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>
This commit is contained in:
Alireza Rezvani
GitHub
@@ -1,335 +0,0 @@
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# How to Use the Technology Stack Evaluator Skill
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The Technology Stack Evaluator skill provides comprehensive evaluation and comparison of technologies, frameworks, and complete technology stacks for engineering teams.
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## Quick Start Examples
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### Example 1: Simple Technology Comparison
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**Conversational (Easiest)**:
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. Can you compare React vs Vue for building a SaaS dashboard?
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```
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**What you'll get**:
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- Executive summary with recommendation
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- Comparison matrix with scores
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- Top 3 pros and cons for each
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- Confidence level
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- Key decision factors
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---
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### Example 2: Complete Stack Evaluation
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. Can you evaluate this technology stack for a real-time collaboration platform:
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- Frontend: Next.js
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- Backend: Node.js + Express
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- Database: PostgreSQL
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- Real-time: WebSockets
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- Hosting: AWS
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Include TCO analysis and ecosystem health assessment.
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```
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**What you'll get**:
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- Complete stack evaluation
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- TCO breakdown (5-year projection)
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- Ecosystem health scores
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- Security assessment
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- Detailed recommendations
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---
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### Example 3: Migration Analysis
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. We're considering migrating from Angular.js (1.x) to React. Our codebase:
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- 75,000 lines of code
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- 300 components
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- 8-person development team
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- Must minimize downtime
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Can you assess migration complexity, effort, risks, and timeline?
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```
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**What you'll get**:
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- Migration complexity score (1-10)
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- Effort estimate (person-months and timeline)
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- Risk assessment (technical, business, team)
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- Phased migration plan
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- Success criteria
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---
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### Example 4: TCO Analysis
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. Calculate total cost of ownership for AWS vs Azure for our workload:
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- 50 EC2/VM instances (growing 25% annually)
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- 20TB database storage
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- Team: 12 developers
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- 5-year projection
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Include hidden costs like technical debt and vendor lock-in.
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```
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**What you'll get**:
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- 5-year TCO breakdown
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- Initial vs operational costs
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- Scaling cost projections
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- Cost per user metrics
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- Hidden costs (technical debt, vendor lock-in, downtime)
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- Cost optimization opportunities
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---
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### Example 5: Security & Compliance Assessment
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. Assess the security posture of our current stack:
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- Express.js (Node.js)
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- MongoDB
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- JWT authentication
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- Hosted on AWS
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We need SOC2 and GDPR compliance. What are the gaps?
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```
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**What you'll get**:
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- Security score (0-100) with grade
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- Vulnerability analysis (CVE counts by severity)
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- Compliance readiness for SOC2 and GDPR
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- Missing security features
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- Recommendations to improve security
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---
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### Example 6: Cloud Provider Comparison
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```
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Hey Claude—I just added the "tech-stack-evaluator" skill. Compare AWS vs Azure vs GCP for machine learning workloads:
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- Priorities: GPU availability (40%), Cost (30%), ML ecosystem (20%), Support (10%)
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- Need: High GPU availability for model training
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- Team: 5 ML engineers, experienced with Python
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Generate weighted decision matrix.
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```
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**What you'll get**:
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- Weighted comparison matrix
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- Scores across all criteria
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- Best performer by category
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- Overall recommendation with confidence
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- Pros/cons for each provider
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---
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## Input Formats Supported
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### 1. Conversational Text (Easiest)
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Just describe what you want in natural language:
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```
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"Compare PostgreSQL vs MongoDB for a SaaS application"
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"Evaluate security of our Express.js + JWT stack"
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"Calculate TCO for migrating to microservices"
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```
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### 2. Structured JSON
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For precise control over evaluation parameters:
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```json
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{
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"comparison": {
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"technologies": ["React", "Vue", "Svelte"],
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"use_case": "Enterprise dashboard",
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"weights": {
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"performance": 25,
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"developer_experience": 30,
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"ecosystem": 25,
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"learning_curve": 20
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}
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}
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}
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```
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### 3. YAML (Alternative Structured Format)
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```yaml
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comparison:
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technologies:
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- React
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- Vue
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use_case: SaaS dashboard
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priorities:
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- Developer productivity
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- Ecosystem maturity
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```
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### 4. URLs for Ecosystem Analysis
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```
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"Analyze ecosystem health for these technologies:
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- https://github.com/facebook/react
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- https://github.com/vuejs/vue
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- https://www.npmjs.com/package/react"
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```
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The skill automatically detects the format and parses accordingly!
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---
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## Report Sections Available
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You can request specific sections or get the full report:
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### Available Sections:
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1. **Executive Summary** (200-300 tokens) - Recommendation + top pros/cons
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2. **Comparison Matrix** - Weighted scoring across all criteria
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3. **TCO Analysis** - Complete cost breakdown (initial + operational + hidden)
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4. **Ecosystem Health** - Community size, maintenance, viability
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5. **Security Assessment** - Vulnerabilities, compliance readiness
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6. **Migration Analysis** - Complexity, effort, risks, timeline
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7. **Performance Benchmarks** - Throughput, latency, resource usage
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### Request Specific Sections:
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```
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"Compare Next.js vs Nuxt.js. Include only: ecosystem health and performance benchmarks. Skip TCO and migration analysis."
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```
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---
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## What to Provide
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### For Technology Comparison:
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- Technologies to compare (2-5 recommended)
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- Use case or application type (optional but helpful)
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- Priorities/weights (optional, uses sensible defaults)
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### For TCO Analysis:
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- Technology/platform name
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- Team size
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- Current costs (hosting, licensing, support)
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- Growth projections (user growth, scaling needs)
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- Developer productivity factors (optional)
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### For Migration Assessment:
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- Source technology (current stack)
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- Target technology (desired stack)
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- Codebase statistics (lines of code, number of components)
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- Team information (size, experience level)
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- Constraints (downtime tolerance, timeline)
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### For Security Assessment:
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- Technology stack components
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- Security features currently implemented
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- Compliance requirements (GDPR, SOC2, HIPAA, PCI-DSS)
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- Known vulnerabilities (if any)
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### For Ecosystem Analysis:
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- Technology name or GitHub/npm URL
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- Specific metrics of interest (optional)
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---
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## Output Formats
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The skill adapts output based on your environment:
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### Claude Desktop (Rich Markdown)
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- Formatted tables with visual indicators
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- Expandable sections
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- Color-coded scores (via markdown formatting)
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- Decision matrices
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### CLI/Terminal (Terminal-Friendly)
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- ASCII tables
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- Compact formatting
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- Plain text output
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- Copy-paste friendly
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The skill automatically detects your environment!
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---
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## Advanced Usage
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### Custom Weighted Criteria:
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```
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"Compare React vs Vue vs Svelte.
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Priorities (weighted):
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- Developer experience: 35%
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- Performance: 30%
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- Ecosystem: 20%
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- Learning curve: 15%"
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```
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### Multiple Analysis Types:
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```
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"Evaluate Next.js for our enterprise SaaS platform.
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Include: TCO (5-year), ecosystem health, security assessment, and performance vs Nuxt.js."
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```
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### Progressive Disclosure:
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```
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"Compare AWS vs Azure. Start with executive summary only."
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(After reviewing summary)
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"Show me the detailed TCO breakdown for AWS."
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```
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---
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## Tips for Best Results
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1. **Be Specific About Use Case**: "Real-time collaboration platform" is better than "web app"
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2. **Provide Context**: Team size, experience level, constraints help generate better recommendations
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3. **Set Clear Priorities**: If cost is more important than performance, say so with weights
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4. **Request Incremental Analysis**: Start with executive summary, then drill into specific sections
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5. **Include Constraints**: Zero-downtime requirement, budget limits, timeline pressure
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6. **Validate Assumptions**: Review the TCO assumptions and adjust if needed
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---
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## Common Questions
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**Q: How current is the data?**
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A: The skill uses current data sources when available (GitHub, npm, CVE databases). Ecosystem metrics are point-in-time snapshots.
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**Q: Can I compare more than 2 technologies?**
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A: Yes! You can compare 2-5 technologies. More than 5 becomes less actionable.
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**Q: What if I don't know the exact data for TCO analysis?**
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A: The skill uses industry-standard defaults. Just provide what you know (team size, rough costs) and it will fill in reasonable estimates.
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**Q: Can I export reports?**
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A: Yes! The skill can generate markdown reports that you can save or export.
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**Q: How do confidence scores work?**
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A: Confidence (0-100%) is based on:
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- Score gap between options (larger gap = higher confidence)
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- Data completeness
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- Clarity of requirements
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**Q: What if technologies are very close in scores?**
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A: The skill will report low confidence and highlight that it's a close call, helping you understand there's no clear winner.
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---
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## Need Help?
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If results aren't what you expected:
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1. **Clarify your use case** - Be more specific about requirements
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2. **Adjust priorities** - Set custom weights for what matters most
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3. **Provide more context** - Team skills, constraints, business goals
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4. **Request specific sections** - Focus on what's most relevant
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Example clarification:
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```
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"The comparison seemed to favor React, but we're a small team (3 devs) with no React experience. Can you re-evaluate with learning curve weighted at 40%?"
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```
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The skill will adjust the analysis based on your refined requirements!
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@@ -1,559 +0,0 @@
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# Technology Stack Evaluator - Comprehensive Tech Decision Support
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**Version**: 1.0.0
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**Author**: Claude Skills Factory
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**Category**: Engineering & Architecture
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**Last Updated**: 2025-11-05
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---
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## Overview
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The **Technology Stack Evaluator** skill provides comprehensive, data-driven evaluation and comparison of technologies, frameworks, cloud providers, and complete technology stacks. It helps engineering teams make informed decisions about technology adoption, migration, and architecture choices.
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### Key Features
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- **8 Comprehensive Evaluation Capabilities**: Technology comparison, stack evaluation, maturity analysis, TCO calculation, security assessment, migration path analysis, cloud provider comparison, and decision reporting
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- **Flexible Input Formats**: Automatic detection and parsing of text, YAML, JSON, and URLs
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- **Context-Aware Output**: Adapts to Claude Desktop (rich markdown) or CLI (terminal-friendly)
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- **Modular Analysis**: Choose which sections to run (quick comparison vs comprehensive report)
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- **Token-Efficient**: Executive summaries (200-300 tokens) with progressive disclosure for details
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- **Intelligent Recommendations**: Data-driven with confidence scores and clear decision factors
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---
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## What This Skill Does
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### 1. Technology Comparison
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Compare frameworks, languages, and tools head-to-head:
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- React vs Vue vs Svelte vs Angular
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- PostgreSQL vs MongoDB vs MySQL
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- Node.js vs Python vs Go for APIs
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- AWS vs Azure vs GCP
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**Outputs**: Weighted decision matrix, pros/cons, confidence scores
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### 2. Stack Evaluation
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Assess complete technology stacks for specific use cases:
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- Real-time collaboration platforms
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- API-heavy SaaS applications
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- Data-intensive applications
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- Enterprise systems
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**Outputs**: Stack health assessment, compatibility analysis, recommendations
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### 3. Maturity & Ecosystem Analysis
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Evaluate technology health and long-term viability:
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- **GitHub Metrics**: Stars, forks, contributors, commit frequency
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- **npm Metrics**: Downloads, version stability, dependencies
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- **Community Health**: Stack Overflow, job market, tutorials
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- **Viability Assessment**: Corporate backing, sustainability, risk scoring
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**Outputs**: Health score (0-100), viability level, risk factors, strengths
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### 4. Total Cost of Ownership (TCO)
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Calculate comprehensive 3-5 year costs:
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- **Initial**: Licensing, training, migration, setup
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- **Operational**: Hosting, support, maintenance (yearly projections)
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- **Scaling**: Per-user costs, infrastructure scaling
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- **Hidden**: Technical debt, vendor lock-in, downtime, turnover
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- **Productivity**: Time-to-market impact, ROI
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**Outputs**: Total TCO, yearly breakdown, cost drivers, optimization opportunities
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### 5. Security & Compliance
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Analyze security posture and compliance readiness:
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- **Vulnerability Analysis**: CVE counts by severity (Critical/High/Medium/Low)
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- **Security Scoring**: 0-100 with letter grade
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- **Compliance Assessment**: GDPR, SOC2, HIPAA, PCI-DSS readiness
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- **Patch Responsiveness**: Average time to patch critical vulnerabilities
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**Outputs**: Security score, compliance gaps, recommendations
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### 6. Migration Path Analysis
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Assess migration complexity and planning:
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- **Complexity Scoring**: 1-10 across 6 factors (code volume, architecture, data, APIs, dependencies, testing)
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- **Effort Estimation**: Person-months, timeline, phase breakdown
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- **Risk Assessment**: Technical, business, and team risks with mitigations
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- **Migration Strategy**: Direct, phased, or strangler pattern
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**Outputs**: Migration plan, timeline, risks, success criteria
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### 7. Cloud Provider Comparison
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Compare AWS vs Azure vs GCP for specific workloads:
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- Weighted decision criteria
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- Workload-specific optimizations
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- Cost comparisons
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- Feature parity analysis
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**Outputs**: Provider recommendation, cost comparison, feature matrix
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### 8. Decision Reports
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Generate comprehensive decision documentation:
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- Executive summaries (200-300 tokens)
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- Detailed analysis (800-1500 tokens)
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- Decision matrices with confidence levels
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- Exportable markdown reports
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**Outputs**: Multi-format reports adapted to context
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---
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## File Structure
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```
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tech-stack-evaluator/
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├── SKILL.md # Main skill definition (YAML + documentation)
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├── README.md # This file - comprehensive guide
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├── HOW_TO_USE.md # Usage examples and patterns
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│
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├── stack_comparator.py # Comparison engine with weighted scoring
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├── tco_calculator.py # Total Cost of Ownership calculations
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├── ecosystem_analyzer.py # Ecosystem health and viability assessment
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├── security_assessor.py # Security and compliance analysis
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├── migration_analyzer.py # Migration path and complexity analysis
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├── format_detector.py # Automatic input format detection
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├── report_generator.py # Context-aware report generation
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│
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├── sample_input_text.json # Conversational input example
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├── sample_input_structured.json # JSON structured input example
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├── sample_input_tco.json # TCO analysis input example
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└── expected_output_comparison.json # Sample output structure
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```
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### Python Modules (7 files)
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1. **`stack_comparator.py`** (355 lines)
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- Weighted scoring algorithm
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- Feature matrices
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- Pros/cons generation
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- Recommendation engine with confidence calculation
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2. **`tco_calculator.py`** (403 lines)
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- Initial costs (licensing, training, migration)
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- Operational costs with growth projections
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- Scaling cost analysis
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- Hidden costs (technical debt, vendor lock-in, downtime)
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- Productivity impact and ROI
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3. **`ecosystem_analyzer.py`** (419 lines)
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- GitHub health scoring (stars, forks, commits, issues)
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- npm health scoring (downloads, versions, dependencies)
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- Community health (Stack Overflow, jobs, tutorials)
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- Corporate backing assessment
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- Viability risk analysis
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4. **`security_assessor.py`** (406 lines)
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- Vulnerability scoring (CVE analysis)
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- Patch responsiveness assessment
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- Security features evaluation
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- Compliance readiness (GDPR, SOC2, HIPAA, PCI-DSS)
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- Risk level determination
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5. **`migration_analyzer.py`** (485 lines)
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- Complexity scoring (6 factors: code, architecture, data, APIs, dependencies, testing)
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- Effort estimation (person-months, timeline)
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- Risk assessment (technical, business, team)
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- Migration strategy recommendation (direct, phased, strangler)
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- Success criteria definition
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6. **`format_detector.py`** (334 lines)
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- Automatic format detection (JSON, YAML, URLs, text)
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- Multi-format parsing
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- Technology name extraction
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- Use case inference
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- Priority detection
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7. **`report_generator.py`** (372 lines)
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- Context detection (Desktop vs CLI)
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- Executive summary generation (200-300 tokens)
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- Full report generation with modular sections
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- Rich markdown (Desktop) vs ASCII tables (CLI)
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- Export to file functionality
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**Total**: ~2,774 lines of Python code
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---
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## Installation
|
||||
|
||||
### Claude Code (Project-Level)
|
||||
```bash
|
||||
# Navigate to your project
|
||||
cd /path/to/your/project
|
||||
|
||||
# Create skills directory if it doesn't exist
|
||||
mkdir -p .claude/skills
|
||||
|
||||
# Copy the skill folder
|
||||
cp -r /path/to/tech-stack-evaluator .claude/skills/
|
||||
```
|
||||
|
||||
### Claude Code (User-Level, All Projects)
|
||||
```bash
|
||||
# Create user-level skills directory
|
||||
mkdir -p ~/.claude/skills
|
||||
|
||||
# Copy the skill folder
|
||||
cp -r /path/to/tech-stack-evaluator ~/.claude/skills/
|
||||
```
|
||||
|
||||
### Claude Desktop
|
||||
1. Locate the skill ZIP file: `tech-stack-evaluator.zip`
|
||||
2. Drag and drop the ZIP into Claude Desktop
|
||||
3. The skill will be automatically loaded
|
||||
|
||||
### Claude Apps (Browser)
|
||||
Use the `skill-creator` skill to import the ZIP file, or manually copy files to your project's `.claude/skills/` directory.
|
||||
|
||||
### API Usage
|
||||
```bash
|
||||
# Upload skill via API
|
||||
curl -X POST https://api.anthropic.com/v1/skills \
|
||||
-H "Authorization: Bearer $ANTHROPIC_API_KEY" \
|
||||
-H "Content-Type: application/json" \
|
||||
-d @tech-stack-evaluator.zip
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Quick Start
|
||||
|
||||
### 1. Simple Comparison (Text Input)
|
||||
```
|
||||
"Compare React vs Vue for a SaaS dashboard"
|
||||
```
|
||||
|
||||
**Output**: Executive summary with recommendation, pros/cons, confidence score
|
||||
|
||||
### 2. TCO Analysis (Structured Input)
|
||||
```json
|
||||
{
|
||||
"tco_analysis": {
|
||||
"technology": "AWS",
|
||||
"team_size": 8,
|
||||
"timeline_years": 5,
|
||||
"operational_costs": {
|
||||
"monthly_hosting": 3000
|
||||
}
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
**Output**: 5-year TCO breakdown with cost optimization suggestions
|
||||
|
||||
### 3. Migration Assessment
|
||||
```
|
||||
"Assess migration from Angular.js to React. Codebase: 50,000 lines, 200 components, 6-person team."
|
||||
```
|
||||
|
||||
**Output**: Complexity score, effort estimate, timeline, risk assessment, migration plan
|
||||
|
||||
### 4. Security & Compliance
|
||||
```
|
||||
"Analyze security of Express.js + MongoDB stack. Need SOC2 compliance."
|
||||
```
|
||||
|
||||
**Output**: Security score, vulnerability analysis, compliance gaps, recommendations
|
||||
|
||||
---
|
||||
|
||||
## Usage Examples
|
||||
|
||||
See **[HOW_TO_USE.md](HOW_TO_USE.md)** for comprehensive examples including:
|
||||
- 6 real-world scenarios
|
||||
- All input format examples
|
||||
- Advanced usage patterns
|
||||
- Tips for best results
|
||||
- Common questions and troubleshooting
|
||||
|
||||
---
|
||||
|
||||
## Metrics and Calculations
|
||||
|
||||
### Scoring Algorithms
|
||||
|
||||
**Technology Comparison (0-100 scale)**:
|
||||
- 8 weighted criteria (performance, scalability, developer experience, ecosystem, learning curve, documentation, community, enterprise readiness)
|
||||
- User-defined weights (defaults provided)
|
||||
- Use-case specific adjustments (e.g., real-time workloads get performance bonus)
|
||||
- Confidence calculation based on score gap
|
||||
|
||||
**Ecosystem Health (0-100 scale)**:
|
||||
- GitHub: Stars, forks, contributors, commit frequency
|
||||
- npm: Weekly downloads, version stability, dependencies count
|
||||
- Community: Stack Overflow questions, job postings, tutorials, forums
|
||||
- Corporate backing: Funding, company type
|
||||
- Maintenance: Issue response time, resolution rate, release frequency
|
||||
|
||||
**Security Score (0-100 scale, A-F grade)**:
|
||||
- Vulnerability count and severity (CVE database)
|
||||
- Patch responsiveness (days to patch critical/high)
|
||||
- Security features (encryption, auth, logging, etc.)
|
||||
- Track record (years since major incident, certifications, audits)
|
||||
|
||||
**Migration Complexity (1-10 scale)**:
|
||||
- Code volume (lines of code, files, components)
|
||||
- Architecture changes (minimal to complete rewrite)
|
||||
- Data migration (database size, schema changes)
|
||||
- API compatibility (breaking changes)
|
||||
- Dependency changes (percentage to replace)
|
||||
- Testing requirements (coverage, test count)
|
||||
|
||||
### Financial Calculations
|
||||
|
||||
**TCO Components**:
|
||||
- Initial: Licensing + Training (hours × rate × team size) + Migration + Setup + Tooling
|
||||
- Operational (yearly): Licensing + Hosting (with growth) + Support + Maintenance (dev hours)
|
||||
- Scaling: User projections × cost per user, Infrastructure scaling
|
||||
- Hidden: Technical debt (15-20% of dev time) + Vendor lock-in risk + Security incidents + Downtime + Turnover
|
||||
|
||||
**ROI Calculation**:
|
||||
- Productivity value = (Additional features per year) × (Feature value)
|
||||
- Net TCO = Total TCO - Productivity value
|
||||
- Break-even analysis
|
||||
|
||||
### Compliance Assessment
|
||||
|
||||
**Standards Supported**: GDPR, SOC2, HIPAA, PCI-DSS
|
||||
|
||||
**Readiness Levels**:
|
||||
- **Ready (90-100%)**: Compliant, minor verification needed
|
||||
- **Mostly Ready (70-89%)**: Minor gaps, additional configuration
|
||||
- **Partial (50-69%)**: Significant work required
|
||||
- **Not Ready (<50%)**: Major gaps, extensive implementation
|
||||
|
||||
**Required Features per Standard**:
|
||||
- **GDPR**: Data privacy, consent management, data portability, right to deletion, audit logging
|
||||
- **SOC2**: Access controls, encryption (at rest + transit), audit logging, backup/recovery
|
||||
- **HIPAA**: PHI protection, encryption, access controls, audit logging
|
||||
- **PCI-DSS**: Payment data encryption, access controls, network security, vulnerability management
|
||||
|
||||
---
|
||||
|
||||
## Best Practices
|
||||
|
||||
### For Accurate Evaluations
|
||||
1. **Define Clear Use Case**: "Real-time collaboration platform" > "web app"
|
||||
2. **Provide Complete Context**: Team size, skills, constraints, timeline
|
||||
3. **Set Realistic Priorities**: Use weighted criteria (total = 100%)
|
||||
4. **Consider Team Skills**: Factor in learning curve and existing expertise
|
||||
5. **Think Long-Term**: Evaluate 3-5 year outlook
|
||||
|
||||
### For TCO Analysis
|
||||
1. **Include All Costs**: Don't forget training, migration, technical debt
|
||||
2. **Realistic Scaling**: Base on actual growth metrics
|
||||
3. **Developer Productivity**: Time-to-market is a critical cost factor
|
||||
4. **Hidden Costs**: Vendor lock-in, exit costs, technical debt
|
||||
5. **Document Assumptions**: Make TCO assumptions explicit
|
||||
|
||||
### For Migration Decisions
|
||||
1. **Risk Assessment First**: Identify showstoppers early
|
||||
2. **Incremental Migration**: Avoid big-bang rewrites
|
||||
3. **Prototype Critical Paths**: Test complex scenarios
|
||||
4. **Rollback Plans**: Always have fallback strategy
|
||||
5. **Baseline Metrics**: Measure current performance before migration
|
||||
|
||||
### For Security Evaluation
|
||||
1. **Recent Vulnerabilities**: Focus on last 12 months
|
||||
2. **Patch Response Time**: Fast patching > zero vulnerabilities
|
||||
3. **Validate Claims**: Vendor claims ≠ actual compliance
|
||||
4. **Supply Chain**: Evaluate security of all dependencies
|
||||
5. **Test Features**: Don't assume features work as documented
|
||||
|
||||
---
|
||||
|
||||
## Limitations
|
||||
|
||||
### Data Accuracy
|
||||
- **Ecosystem metrics**: Point-in-time snapshots (GitHub/npm data changes rapidly)
|
||||
- **TCO calculations**: Estimates based on assumptions and market rates
|
||||
- **Benchmark data**: May not reflect your specific configuration
|
||||
- **Vulnerability data**: Depends on public CVE database completeness
|
||||
|
||||
### Scope Boundaries
|
||||
- **Industry-specific requirements**: Some specialized needs not covered by standard analysis
|
||||
- **Emerging technologies**: Very new tech (<1 year) may lack sufficient data
|
||||
- **Custom/proprietary solutions**: Cannot evaluate closed-source tools without data
|
||||
- **Organizational factors**: Cannot account for politics, vendor relationships, legacy commitments
|
||||
|
||||
### When NOT to Use
|
||||
- **Trivial decisions**: Nearly-identical tools (use team preference)
|
||||
- **Mandated solutions**: Technology choice already decided
|
||||
- **Insufficient context**: Unknown requirements or priorities
|
||||
- **Real-time production**: Use for planning, not emergencies
|
||||
- **Non-technical decisions**: Business strategy, hiring, org issues
|
||||
|
||||
---
|
||||
|
||||
## Confidence Levels
|
||||
|
||||
All recommendations include confidence scores (0-100%):
|
||||
|
||||
- **High (80-100%)**: Strong data, clear winner, low risk
|
||||
- **Medium (50-79%)**: Good data, trade-offs present, moderate risk
|
||||
- **Low (<50%)**: Limited data, close call, high uncertainty
|
||||
- **Insufficient Data**: Cannot recommend without more information
|
||||
|
||||
**Confidence based on**:
|
||||
- Data completeness and recency
|
||||
- Consensus across multiple metrics
|
||||
- Clarity of use case requirements
|
||||
- Industry maturity and standards
|
||||
|
||||
---
|
||||
|
||||
## Output Examples
|
||||
|
||||
### Executive Summary (200-300 tokens)
|
||||
```markdown
|
||||
# Technology Evaluation: React vs Vue
|
||||
|
||||
## Recommendation
|
||||
**React is recommended for your SaaS dashboard project**
|
||||
*Confidence: 78%*
|
||||
|
||||
### Top Strengths
|
||||
- Larger ecosystem with 2.5× more packages available
|
||||
- Stronger corporate backing (Meta) ensures long-term viability
|
||||
- Higher job market demand (3× more job postings)
|
||||
|
||||
### Key Concerns
|
||||
- Steeper learning curve (score: 65 vs Vue's 80)
|
||||
- More complex state management patterns
|
||||
- Requires additional libraries for routing, forms
|
||||
|
||||
### Decision Factors
|
||||
- **Ecosystem**: React (score: 95)
|
||||
- **Developer Experience**: Vue (score: 88)
|
||||
- **Community Support**: React (score: 92)
|
||||
```
|
||||
|
||||
### Comparison Matrix (Desktop)
|
||||
```markdown
|
||||
| Category | Weight | React | Vue |
|
||||
|-----------------------|--------|-------|-------|
|
||||
| Performance | 15% | 85.0 | 87.0 |
|
||||
| Scalability | 15% | 90.0 | 85.0 |
|
||||
| Developer Experience | 20% | 80.0 | 88.0 |
|
||||
| Ecosystem | 15% | 95.0 | 82.0 |
|
||||
| Learning Curve | 10% | 65.0 | 80.0 |
|
||||
| Documentation | 10% | 92.0 | 90.0 |
|
||||
| Community Support | 10% | 92.0 | 85.0 |
|
||||
| Enterprise Readiness | 5% | 95.0 | 80.0 |
|
||||
| **WEIGHTED TOTAL** | 100% | 85.3 | 84.9 |
|
||||
```
|
||||
|
||||
### TCO Summary
|
||||
```markdown
|
||||
## Total Cost of Ownership: AWS (5 years)
|
||||
|
||||
**Total TCO**: $1,247,500
|
||||
**Net TCO (after productivity gains)**: $987,300
|
||||
**Average Yearly**: $249,500
|
||||
|
||||
### Initial Investment: $125,000
|
||||
- Training: $40,000 (10 devs × 40 hours × $100/hr)
|
||||
- Migration: $50,000
|
||||
- Setup & Tooling: $35,000
|
||||
|
||||
### Key Cost Drivers
|
||||
- Infrastructure/hosting ($625,000 over 5 years)
|
||||
- Developer maintenance time ($380,000)
|
||||
- Technical debt accumulation ($87,500)
|
||||
|
||||
### Optimization Opportunities
|
||||
- Improve scaling efficiency - costs growing 25% YoY
|
||||
- Address technical debt accumulation
|
||||
- Consider reserved instances for 30% hosting savings
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Version History
|
||||
|
||||
### v1.0.0 (2025-11-05)
|
||||
- Initial release
|
||||
- 8 comprehensive evaluation capabilities
|
||||
- 7 Python modules (2,774 lines)
|
||||
- Automatic format detection (text, YAML, JSON, URLs)
|
||||
- Context-aware output (Desktop vs CLI)
|
||||
- Modular reporting with progressive disclosure
|
||||
- Complete documentation with 6+ usage examples
|
||||
|
||||
---
|
||||
|
||||
## Dependencies
|
||||
|
||||
**Python Standard Library Only** - No external dependencies required:
|
||||
- `typing` - Type hints
|
||||
- `json` - JSON parsing
|
||||
- `re` - Regular expressions
|
||||
- `datetime` - Date/time operations
|
||||
- `os` - Environment detection
|
||||
- `platform` - Platform information
|
||||
|
||||
**Why no external dependencies?**
|
||||
- Ensures compatibility across all Claude environments
|
||||
- No installation or version conflicts
|
||||
- Faster loading and execution
|
||||
- Simpler deployment
|
||||
|
||||
---
|
||||
|
||||
## Support and Feedback
|
||||
|
||||
### Getting Help
|
||||
1. Review **[HOW_TO_USE.md](HOW_TO_USE.md)** for detailed examples
|
||||
2. Check sample input files for format references
|
||||
3. Start with conversational text input (easiest)
|
||||
4. Request specific sections if full report is overwhelming
|
||||
|
||||
### Improving Results
|
||||
If recommendations don't match expectations:
|
||||
- **Clarify use case**: Be more specific about requirements
|
||||
- **Adjust priorities**: Set custom weights for criteria
|
||||
- **Provide more context**: Team skills, constraints, business goals
|
||||
- **Request specific sections**: Focus on most relevant analyses
|
||||
|
||||
### Known Issues
|
||||
- Very new technologies (<6 months) may have limited ecosystem data
|
||||
- Proprietary/closed-source tools require manual data input
|
||||
- Compliance assessment is guidance, not legal certification
|
||||
|
||||
---
|
||||
|
||||
## Contributing
|
||||
|
||||
This skill is part of the Claude Skills Factory. To contribute improvements:
|
||||
1. Test changes with multiple scenarios
|
||||
2. Maintain Python standard library only (no external deps)
|
||||
3. Update documentation to match code changes
|
||||
4. Preserve token efficiency (200-300 token summaries)
|
||||
5. Validate all calculations with real-world data
|
||||
|
||||
---
|
||||
|
||||
## License
|
||||
|
||||
Part of Claude Skills Factory
|
||||
© 2025 Claude Skills Factory
|
||||
Licensed under MIT License
|
||||
|
||||
---
|
||||
|
||||
## Related Skills
|
||||
|
||||
- **prompt-factory**: Generate domain-specific prompts
|
||||
- **aws-solution-architect**: AWS-specific architecture evaluation
|
||||
- **psychology-advisor**: Decision-making psychology
|
||||
- **content-researcher**: Technology trend research
|
||||
|
||||
---
|
||||
|
||||
**Ready to evaluate your tech stack?** See [HOW_TO_USE.md](HOW_TO_USE.md) for quick start examples!
|
||||
@@ -1,429 +1,184 @@
|
||||
---
|
||||
name: tech-stack-evaluator
|
||||
description: Comprehensive technology stack evaluation and comparison tool with TCO analysis, security assessment, and intelligent recommendations for engineering teams
|
||||
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
|
||||
|
||||
A comprehensive evaluation framework for comparing technologies, frameworks, cloud providers, and complete technology stacks. Provides data-driven recommendations with TCO analysis, security assessment, ecosystem health scoring, and migration path analysis.
|
||||
Evaluate and compare technologies, frameworks, and cloud providers with data-driven analysis and actionable recommendations.
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Capabilities](#capabilities)
|
||||
- [Quick Start](#quick-start)
|
||||
- [Input Formats](#input-formats)
|
||||
- [Analysis Types](#analysis-types)
|
||||
- [Scripts](#scripts)
|
||||
- [References](#references)
|
||||
|
||||
---
|
||||
|
||||
## Capabilities
|
||||
|
||||
This skill provides eight comprehensive evaluation 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 |
|
||||
|
||||
- **Technology Comparison**: Head-to-head comparisons of frameworks, languages, and tools (React vs Vue, PostgreSQL vs MongoDB, Node.js vs Python)
|
||||
- **Stack Evaluation**: Assess complete technology stacks for specific use cases (real-time collaboration, API-heavy SaaS, data-intensive platforms)
|
||||
- **Maturity & Ecosystem Analysis**: Evaluate community health, maintenance status, long-term viability, and ecosystem strength
|
||||
- **Total Cost of Ownership (TCO)**: Calculate comprehensive costs including licensing, hosting, developer productivity, and scaling
|
||||
- **Security & Compliance**: Analyze vulnerabilities, compliance readiness (GDPR, SOC2, HIPAA), and security posture
|
||||
- **Migration Path Analysis**: Assess migration complexity, risks, timelines, and strategies from legacy to modern stacks
|
||||
- **Cloud Provider Comparison**: Compare AWS vs Azure vs GCP for specific workloads with cost and feature analysis
|
||||
- **Decision Reports**: Generate comprehensive decision matrices with pros/cons, confidence scores, and actionable recommendations
|
||||
---
|
||||
|
||||
## Input Requirements
|
||||
## Quick Start
|
||||
|
||||
### Flexible Input Formats (Automatic Detection)
|
||||
### Compare Two Technologies
|
||||
|
||||
The skill automatically detects and processes multiple input formats:
|
||||
|
||||
**Text/Conversational**:
|
||||
```
|
||||
"Compare React vs Vue for building a SaaS dashboard"
|
||||
"Evaluate technology stack for real-time collaboration platform"
|
||||
"Should we migrate from MongoDB to PostgreSQL?"
|
||||
Compare React vs Vue for a SaaS dashboard.
|
||||
Priorities: developer productivity (40%), ecosystem (30%), performance (30%).
|
||||
```
|
||||
|
||||
**Structured (YAML)**:
|
||||
### 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
|
||||
```yaml
|
||||
comparison:
|
||||
technologies:
|
||||
- name: "React"
|
||||
- name: "Vue"
|
||||
technologies: ["React", "Vue"]
|
||||
use_case: "SaaS dashboard"
|
||||
priorities:
|
||||
- "Developer productivity"
|
||||
- "Ecosystem maturity"
|
||||
- "Performance"
|
||||
weights:
|
||||
ecosystem: 30
|
||||
performance: 25
|
||||
developer_experience: 45
|
||||
```
|
||||
|
||||
**Structured (JSON)**:
|
||||
**JSON** - Programmatic integration
|
||||
```json
|
||||
{
|
||||
"comparison": {
|
||||
"technologies": ["React", "Vue"],
|
||||
"use_case": "SaaS dashboard",
|
||||
"priorities": ["Developer productivity", "Ecosystem maturity"]
|
||||
}
|
||||
"technologies": ["React", "Vue"],
|
||||
"use_case": "SaaS dashboard"
|
||||
}
|
||||
```
|
||||
|
||||
**URLs for Ecosystem Analysis**:
|
||||
- GitHub repository URLs (for health scoring)
|
||||
- npm package URLs (for download statistics)
|
||||
- Technology documentation URLs (for feature extraction)
|
||||
---
|
||||
|
||||
### Analysis Scope Selection
|
||||
## Analysis Types
|
||||
|
||||
Users can select which analyses to run:
|
||||
- **Quick Comparison**: Basic scoring and comparison (200-300 tokens)
|
||||
- **Standard Analysis**: Scoring + TCO + Security (500-800 tokens)
|
||||
- **Comprehensive Report**: All analyses including migration paths (1200-1500 tokens)
|
||||
- **Custom**: User selects specific sections (modular)
|
||||
### Quick Comparison (200-300 tokens)
|
||||
- Weighted scores and recommendation
|
||||
- Top 3 decision factors
|
||||
- Confidence level
|
||||
|
||||
## Output Formats
|
||||
### Standard Analysis (500-800 tokens)
|
||||
- Comparison matrix
|
||||
- TCO overview
|
||||
- Security summary
|
||||
|
||||
### Context-Aware Output
|
||||
### Full Report (1200-1500 tokens)
|
||||
- All metrics and calculations
|
||||
- Migration analysis
|
||||
- Detailed recommendations
|
||||
|
||||
The skill automatically adapts output based on environment:
|
||||
|
||||
**Claude Desktop (Rich Markdown)**:
|
||||
- Formatted tables with color indicators
|
||||
- Expandable sections for detailed analysis
|
||||
- Visual decision matrices
|
||||
- Charts and graphs (when appropriate)
|
||||
|
||||
**CLI/Terminal (Terminal-Friendly)**:
|
||||
- Plain text tables with ASCII borders
|
||||
- Compact formatting
|
||||
- Clear section headers
|
||||
- Copy-paste friendly code blocks
|
||||
|
||||
### Progressive Disclosure Structure
|
||||
|
||||
**Executive Summary (200-300 tokens)**:
|
||||
- Recommendation summary
|
||||
- Top 3 pros and cons
|
||||
- Confidence level (High/Medium/Low)
|
||||
- Key decision factors
|
||||
|
||||
**Detailed Breakdown (on-demand)**:
|
||||
- Complete scoring matrices
|
||||
- Detailed TCO calculations
|
||||
- Full security analysis
|
||||
- Migration complexity assessment
|
||||
- All supporting data and calculations
|
||||
|
||||
### Report Sections (User-Selectable)
|
||||
|
||||
Users choose which sections to include:
|
||||
|
||||
1. **Scoring & Comparison Matrix**
|
||||
- Weighted decision scores
|
||||
- Head-to-head comparison tables
|
||||
- Strengths and weaknesses
|
||||
|
||||
2. **Financial Analysis**
|
||||
- TCO breakdown (5-year projection)
|
||||
- ROI analysis
|
||||
- Cost per user/request metrics
|
||||
- Hidden cost identification
|
||||
|
||||
3. **Ecosystem Health**
|
||||
- Community size and activity
|
||||
- GitHub stars, npm downloads
|
||||
- Release frequency and maintenance
|
||||
- Issue response times
|
||||
- Viability assessment
|
||||
|
||||
4. **Security & Compliance**
|
||||
- Vulnerability count (CVE database)
|
||||
- Security patch frequency
|
||||
- Compliance readiness (GDPR, SOC2, HIPAA)
|
||||
- Security scoring
|
||||
|
||||
5. **Migration Analysis** (when applicable)
|
||||
- Migration complexity scoring
|
||||
- Code change estimates
|
||||
- Data migration requirements
|
||||
- Downtime assessment
|
||||
- Risk mitigation strategies
|
||||
|
||||
6. **Performance Benchmarks**
|
||||
- Throughput/latency comparisons
|
||||
- Resource usage analysis
|
||||
- Scalability characteristics
|
||||
|
||||
## How to Use
|
||||
|
||||
### Basic Invocations
|
||||
|
||||
**Quick Comparison**:
|
||||
```
|
||||
"Compare React vs Vue for our SaaS dashboard project"
|
||||
"PostgreSQL vs MongoDB for our application"
|
||||
```
|
||||
|
||||
**Stack Evaluation**:
|
||||
```
|
||||
"Evaluate technology stack for real-time collaboration platform:
|
||||
Node.js, WebSockets, Redis, PostgreSQL"
|
||||
```
|
||||
|
||||
**TCO Analysis**:
|
||||
```
|
||||
"Calculate total cost of ownership for AWS vs Azure for our workload:
|
||||
- 50 EC2/VM instances
|
||||
- 10TB storage
|
||||
- High bandwidth requirements"
|
||||
```
|
||||
|
||||
**Security Assessment**:
|
||||
```
|
||||
"Analyze security posture of our current stack:
|
||||
Express.js, MongoDB, JWT authentication.
|
||||
Need SOC2 compliance."
|
||||
```
|
||||
|
||||
**Migration Path**:
|
||||
```
|
||||
"Assess migration from Angular.js (1.x) to React.
|
||||
Application has 50,000 lines of code, 200 components."
|
||||
```
|
||||
|
||||
### Advanced Invocations
|
||||
|
||||
**Custom Analysis Sections**:
|
||||
```
|
||||
"Compare Next.js vs Nuxt.js.
|
||||
Include: Ecosystem health, TCO, and performance benchmarks.
|
||||
Skip: Migration analysis, compliance."
|
||||
```
|
||||
|
||||
**Weighted Decision Criteria**:
|
||||
```
|
||||
"Compare cloud providers for ML workloads.
|
||||
Priorities (weighted):
|
||||
- GPU availability (40%)
|
||||
- Cost (30%)
|
||||
- Ecosystem (20%)
|
||||
- Support (10%)"
|
||||
```
|
||||
|
||||
**Multi-Technology Comparison**:
|
||||
```
|
||||
"Compare: React, Vue, Svelte, Angular for enterprise SaaS.
|
||||
Use case: Large team (20+ developers), complex state management.
|
||||
Generate comprehensive decision matrix."
|
||||
```
|
||||
---
|
||||
|
||||
## Scripts
|
||||
|
||||
### Core Modules
|
||||
### stack_comparator.py
|
||||
|
||||
- **`stack_comparator.py`**: Main comparison engine with weighted scoring algorithms
|
||||
- **`tco_calculator.py`**: Total Cost of Ownership calculations (licensing, hosting, developer productivity, scaling)
|
||||
- **`ecosystem_analyzer.py`**: Community health scoring, GitHub/npm metrics, viability assessment
|
||||
- **`security_assessor.py`**: Vulnerability analysis, compliance readiness, security scoring
|
||||
- **`migration_analyzer.py`**: Migration complexity scoring, risk assessment, effort estimation
|
||||
- **`format_detector.py`**: Automatic input format detection (text, YAML, JSON, URLs)
|
||||
- **`report_generator.py`**: Context-aware report generation with progressive disclosure
|
||||
Compare technologies with customizable weighted criteria.
|
||||
|
||||
### Utility Modules
|
||||
```bash
|
||||
python scripts/stack_comparator.py --help
|
||||
```
|
||||
|
||||
- **`data_fetcher.py`**: Fetch real-time data from GitHub, npm, CVE databases
|
||||
- **`benchmark_processor.py`**: Process and normalize performance benchmark data
|
||||
- **`confidence_scorer.py`**: Calculate confidence levels for recommendations
|
||||
### tco_calculator.py
|
||||
|
||||
## Metrics and Calculations
|
||||
Calculate total cost of ownership over multi-year projections.
|
||||
|
||||
### 1. Scoring & Comparison Metrics
|
||||
```bash
|
||||
python scripts/tco_calculator.py --input assets/sample_input_tco.json
|
||||
```
|
||||
|
||||
**Technology Comparison Matrix**:
|
||||
- Feature completeness (0-100 scale)
|
||||
- Learning curve assessment (Easy/Medium/Hard)
|
||||
- Developer experience scoring
|
||||
- Documentation quality (0-10 scale)
|
||||
- Weighted total scores
|
||||
### ecosystem_analyzer.py
|
||||
|
||||
**Decision Scoring Algorithm**:
|
||||
- User-defined weights for criteria
|
||||
- Normalized scoring (0-100)
|
||||
- Confidence intervals
|
||||
- Sensitivity analysis
|
||||
Analyze ecosystem health from GitHub, npm, and community metrics.
|
||||
|
||||
### 2. Financial Calculations
|
||||
```bash
|
||||
python scripts/ecosystem_analyzer.py --technology react
|
||||
```
|
||||
|
||||
**TCO Components**:
|
||||
- **Initial Costs**: Licensing, training, migration
|
||||
- **Operational Costs**: Hosting, support, maintenance (monthly/yearly)
|
||||
- **Scaling Costs**: Per-user costs, infrastructure scaling projections
|
||||
- **Developer Productivity**: Time-to-market impact, development speed multipliers
|
||||
- **Hidden Costs**: Technical debt, vendor lock-in risks
|
||||
### security_assessor.py
|
||||
|
||||
**ROI Calculations**:
|
||||
- Cost savings projections (3-year, 5-year)
|
||||
- Productivity gains (developer hours saved)
|
||||
- Break-even analysis
|
||||
- Risk-adjusted returns
|
||||
Evaluate security posture and compliance readiness.
|
||||
|
||||
**Cost Per Metric**:
|
||||
- Cost per user (monthly/yearly)
|
||||
- Cost per API request
|
||||
- Cost per GB stored/transferred
|
||||
- Cost per compute hour
|
||||
```bash
|
||||
python scripts/security_assessor.py --technology express --compliance soc2,gdpr
|
||||
```
|
||||
|
||||
### 3. Maturity & Ecosystem Metrics
|
||||
### migration_analyzer.py
|
||||
|
||||
**Health Scoring (0-100 scale)**:
|
||||
- **GitHub Metrics**: Stars, forks, contributors, commit frequency
|
||||
- **npm Metrics**: Weekly downloads, version stability, dependency count
|
||||
- **Release Cadence**: Regular releases, semantic versioning adherence
|
||||
- **Issue Management**: Response time, resolution rate, open vs closed issues
|
||||
Estimate migration complexity, effort, and risks.
|
||||
|
||||
**Community Metrics**:
|
||||
- Active maintainers count
|
||||
- Contributor growth rate
|
||||
- Stack Overflow question volume
|
||||
- Job market demand (job postings analysis)
|
||||
```bash
|
||||
python scripts/migration_analyzer.py --from angular-1.x --to react
|
||||
```
|
||||
|
||||
**Viability Assessment**:
|
||||
- Corporate backing strength
|
||||
- Community sustainability
|
||||
- Alternative availability
|
||||
- Long-term risk scoring
|
||||
---
|
||||
|
||||
### 4. Security & Compliance Metrics
|
||||
## References
|
||||
|
||||
**Security Scoring**:
|
||||
- **CVE Count**: Known vulnerabilities (last 12 months, last 3 years)
|
||||
- **Severity Distribution**: Critical/High/Medium/Low vulnerability counts
|
||||
- **Patch Frequency**: Average time to patch (days)
|
||||
- **Security Track Record**: Historical security posture
|
||||
| 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 |
|
||||
|
||||
**Compliance Readiness**:
|
||||
- **GDPR**: Data privacy features, consent management, data portability
|
||||
- **SOC2**: Access controls, encryption, audit logging
|
||||
- **HIPAA**: PHI handling, encryption standards, access controls
|
||||
- **PCI-DSS**: Payment data security (if applicable)
|
||||
|
||||
**Compliance Scoring (per standard)**:
|
||||
- Ready: 90-100% compliant
|
||||
- Mostly Ready: 70-89% (minor gaps)
|
||||
- Partial: 50-69% (significant work needed)
|
||||
- Not Ready: <50% (major gaps)
|
||||
|
||||
### 5. Migration Analysis Metrics
|
||||
|
||||
**Complexity Scoring (1-10 scale)**:
|
||||
- **Code Changes**: Estimated lines of code affected
|
||||
- **Architecture Impact**: Breaking changes, API compatibility
|
||||
- **Data Migration**: Schema changes, data transformation complexity
|
||||
- **Downtime Requirements**: Zero-downtime possible vs planned outage
|
||||
|
||||
**Effort Estimation**:
|
||||
- Development hours (by component)
|
||||
- Testing hours
|
||||
- Training hours
|
||||
- Total person-months
|
||||
|
||||
**Risk Assessment**:
|
||||
- **Technical Risks**: API incompatibilities, performance regressions
|
||||
- **Business Risks**: Downtime impact, feature parity gaps
|
||||
- **Team Risks**: Learning curve, skill gaps
|
||||
- **Mitigation Strategies**: Risk-specific recommendations
|
||||
|
||||
**Migration Phases**:
|
||||
- Phase 1: Planning and prototyping (timeline, effort)
|
||||
- Phase 2: Core migration (timeline, effort)
|
||||
- Phase 3: Testing and validation (timeline, effort)
|
||||
- Phase 4: Deployment and monitoring (timeline, effort)
|
||||
|
||||
### 6. Performance Benchmark Metrics
|
||||
|
||||
**Throughput/Latency**:
|
||||
- Requests per second (RPS)
|
||||
- Average response time (ms)
|
||||
- P95/P99 latency percentiles
|
||||
- Concurrent user capacity
|
||||
|
||||
**Resource Usage**:
|
||||
- Memory consumption (MB/GB)
|
||||
- CPU utilization (%)
|
||||
- Storage requirements
|
||||
- Network bandwidth
|
||||
|
||||
**Scalability Characteristics**:
|
||||
- Horizontal scaling efficiency
|
||||
- Vertical scaling limits
|
||||
- Cost per performance unit
|
||||
- Scaling inflection points
|
||||
|
||||
## Best Practices
|
||||
|
||||
### For Accurate Evaluations
|
||||
|
||||
1. **Define Clear Use Case**: Specify exact requirements, constraints, and priorities
|
||||
2. **Provide Complete Context**: Team size, existing stack, timeline, budget constraints
|
||||
3. **Set Realistic Priorities**: Use weighted criteria (total = 100%) for multi-factor decisions
|
||||
4. **Consider Team Skills**: Factor in learning curve and existing expertise
|
||||
5. **Think Long-Term**: Evaluate 3-5 year outlook, not just immediate needs
|
||||
|
||||
### For TCO Analysis
|
||||
|
||||
1. **Include All Cost Components**: Don't forget training, migration, technical debt
|
||||
2. **Use Realistic Scaling Projections**: Base on actual growth metrics, not wishful thinking
|
||||
3. **Account for Developer Productivity**: Time-to-market and development speed are critical costs
|
||||
4. **Consider Hidden Costs**: Vendor lock-in, exit costs, technical debt accumulation
|
||||
5. **Validate Assumptions**: Document all TCO assumptions for review
|
||||
|
||||
### For Migration Decisions
|
||||
|
||||
1. **Start with Risk Assessment**: Identify showstoppers early
|
||||
2. **Plan Incremental Migration**: Avoid big-bang rewrites when possible
|
||||
3. **Prototype Critical Paths**: Test complex migration scenarios before committing
|
||||
4. **Build Rollback Plans**: Always have a fallback strategy
|
||||
5. **Measure Baseline Performance**: Establish current metrics before migration
|
||||
|
||||
### For Security Evaluation
|
||||
|
||||
1. **Check Recent Vulnerabilities**: Focus on last 12 months for current security posture
|
||||
2. **Review Patch Response Time**: Fast patching is more important than zero vulnerabilities
|
||||
3. **Validate Compliance Claims**: Vendor claims ≠ actual compliance readiness
|
||||
4. **Consider Supply Chain**: Evaluate security of all dependencies
|
||||
5. **Test Security Features**: Don't assume features work as documented
|
||||
|
||||
## Limitations
|
||||
|
||||
### Data Accuracy
|
||||
|
||||
- **Ecosystem metrics** are point-in-time snapshots (GitHub stars, npm downloads change rapidly)
|
||||
- **TCO calculations** are estimates based on provided assumptions and market rates
|
||||
- **Benchmark data** may not reflect your specific use case or configuration
|
||||
- **Security vulnerability counts** depend on public CVE database completeness
|
||||
|
||||
### Scope Boundaries
|
||||
|
||||
- **Industry-Specific Requirements**: Some specialized industries may have unique constraints not covered by standard analysis
|
||||
- **Emerging Technologies**: Very new technologies (<1 year old) may lack sufficient data for accurate assessment
|
||||
- **Custom/Proprietary Solutions**: Cannot evaluate closed-source or internal tools without data
|
||||
- **Political/Organizational Factors**: Cannot account for company politics, vendor relationships, or legacy commitments
|
||||
|
||||
### Contextual Limitations
|
||||
|
||||
- **Team Skill Assessment**: Cannot directly evaluate your team's specific skills and learning capacity
|
||||
- **Existing Architecture**: Recommendations assume greenfield unless migration context provided
|
||||
- **Budget Constraints**: TCO analysis provides costs but cannot make budget decisions for you
|
||||
- **Timeline Pressure**: Cannot account for business deadlines and time-to-market urgency
|
||||
|
||||
### When NOT to Use This Skill
|
||||
|
||||
- **Trivial Decisions**: Choosing between nearly-identical tools (use team preference)
|
||||
- **Mandated Solutions**: When technology choice is already decided by management/policy
|
||||
- **Insufficient Context**: When you don't know your requirements, priorities, or constraints
|
||||
- **Real-Time Production Decisions**: Use for planning, not emergency production issues
|
||||
- **Non-Technical Decisions**: Business strategy, hiring, organizational issues
|
||||
---
|
||||
|
||||
## Confidence Levels
|
||||
|
||||
The skill provides confidence scores with all recommendations:
|
||||
| Level | Score | Interpretation |
|
||||
|-------|-------|----------------|
|
||||
| High | 80-100% | Clear winner, strong data |
|
||||
| Medium | 50-79% | Trade-offs present, moderate uncertainty |
|
||||
| Low | < 50% | Close call, limited data |
|
||||
|
||||
- **High Confidence (80-100%)**: Strong data, clear winner, low risk
|
||||
- **Medium Confidence (50-79%)**: Good data, trade-offs present, moderate risk
|
||||
- **Low Confidence (<50%)**: Limited data, close call, high uncertainty
|
||||
- **Insufficient Data**: Cannot make recommendation without more information
|
||||
---
|
||||
|
||||
Confidence is based on:
|
||||
- Data completeness and recency
|
||||
- Consensus across multiple metrics
|
||||
- Clarity of use case requirements
|
||||
- Industry maturity and standards
|
||||
## 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)
|
||||
|
||||
383
engineering-team/tech-stack-evaluator/references/examples.md
Normal file
383
engineering-team/tech-stack-evaluator/references/examples.md
Normal file
@@ -0,0 +1,383 @@
|
||||
# Technology Evaluation Examples
|
||||
|
||||
Concrete examples showing input formats and expected outputs.
|
||||
|
||||
---
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Quick Comparison Example](#quick-comparison-example)
|
||||
- [TCO Analysis Example](#tco-analysis-example)
|
||||
- [Ecosystem Analysis Example](#ecosystem-analysis-example)
|
||||
- [Migration Assessment Example](#migration-assessment-example)
|
||||
- [Multi-Technology Comparison](#multi-technology-comparison)
|
||||
|
||||
---
|
||||
|
||||
## Quick Comparison Example
|
||||
|
||||
### Input (Text Format)
|
||||
|
||||
```
|
||||
Compare React vs Vue for building a SaaS dashboard.
|
||||
Focus on: developer productivity, ecosystem maturity, performance.
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
TECHNOLOGY COMPARISON: React vs Vue for SaaS Dashboard
|
||||
=======================================================
|
||||
|
||||
RECOMMENDATION: React
|
||||
Confidence: 78% (Medium-High)
|
||||
|
||||
COMPARISON MATRIX
|
||||
-----------------
|
||||
| Category | Weight | React | Vue |
|
||||
|----------------------|--------|-------|------|
|
||||
| Performance | 15% | 82.0 | 85.0 |
|
||||
| Scalability | 15% | 88.0 | 80.0 |
|
||||
| Developer Experience | 20% | 85.0 | 90.0 |
|
||||
| Ecosystem | 15% | 92.0 | 78.0 |
|
||||
| Learning Curve | 10% | 70.0 | 85.0 |
|
||||
| Documentation | 10% | 88.0 | 82.0 |
|
||||
| Community Support | 10% | 90.0 | 75.0 |
|
||||
| Enterprise Readiness | 5% | 85.0 | 72.0 |
|
||||
|----------------------|--------|-------|------|
|
||||
| WEIGHTED TOTAL | 100% | 85.2 | 81.1 |
|
||||
|
||||
KEY DECISION FACTORS
|
||||
--------------------
|
||||
1. Ecosystem (15%): React leads with 92.0 - larger npm ecosystem
|
||||
2. Developer Experience (20%): Vue leads with 90.0 - gentler learning curve
|
||||
3. Community Support (10%): React leads with 90.0 - more Stack Overflow resources
|
||||
|
||||
PROS/CONS SUMMARY
|
||||
-----------------
|
||||
React:
|
||||
✓ Excellent ecosystem (92.0/100)
|
||||
✓ Strong community support (90.0/100)
|
||||
✓ Excellent scalability (88.0/100)
|
||||
✗ Steeper learning curve (70.0/100)
|
||||
|
||||
Vue:
|
||||
✓ Excellent developer experience (90.0/100)
|
||||
✓ Good performance (85.0/100)
|
||||
✓ Easier learning curve (85.0/100)
|
||||
✗ Smaller enterprise presence (72.0/100)
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## TCO Analysis Example
|
||||
|
||||
### Input (JSON Format)
|
||||
|
||||
```json
|
||||
{
|
||||
"technology": "Next.js on Vercel",
|
||||
"team_size": 8,
|
||||
"timeline_years": 5,
|
||||
"initial_costs": {
|
||||
"licensing": 0,
|
||||
"training_hours_per_dev": 24,
|
||||
"developer_hourly_rate": 85,
|
||||
"migration": 15000,
|
||||
"setup": 5000
|
||||
},
|
||||
"operational_costs": {
|
||||
"monthly_hosting": 2500,
|
||||
"annual_support": 0,
|
||||
"maintenance_hours_per_dev_monthly": 16
|
||||
},
|
||||
"scaling_params": {
|
||||
"initial_users": 5000,
|
||||
"annual_growth_rate": 0.40,
|
||||
"initial_servers": 3,
|
||||
"cost_per_server_monthly": 150
|
||||
}
|
||||
}
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
TCO ANALYSIS: Next.js on Vercel (5-Year Projection)
|
||||
====================================================
|
||||
|
||||
EXECUTIVE SUMMARY
|
||||
-----------------
|
||||
Total TCO: $1,247,320
|
||||
Net TCO (after productivity gains): $987,320
|
||||
Average Yearly Cost: $249,464
|
||||
|
||||
INITIAL COSTS (One-Time)
|
||||
------------------------
|
||||
| Component | Cost |
|
||||
|----------------|-----------|
|
||||
| Licensing | $0 |
|
||||
| Training | $16,820 |
|
||||
| Migration | $15,000 |
|
||||
| Setup | $5,000 |
|
||||
|----------------|-----------|
|
||||
| TOTAL INITIAL | $36,820 |
|
||||
|
||||
OPERATIONAL COSTS (Per Year)
|
||||
----------------------------
|
||||
| Year | Hosting | Maintenance | Total |
|
||||
|------|----------|-------------|-----------|
|
||||
| 1 | $30,000 | $130,560 | $160,560 |
|
||||
| 2 | $42,000 | $130,560 | $172,560 |
|
||||
| 3 | $58,800 | $130,560 | $189,360 |
|
||||
| 4 | $82,320 | $130,560 | $212,880 |
|
||||
| 5 | $115,248 | $130,560 | $245,808 |
|
||||
|
||||
SCALING ANALYSIS
|
||||
----------------
|
||||
User Projections: 5,000 → 7,000 → 9,800 → 13,720 → 19,208
|
||||
Cost per User: $32.11 → $24.65 → $19.32 → $15.52 → $12.79
|
||||
Scaling Efficiency: Excellent - economies of scale achieved
|
||||
|
||||
KEY COST DRIVERS
|
||||
----------------
|
||||
1. Developer maintenance time ($652,800 over 5 years)
|
||||
2. Infrastructure/hosting ($328,368 over 5 years)
|
||||
|
||||
OPTIMIZATION OPPORTUNITIES
|
||||
--------------------------
|
||||
• Consider automation to reduce maintenance hours
|
||||
• Evaluate reserved capacity pricing for hosting
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Ecosystem Analysis Example
|
||||
|
||||
### Input
|
||||
|
||||
```yaml
|
||||
technology: "Svelte"
|
||||
github:
|
||||
stars: 78000
|
||||
forks: 4100
|
||||
contributors: 680
|
||||
commits_last_month: 45
|
||||
avg_issue_response_hours: 36
|
||||
issue_resolution_rate: 0.72
|
||||
releases_per_year: 8
|
||||
active_maintainers: 5
|
||||
npm:
|
||||
weekly_downloads: 420000
|
||||
version: "4.2.8"
|
||||
dependencies_count: 0
|
||||
days_since_last_publish: 21
|
||||
community:
|
||||
stackoverflow_questions: 8500
|
||||
job_postings: 1200
|
||||
tutorials_count: 350
|
||||
forum_members: 25000
|
||||
corporate_backing:
|
||||
type: "community_led"
|
||||
funding_millions: 0
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
ECOSYSTEM ANALYSIS: Svelte
|
||||
==========================
|
||||
|
||||
OVERALL HEALTH SCORE: 71.5/100
|
||||
|
||||
HEALTH SCORE BREAKDOWN
|
||||
----------------------
|
||||
| Category | Score | Assessment |
|
||||
|--------------------|-------|-------------------|
|
||||
| GitHub Health | 78.0 | Strong |
|
||||
| npm Health | 72.0 | Good |
|
||||
| Community Health | 58.0 | Moderate |
|
||||
| Corporate Backing | 40.0 | Community-led |
|
||||
| Maintenance Health | 75.0 | Active |
|
||||
|
||||
VIABILITY ASSESSMENT
|
||||
--------------------
|
||||
Overall: Good - Solid viability with minor concerns
|
||||
Risk Level: Low-Medium
|
||||
|
||||
Strengths:
|
||||
• Strong GitHub presence with active community
|
||||
• Active maintenance with responsive issue resolution
|
||||
• High npm adoption with stable releases
|
||||
|
||||
Risks:
|
||||
• Weak corporate backing - sustainability concerns
|
||||
• Smaller community - limited enterprise resources
|
||||
|
||||
RECOMMENDATION
|
||||
--------------
|
||||
Suitable for adoption - monitor corporate backing situation.
|
||||
Consider alternative with stronger backing for mission-critical enterprise apps.
|
||||
|
||||
KEY METRICS
|
||||
-----------
|
||||
GitHub: 78,000 stars, 680 contributors, 45 commits/month
|
||||
npm: 420,000 weekly downloads, v4.2.8
|
||||
Community: 8,500 SO questions, 1,200 job postings
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Migration Assessment Example
|
||||
|
||||
### Input
|
||||
|
||||
```
|
||||
Assess migration from Angular.js (1.x) to React.
|
||||
Application: 50,000 lines of code, 200 components.
|
||||
Team: 6 developers, 2 have React experience.
|
||||
Timeline: Need completion within 8 months.
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
MIGRATION ASSESSMENT: Angular.js 1.x → React
|
||||
=============================================
|
||||
|
||||
COMPLEXITY SCORE: 7.8/10 (High)
|
||||
|
||||
COMPLEXITY BREAKDOWN
|
||||
--------------------
|
||||
| Factor | Score | Impact |
|
||||
|---------------------|-------|-------------|
|
||||
| Code Changes | 8/10 | 50K LOC |
|
||||
| Architecture Impact | 9/10 | Complete |
|
||||
| Data Migration | 5/10 | State only |
|
||||
| Downtime Risk | 6/10 | Mitigatable |
|
||||
|
||||
EFFORT ESTIMATION
|
||||
-----------------
|
||||
| Phase | Hours | Duration |
|
||||
|--------------------------|--------|----------|
|
||||
| Planning & Prototyping | 240 | 3 weeks |
|
||||
| Core Migration | 2,400 | 16 weeks |
|
||||
| Testing & Validation | 480 | 5 weeks |
|
||||
| Deployment & Monitoring | 160 | 2 weeks |
|
||||
|--------------------------|--------|----------|
|
||||
| TOTAL | 3,280 | 26 weeks |
|
||||
|
||||
Timeline Assessment: 26 weeks exceeds 8-month target (32 weeks)
|
||||
Recommendation: Feasible with buffer
|
||||
|
||||
RISK ASSESSMENT
|
||||
---------------
|
||||
Technical Risks:
|
||||
• High - Two-way binding to unidirectional data flow
|
||||
• Medium - Dependency injection to hooks/context
|
||||
• Medium - Performance regression during transition
|
||||
|
||||
Business Risks:
|
||||
• Medium - Feature freeze during migration
|
||||
• Low - Customer impact with phased approach
|
||||
|
||||
Team Risks:
|
||||
• High - 4 of 6 developers need React training
|
||||
• Medium - Learning curve affects velocity initially
|
||||
|
||||
MIGRATION STRATEGY
|
||||
------------------
|
||||
Recommended Approach: Strangler Fig Pattern
|
||||
|
||||
Phase 1 (Weeks 1-8): Strangler setup
|
||||
• Create React shell application
|
||||
• Set up micro-frontend routing
|
||||
• Migrate shared utilities
|
||||
|
||||
Phase 2 (Weeks 9-18): Component migration
|
||||
• Migrate components by feature area
|
||||
• Maintain Angular.js for untouched areas
|
||||
• Continuous integration testing
|
||||
|
||||
Phase 3 (Weeks 19-24): Completion
|
||||
• Migrate remaining components
|
||||
• Remove Angular.js dependencies
|
||||
• Performance optimization
|
||||
|
||||
Phase 4 (Weeks 25-26): Stabilization
|
||||
• Production deployment
|
||||
• Monitoring and fixes
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## Multi-Technology Comparison
|
||||
|
||||
### Input
|
||||
|
||||
```
|
||||
Compare: React, Vue, Svelte, Angular for enterprise SaaS.
|
||||
Use case: Large team (20+ developers), complex state management.
|
||||
Generate comprehensive decision matrix.
|
||||
```
|
||||
|
||||
### Output
|
||||
|
||||
```
|
||||
MULTI-TECHNOLOGY COMPARISON: Enterprise SaaS Platform
|
||||
======================================================
|
||||
|
||||
RECOMMENDATION: React
|
||||
Confidence: 72% (Medium)
|
||||
Runner-up: Angular (close second for enterprise)
|
||||
|
||||
DECISION MATRIX
|
||||
---------------
|
||||
| Category | Wt | React | Vue | Svelte | Angular |
|
||||
|----------------------|------|-------|------|--------|---------|
|
||||
| Performance | 15% | 82 | 85 | 95 | 78 |
|
||||
| Scalability | 15% | 90 | 82 | 75 | 92 |
|
||||
| Developer Experience | 20% | 85 | 90 | 88 | 75 |
|
||||
| Ecosystem | 15% | 95 | 80 | 65 | 88 |
|
||||
| Learning Curve | 10% | 70 | 85 | 80 | 60 |
|
||||
| Documentation | 10% | 90 | 85 | 75 | 92 |
|
||||
| Community Support | 10% | 92 | 78 | 55 | 85 |
|
||||
| Enterprise Readiness | 5% | 88 | 72 | 50 | 95 |
|
||||
|----------------------|------|-------|------|--------|---------|
|
||||
| WEIGHTED TOTAL | 100% | 86.3 | 83.1 | 76.2 | 83.0 |
|
||||
|
||||
FRAMEWORK PROFILES
|
||||
------------------
|
||||
React: Best for large ecosystem, hiring pool
|
||||
Angular: Best for enterprise structure, TypeScript-first
|
||||
Vue: Best for developer experience, gradual adoption
|
||||
Svelte: Best for performance, smaller bundles
|
||||
|
||||
RECOMMENDATION RATIONALE
|
||||
------------------------
|
||||
For 20+ developer team with complex state management:
|
||||
|
||||
1. React (Recommended)
|
||||
• Largest talent pool for hiring
|
||||
• Extensive enterprise libraries (Redux, React Query)
|
||||
• Meta backing ensures long-term support
|
||||
• Most Stack Overflow resources
|
||||
|
||||
2. Angular (Strong Alternative)
|
||||
• Built-in structure for large teams
|
||||
• TypeScript-first reduces bugs
|
||||
• Comprehensive CLI and tooling
|
||||
• Google enterprise backing
|
||||
|
||||
3. Vue (Consider for DX)
|
||||
• Excellent documentation
|
||||
• Easier onboarding
|
||||
• Growing enterprise adoption
|
||||
• Consider if DX is top priority
|
||||
|
||||
4. Svelte (Not Recommended for This Use Case)
|
||||
• Smaller ecosystem for enterprise
|
||||
• Limited hiring pool
|
||||
• State management options less mature
|
||||
• Better for smaller teams/projects
|
||||
```
|
||||
242
engineering-team/tech-stack-evaluator/references/metrics.md
Normal file
242
engineering-team/tech-stack-evaluator/references/metrics.md
Normal file
@@ -0,0 +1,242 @@
|
||||
# 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 |
|
||||
362
engineering-team/tech-stack-evaluator/references/workflows.md
Normal file
362
engineering-team/tech-stack-evaluator/references/workflows.md
Normal file
@@ -0,0 +1,362 @@
|
||||
# Technology Evaluation Workflows
|
||||
|
||||
Step-by-step workflows for common evaluation scenarios.
|
||||
|
||||
---
|
||||
|
||||
## Table of Contents
|
||||
|
||||
- [Framework Comparison Workflow](#framework-comparison-workflow)
|
||||
- [TCO Analysis Workflow](#tco-analysis-workflow)
|
||||
- [Migration Assessment Workflow](#migration-assessment-workflow)
|
||||
- [Security Evaluation Workflow](#security-evaluation-workflow)
|
||||
- [Cloud Provider Selection Workflow](#cloud-provider-selection-workflow)
|
||||
|
||||
---
|
||||
|
||||
## Framework Comparison Workflow
|
||||
|
||||
Use this workflow when comparing frontend/backend frameworks or libraries.
|
||||
|
||||
### Step 1: Define Requirements
|
||||
|
||||
1. Identify the use case:
|
||||
- What type of application? (SaaS, e-commerce, real-time, etc.)
|
||||
- What scale? (users, requests, data volume)
|
||||
- What team size and skill level?
|
||||
|
||||
2. Set priorities (weights must sum to 100%):
|
||||
- Performance: ____%
|
||||
- Scalability: ____%
|
||||
- Developer Experience: ____%
|
||||
- Ecosystem: ____%
|
||||
- Learning Curve: ____%
|
||||
- Other: ____%
|
||||
|
||||
3. List constraints:
|
||||
- Budget limitations
|
||||
- Timeline requirements
|
||||
- Compliance needs
|
||||
- Existing infrastructure
|
||||
|
||||
### Step 2: Run Comparison
|
||||
|
||||
```bash
|
||||
python scripts/stack_comparator.py \
|
||||
--technologies "React,Vue,Angular" \
|
||||
--use-case "enterprise-saas" \
|
||||
--weights "performance:20,ecosystem:25,scalability:20,developer_experience:35"
|
||||
```
|
||||
|
||||
### Step 3: Analyze Results
|
||||
|
||||
1. Review weighted total scores
|
||||
2. Check confidence level (High/Medium/Low)
|
||||
3. Examine strengths and weaknesses for each option
|
||||
4. Review decision factors
|
||||
|
||||
### Step 4: Validate Recommendation
|
||||
|
||||
1. Match recommendation to your constraints
|
||||
2. Consider team skills and hiring market
|
||||
3. Evaluate ecosystem for your specific needs
|
||||
4. Check corporate backing and long-term viability
|
||||
|
||||
### Step 5: Document Decision
|
||||
|
||||
Record:
|
||||
- Final selection with rationale
|
||||
- Trade-offs accepted
|
||||
- Risks identified
|
||||
- Mitigation strategies
|
||||
|
||||
---
|
||||
|
||||
## TCO Analysis Workflow
|
||||
|
||||
Use this workflow for comprehensive cost analysis over multiple years.
|
||||
|
||||
### Step 1: Gather Cost Data
|
||||
|
||||
**Initial Costs:**
|
||||
- [ ] Licensing fees (if any)
|
||||
- [ ] Training hours per developer
|
||||
- [ ] Developer hourly rate
|
||||
- [ ] Migration costs
|
||||
- [ ] Setup and tooling costs
|
||||
|
||||
**Operational Costs:**
|
||||
- [ ] Monthly hosting costs
|
||||
- [ ] Annual support contracts
|
||||
- [ ] Maintenance hours per developer per month
|
||||
|
||||
**Scaling Parameters:**
|
||||
- [ ] Initial user count
|
||||
- [ ] Expected annual growth rate
|
||||
- [ ] Infrastructure scaling approach
|
||||
|
||||
### Step 2: Run TCO Calculator
|
||||
|
||||
```bash
|
||||
python scripts/tco_calculator.py \
|
||||
--input assets/sample_input_tco.json \
|
||||
--years 5 \
|
||||
--output tco_report.json
|
||||
```
|
||||
|
||||
### Step 3: Analyze Cost Breakdown
|
||||
|
||||
1. Review initial vs. operational costs ratio
|
||||
2. Examine year-over-year cost growth
|
||||
3. Check cost per user trends
|
||||
4. Identify scaling efficiency
|
||||
|
||||
### Step 4: Identify Optimization Opportunities
|
||||
|
||||
Review:
|
||||
- Can hosting costs be reduced with reserved pricing?
|
||||
- Can automation reduce maintenance hours?
|
||||
- Are there cheaper alternatives for specific components?
|
||||
|
||||
### Step 5: Compare Multiple Options
|
||||
|
||||
Run TCO analysis for each technology option:
|
||||
1. Current state (baseline)
|
||||
2. Option A
|
||||
3. Option B
|
||||
|
||||
Compare:
|
||||
- 5-year total cost
|
||||
- Break-even point
|
||||
- Risk-adjusted costs
|
||||
|
||||
---
|
||||
|
||||
## Migration Assessment Workflow
|
||||
|
||||
Use this workflow when planning technology migrations.
|
||||
|
||||
### Step 1: Document Current State
|
||||
|
||||
1. Count lines of code
|
||||
2. List all components/modules
|
||||
3. Identify dependencies
|
||||
4. Document current architecture
|
||||
5. Note existing pain points
|
||||
|
||||
### Step 2: Define Target State
|
||||
|
||||
1. Target technology/framework
|
||||
2. Target architecture
|
||||
3. Expected benefits
|
||||
4. Success criteria
|
||||
|
||||
### Step 3: Assess Team Readiness
|
||||
|
||||
- How many developers have target technology experience?
|
||||
- What training is needed?
|
||||
- What is the team's capacity during migration?
|
||||
|
||||
### Step 4: Run Migration Analysis
|
||||
|
||||
```bash
|
||||
python scripts/migration_analyzer.py \
|
||||
--from "angular-1.x" \
|
||||
--to "react" \
|
||||
--codebase-size 50000 \
|
||||
--components 200 \
|
||||
--team-size 6
|
||||
```
|
||||
|
||||
### Step 5: Review Risk Assessment
|
||||
|
||||
For each risk category:
|
||||
1. Identify specific risks
|
||||
2. Assess probability and impact
|
||||
3. Define mitigation strategies
|
||||
4. Assign risk owners
|
||||
|
||||
### Step 6: Plan Migration Phases
|
||||
|
||||
1. **Phase 1: Foundation**
|
||||
- Setup new infrastructure
|
||||
- Create migration utilities
|
||||
- Train team
|
||||
|
||||
2. **Phase 2: Incremental Migration**
|
||||
- Migrate by feature area
|
||||
- Maintain parallel systems
|
||||
- Continuous testing
|
||||
|
||||
3. **Phase 3: Completion**
|
||||
- Remove legacy code
|
||||
- Optimize performance
|
||||
- Complete documentation
|
||||
|
||||
4. **Phase 4: Stabilization**
|
||||
- Monitor production
|
||||
- Address issues
|
||||
- Gather metrics
|
||||
|
||||
### Step 7: Define Rollback Plan
|
||||
|
||||
Document:
|
||||
- Trigger conditions for rollback
|
||||
- Rollback procedure
|
||||
- Data recovery steps
|
||||
- Communication plan
|
||||
|
||||
---
|
||||
|
||||
## Security Evaluation Workflow
|
||||
|
||||
Use this workflow for security and compliance assessment.
|
||||
|
||||
### Step 1: Identify Requirements
|
||||
|
||||
1. List applicable compliance standards:
|
||||
- [ ] GDPR
|
||||
- [ ] SOC2
|
||||
- [ ] HIPAA
|
||||
- [ ] PCI-DSS
|
||||
- [ ] Other: _____
|
||||
|
||||
2. Define security priorities:
|
||||
- Data encryption requirements
|
||||
- Access control needs
|
||||
- Audit logging requirements
|
||||
- Incident response expectations
|
||||
|
||||
### Step 2: Gather Security Data
|
||||
|
||||
For each technology:
|
||||
- [ ] CVE count (last 12 months)
|
||||
- [ ] CVE count (last 3 years)
|
||||
- [ ] Severity distribution
|
||||
- [ ] Average patch time
|
||||
- [ ] Security features list
|
||||
|
||||
### Step 3: Run Security Assessment
|
||||
|
||||
```bash
|
||||
python scripts/security_assessor.py \
|
||||
--technology "express-js" \
|
||||
--compliance "soc2,gdpr" \
|
||||
--output security_report.json
|
||||
```
|
||||
|
||||
### Step 4: Analyze Results
|
||||
|
||||
Review:
|
||||
1. Overall security score
|
||||
2. Vulnerability trends
|
||||
3. Patch responsiveness
|
||||
4. Compliance readiness per standard
|
||||
|
||||
### Step 5: Identify Gaps
|
||||
|
||||
For each compliance standard:
|
||||
1. List missing requirements
|
||||
2. Estimate remediation effort
|
||||
3. Identify workarounds if available
|
||||
4. Calculate compliance cost
|
||||
|
||||
### Step 6: Make Risk-Based Decision
|
||||
|
||||
Consider:
|
||||
- Acceptable risk level
|
||||
- Cost of remediation
|
||||
- Alternative technologies
|
||||
- Business impact of compliance gaps
|
||||
|
||||
---
|
||||
|
||||
## Cloud Provider Selection Workflow
|
||||
|
||||
Use this workflow for AWS vs Azure vs GCP decisions.
|
||||
|
||||
### Step 1: Define Workload Requirements
|
||||
|
||||
1. Workload type:
|
||||
- [ ] Web application
|
||||
- [ ] API services
|
||||
- [ ] Data analytics
|
||||
- [ ] Machine learning
|
||||
- [ ] IoT
|
||||
- [ ] Other: _____
|
||||
|
||||
2. Resource requirements:
|
||||
- Compute: ____ instances, ____ cores, ____ GB RAM
|
||||
- Storage: ____ TB, type (block/object/file)
|
||||
- Database: ____ type, ____ size
|
||||
- Network: ____ GB/month transfer
|
||||
|
||||
3. Special requirements:
|
||||
- [ ] GPU/TPU for ML
|
||||
- [ ] Edge computing
|
||||
- [ ] Multi-region
|
||||
- [ ] Specific compliance certifications
|
||||
|
||||
### Step 2: Evaluate Feature Availability
|
||||
|
||||
For each provider, verify:
|
||||
- Required services exist
|
||||
- Service maturity level
|
||||
- Regional availability
|
||||
- SLA guarantees
|
||||
|
||||
### Step 3: Run Cost Comparison
|
||||
|
||||
```bash
|
||||
python scripts/tco_calculator.py \
|
||||
--providers "aws,azure,gcp" \
|
||||
--workload-config workload.json \
|
||||
--years 3
|
||||
```
|
||||
|
||||
### Step 4: Assess Ecosystem Fit
|
||||
|
||||
Consider:
|
||||
- Team's existing expertise
|
||||
- Development tooling preferences
|
||||
- CI/CD integration
|
||||
- Monitoring and observability tools
|
||||
|
||||
### Step 5: Evaluate Vendor Lock-in
|
||||
|
||||
For each provider:
|
||||
1. List proprietary services you'll use
|
||||
2. Estimate migration cost if switching
|
||||
3. Identify portable alternatives
|
||||
4. Calculate lock-in risk score
|
||||
|
||||
### Step 6: Make Final Selection
|
||||
|
||||
Weight factors:
|
||||
- Cost: ____%
|
||||
- Features: ____%
|
||||
- Team expertise: ____%
|
||||
- Lock-in risk: ____%
|
||||
- Support quality: ____%
|
||||
|
||||
Select provider with highest weighted score.
|
||||
|
||||
---
|
||||
|
||||
## Best Practices
|
||||
|
||||
### For All Evaluations
|
||||
|
||||
1. **Document assumptions** - Make all assumptions explicit
|
||||
2. **Validate data** - Verify metrics from multiple sources
|
||||
3. **Consider context** - Generic scores may not apply to your situation
|
||||
4. **Include stakeholders** - Get input from team members who will use the technology
|
||||
5. **Plan for change** - Technology landscapes evolve; plan for flexibility
|
||||
|
||||
### Common Pitfalls to Avoid
|
||||
|
||||
1. Over-weighting recent popularity vs. long-term stability
|
||||
2. Ignoring team learning curve in timeline estimates
|
||||
3. Underestimating migration complexity
|
||||
4. Assuming vendor claims are accurate
|
||||
5. Not accounting for hidden costs (training, hiring, technical debt)
|
||||
Reference in New Issue
Block a user