Technology Stack Evaluator is a development claude skill built by Alireza Rezvani. Best for: Engineering teams use this to make data-driven decisions when selecting frameworks, platforms, and cloud providers for new projects or migrations..

What it does
Evaluate and compare technology stacks with TCO analysis, security assessment, and ecosystem health scoring.
Category
development
Created by
Alireza Rezvani
Last updated
Claude Skilldevelopment GitHub-backed CuratedintermediateClaude Code

Technology Stack Evaluator

Evaluate and compare technology stacks with TCO analysis, security assessment, and ecosystem health scoring.

Skill instructions


name: "tech-stack-evaluator" description: Technology stack evaluation and comparison with TCO analysis, security assessment, and ecosystem health scoring. Use when comparing frameworks, evaluating technology stacks, calculating total cost of ownership, assessing migration paths, or analyzing ecosystem viability.

Technology Stack Evaluator

Evaluate and compare technologies, frameworks, and cloud providers with data-driven analysis and actionable recommendations.

Table of Contents


Capabilities

| Capability | Description | |------------|-------------| | Technology Comparison | Compare frameworks and libraries with weighted scoring | | TCO Analysis | Calculate 5-year total cost including hidden costs | | Ecosystem Health | Assess GitHub metrics, npm adoption, community strength | | Security Assessment | Evaluate vulnerabilities and compliance readiness | | Migration Analysis | Estimate effort, risks, and timeline for migrations | | Cloud Comparison | Compare AWS, Azure, GCP for specific workloads |


Quick Start

Compare Two Technologies

Compare React vs Vue for a SaaS dashboard.
Priorities: developer productivity (40%), ecosystem (30%), performance (30%).

Calculate TCO

Calculate 5-year TCO for Next.js on Vercel.
Team: 8 developers. Hosting: $2500/month. Growth: 40%/year.

Assess Migration

Evaluate migrating from Angular.js to React.
Codebase: 50,000 lines, 200 components. Team: 6 developers.

Input Formats

The evaluator accepts three input formats:

Text - Natural language queries

Compare PostgreSQL vs MongoDB for our e-commerce platform.

YAML - Structured input for automation

comparison:
  technologies: ["React", "Vue"]
  use_case: "SaaS dashboard"
  weights:
    ecosystem: 30
    performance: 25
    developer_experience: 45

JSON - Programmatic integration

{
  "technologies": ["React", "Vue"],
  "use_case": "SaaS dashboard"
}

Analysis Types

Quick Comparison (200-300 tokens)

  • Weighted scores and recommendation
  • Top 3 decision factors
  • Confidence level

Standard Analysis (500-800 tokens)

  • Comparison matrix
  • TCO overview
  • Security summary

Full Report (1200-1500 tokens)

  • All metrics and calculations
  • Migration analysis
  • Detailed recommendations

Scripts

stack_comparator.py

Compare technologies with customizable weighted criteria.

python scripts/stack_comparator.py --help

tco_calculator.py

Calculate total cost of ownership over multi-year projections.

python scripts/tco_calculator.py --input assets/sample_input_tco.json

ecosystem_analyzer.py

Analyze ecosystem health from GitHub, npm, and community metrics.

python scripts/ecosystem_analyzer.py --technology react

security_assessor.py

Evaluate security posture and compliance readiness.

python scripts/security_assessor.py --technology express --compliance soc2,gdpr

migration_analyzer.py

Estimate migration complexity, effort, and risks.

python scripts/migration_analyzer.py --from angular-1.x --to react

References

| Document | Content | |----------|---------| | references/metrics.md | Detailed scoring algorithms and calculation formulas | | references/examples.md | Input/output examples for all analysis types | | references/workflows.md | Step-by-step evaluation workflows |


Confidence Levels

| Level | Score | Interpretation | |-------|-------|----------------| | High | 80-100% | Clear winner, strong data | | Medium | 50-79% | Trade-offs present, moderate uncertainty | | Low | < 50% | Close call, limited data |


When to Use

  • Comparing frontend/backend frameworks for new projects
  • Evaluating cloud providers for specific workloads
  • Planning technology migrations with risk assessment
  • Calculating build vs. buy decisions with TCO
  • Assessing open-source library viability

When NOT to Use

  • Trivial decisions between similar tools (use team preference)
  • Mandated technology choices (decision already made)
  • Emergency production issues (use monitoring tools)

Use this skill

Most skills are portable instruction packages. Claude Code supports SKILL.md directly. Other agents can use adapted files like AGENTS.md, .cursorrules, and GEMINI.md.

Claude Code

Save SKILL.md into your Claude Skills folder, then restart Claude Code.

mkdir -p ~/.claude/skills/technology-stack-evaluator && curl -L "https://raw.githubusercontent.com/alirezarezvani/claude-skills/HEAD/engineering-team/tech-stack-evaluator/SKILL.md" -o ~/.claude/skills/technology-stack-evaluator/SKILL.md

Installs to ~/.claude/skills/technology-stack-evaluator/SKILL.md.

Use cases

Engineering teams use this to make data-driven decisions when selecting frameworks, platforms, and cloud providers for new projects or migrations.

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Stats

Installs0
GitHub Stars11.6k
Forks1507
LicenseMIT
UpdatedMar 27, 2026