tech-stack-evaluator

---
name: tech-stack-evaluator
description: Use when comparing frameworks, evaluating technology stacks, calculating TCO, assessing migration paths, or analyzing ecosystem viability with weighted scoring and data-driven recommendations.
category: Engineering
version: 1.0.0
tools: []
---

# Technology Stack Evaluator

Evaluate and compare technologies, frameworks, and cloud providers with data-driven analysis, TCO calculations, and ecosystem health scoring.

## Capabilities

| Capability | Description |
|------------|-------------|
| Technology Comparison | Compare frameworks/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, 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
**YAML** — Structured input for automation
**JSON** — Programmatic integration

## Analysis Types

| Type | Length | Output |
|------|--------|--------|
| Quick Comparison | 200–300 tokens | Weighted scores, top 3 decision factors, confidence |
| Standard Analysis | 500–800 tokens | Comparison matrix, TCO overview, security summary |
| Full Report | 1200–1500 tokens | All metrics, migration analysis, detailed recommendations |

## Scripts

| Script | Purpose |
|--------|----------|
| `stack_comparator.py` | Compare technologies with weighted criteria |
| `tco_calculator.py` | Calculate total cost of ownership over multi-year projections |
| `ecosystem_analyzer.py` | Analyze ecosystem health from GitHub, npm, and community metrics |
| `security_assessor.py` | Evaluate security posture and compliance readiness |
| `migration_analyzer.py` | Estimate migration complexity, effort, and risks |

## Prioritization Frameworks

- `cost_of_delay`: weighted by business impact
- `wsjf`: weighted shortest job first (value, urgency, complexity, risk)
- `rice`: reach, impact, confidence, effort

## 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)