claude-skills-reference/engineering-team/tech-stack-evaluator/references/metrics.md

Technology Evaluation Metrics

Detailed metrics and calculations used in technology stack evaluation.

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Table of Contents

• Scoring and Comparison
• Financial Calculations
• Ecosystem Health Metrics
• Security Metrics
• Migration Metrics
• Performance Benchmarks

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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:

# 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%)

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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

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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

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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

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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

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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