
| Time | Time to implement, Time to value |
Feasibility Dimensions
| Dimension | Key Questions |
|---|---|
| Technical | Can we build/implement it? Do we have the skills? |
| Operational | Can we operate it? Does it fit our processes? |
| Economic | Can we afford it? Is the ROI acceptable? |
| Legal | Does it comply with regulations? |
| Schedule | Can we deliver it in time? |
Sensitivity Analysis Approach
- Establish base case with current weights
- Vary one criterion weight at a time (+/- 20%)
- Recalculate option scores
- Identify criteria that change the ranking
- Report "switching point" weights
Recommendation Framework
RECOMMENDATION: [Option X]
CONFIDENCE LEVEL: [High/Medium/Low]
RATIONALE:
- [Key strength 1]
- [Key strength 2]
- [Key strength 3]
KEY RISKS:
- [Risk 1 with mitigation]
- [Risk 2 with mitigation]
ALTERNATIVES CONSIDERED:
- Option Y: Not recommended because [reason]
- Option Z: Not recommended because [reason]
NEXT STEPS:
1. [Immediate action]
2. [Follow-up action]
Decision Documentation Checklist
- All options fully described
- Criteria aligned with objectives
- Weights agreed by stakeholders
- Ratings based on evidence
- Sensitivity analysis completed
- Risks identified and assessed
- Recommendation justified
- Decision authority identified
Signals
- GitHub stars
- 2k
- Forks
- 112
- Last commit
- Sep 2026
Advanced
- Item type
- skill
- Key
options-scoring- Source
- github.com/a5c-ai/babysitter