tech-stack-evaluator

📁 aleister1102/skills 📅 10 days ago
0
总安装量
8
周安装量
安装命令
npx skills add https://github.com/aleister1102/skills --skill tech-stack-evaluator

Agent 安装分布

trae 8
opencode 8
cursor 8
kiro-cli 8
codex 8
github-copilot 8

Skill 文档

Technology Stack Evaluator

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

When to Use

  • You need to compare frameworks, cloud providers, or technology stacks across cost, ecosystem, security, or migration criteria.
  • You are preparing a migration recommendation or technology selection spreadsheet with TCO and risk factors.
  • The decision requires structured scoring (ecosystem health, security, performance).

When NOT to Use

  • The request is for a quick coding question or implementation detail unrelated to evaluating tech stacks.
  • The situation involves a single technology with no comparison or migration decision.
  • You only need a high-level opinion without structured analysis or evidence.

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)