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claude-skills-reference/engineering-team/tech-stack-evaluator/references/metrics.md
Alireza Rezvani a10a4f2c4b fix(skill): restructure tech-stack-evaluator with Progressive Disclosure (#64) (#120) 
Restructure skill to follow Progressive Disclosure Architecture:

Structure Changes:
- Move Python scripts to scripts/ directory
- Move sample JSON files to assets/ directory
- Create references/ directory with extracted content
- Remove redundant HOW_TO_USE.md and README.md

New Reference Files:
- references/metrics.md: Detailed scoring algorithms and formulas
- references/examples.md: Concrete input/output examples
- references/workflows.md: Step-by-step evaluation workflows

SKILL.md Improvements:
- Reduced from 430 lines to ~180 lines
- Added table of contents
- Added trigger phrases in description
- Consistent imperative voice
- Points to references for details

Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-30 06:28:42 +01:00

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# Technology Evaluation Metrics
Detailed metrics and calculations used in technology stack evaluation.
---
## Table of Contents
- [Scoring and Comparison](#scoring-and-comparison)
- [Financial Calculations](#financial-calculations)
- [Ecosystem Health Metrics](#ecosystem-health-metrics)
- [Security Metrics](#security-metrics)
- [Migration Metrics](#migration-metrics)
- [Performance Benchmarks](#performance-benchmarks)
---
## Scoring and Comparison
### Technology Comparison Matrix
| Metric | Scale | Description |
|--------|-------|-------------|
| Feature Completeness | 0-100 | Coverage of required features |
| Learning Curve | Easy/Medium/Hard | Time to developer proficiency |
| Developer Experience | 0-100 | Tooling, debugging, workflow quality |
| Documentation Quality | 0-10 | Completeness, clarity, examples |
### Weighted Scoring Algorithm
The comparator uses normalized weighted scoring:
```python
# Default category weights (sum to 100%)
weights = {
"performance": 15,
"scalability": 15,
"developer_experience": 20,
"ecosystem": 15,
"learning_curve": 10,
"documentation": 10,
"community_support": 10,
"enterprise_readiness": 5
}
# Final score calculation
weighted_score = sum(category_score * weight / 100 for each category)
```
### Confidence Scoring
Confidence is calculated based on score gap between top options:
| Score Gap | Confidence Level |
|-----------|------------------|
| < 5 points | Low (40-50%) |
| 5-15 points | Medium (50-70%) |
| > 15 points | High (70-100%) |
---
## Financial Calculations
### TCO Components
**Initial Costs (One-Time)**
- Licensing fees
- Training: `team_size * hours_per_dev * hourly_rate + materials`
- Migration costs
- Setup and tooling
**Operational Costs (Annual)**
- Licensing renewals
- Hosting: `base_cost * (1 + growth_rate)^(year - 1)`
- Support contracts
- Maintenance: `team_size * hours_per_dev_monthly * hourly_rate * 12`
**Scaling Costs**
- Infrastructure: `servers * cost_per_server * 12`
- Cost per user: `total_yearly_cost / user_count`
### ROI Calculations
```
productivity_value = additional_features_per_year * avg_feature_value
net_tco = total_cost - (productivity_value * years)
roi_percentage = (benefits - costs) / costs * 100
```
### Cost Per Metric Reference
| Metric | Description |
|--------|-------------|
| Cost per user | Monthly or yearly per active user |
| Cost per API request | Average cost per 1000 requests |
| Cost per GB | Storage and transfer costs |
| Cost per compute hour | Processing time costs |
---
## Ecosystem Health Metrics
### GitHub Health Score (0-100)
| Metric | Max Points | Thresholds |
|--------|------------|------------|
| Stars | 30 | 50K+: 30, 20K+: 25, 10K+: 20, 5K+: 15, 1K+: 10 |
| Forks | 20 | 10K+: 20, 5K+: 15, 2K+: 12, 1K+: 10 |
| Contributors | 20 | 500+: 20, 200+: 15, 100+: 12, 50+: 10 |
| Commits/month | 30 | 100+: 30, 50+: 25, 25+: 20, 10+: 15 |
### npm Health Score (0-100)
| Metric | Max Points | Thresholds |
|--------|------------|------------|
| Weekly downloads | 40 | 1M+: 40, 500K+: 35, 100K+: 30, 50K+: 25, 10K+: 20 |
| Major version | 20 | v5+: 20, v3+: 15, v1+: 10 |
| Dependencies | 20 | ≤10: 20, ≤25: 15, ≤50: 10 (fewer is better) |
| Days since publish | 20 | ≤30: 20, ≤90: 15, ≤180: 10, ≤365: 5 |
### Community Health Score (0-100)
| Metric | Max Points | Thresholds |
|--------|------------|------------|
| Stack Overflow questions | 25 | 50K+: 25, 20K+: 20, 10K+: 15, 5K+: 10 |
| Job postings | 25 | 5K+: 25, 2K+: 20, 1K+: 15, 500+: 10 |
| Tutorials | 25 | 1K+: 25, 500+: 20, 200+: 15, 100+: 10 |
| Forum/Discord members | 25 | 50K+: 25, 20K+: 20, 10K+: 15, 5K+: 10 |
### Corporate Backing Score
| Backing Type | Score |
|--------------|-------|
| Major tech company (Google, Microsoft, Meta) | 100 |
| Established company (Vercel, HashiCorp) | 80 |
| Funded startup | 60 |
| Community-led (strong community) | 40 |
| Individual maintainers | 20 |
---
## Security Metrics
### Security Scoring Components
| Metric | Description |
|--------|-------------|
| CVE Count (12 months) | Known vulnerabilities in last year |
| CVE Count (3 years) | Longer-term vulnerability history |
| Severity Distribution | Critical/High/Medium/Low counts |
| Patch Frequency | Average days to patch vulnerabilities |
### Compliance Readiness Levels
| Level | Score Range | Description |
|-------|-------------|-------------|
| Ready | 90-100% | Meets compliance requirements |
| Mostly Ready | 70-89% | Minor gaps to address |
| Partial | 50-69% | Significant work needed |
| Not Ready | < 50% | Major gaps exist |
### Compliance Framework Coverage
**GDPR**
- Data privacy features
- Consent management
- Data portability
- Right to deletion
**SOC2**
- Access controls
- Encryption at rest/transit
- Audit logging
- Change management
**HIPAA**
- PHI handling
- Encryption standards
- Access controls
- Audit trails
---
## Migration Metrics
### Complexity Scoring (1-10 Scale)
| Factor | Weight | Description |
|--------|--------|-------------|
| Code Changes | 30% | Lines of code affected |
| Architecture Impact | 25% | Breaking changes, API compatibility |
| Data Migration | 25% | Schema changes, data transformation |
| Downtime Requirements | 20% | Zero-downtime possible vs planned outage |
### Effort Estimation
| Phase | Components |
|-------|------------|
| Development | Hours per component * complexity factor |
| Testing | Unit + integration + E2E hours |
| Training | Team size * learning curve hours |
| Buffer | 20-30% for unknowns |
### Risk Assessment Matrix
| Risk Category | Factors Evaluated |
|---------------|-------------------|
| Technical | API incompatibilities, performance regressions |
| Business | Downtime impact, feature parity gaps |
| Team | Learning curve, skill gaps |
---
## Performance Benchmarks
### Throughput/Latency Metrics
| Metric | Description |
|--------|-------------|
| RPS | Requests per second |
| Avg Response Time | Mean response latency (ms) |
| P95 Latency | 95th percentile response time |
| P99 Latency | 99th percentile response time |
| Concurrent Users | Maximum simultaneous connections |
### Resource Usage Metrics
| Metric | Unit |
|--------|------|
| Memory | MB/GB per instance |
| CPU | Utilization percentage |
| Storage | GB required |
| Network | Bandwidth MB/s |
### Scalability Characteristics
| Type | Description |
|------|-------------|
| Horizontal | Add more instances, efficiency factor |
| Vertical | CPU/memory limits per instance |
| Cost per Performance | Dollar per 1000 RPS |
| Scaling Inflection | Point where cost efficiency changes |
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