tech-stack-evaluator
技術スタックの評価や比較に加え、総所有コストやセキュリティ、エコシステムの健全性まで分析し、最適な選択を支援するSkill。
📜 元の英語説明(参考)
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.
🇯🇵 日本人クリエイター向け解説
技術スタックの評価や比較に加え、総所有コストやセキュリティ、エコシステムの健全性まで分析し、最適な選択を支援するSkill。
※ jpskill.com 編集部が日本のビジネス現場向けに補足した解説です。Skill本体の挙動とは独立した参考情報です。
⚠️ ダウンロード・利用は自己責任でお願いします。当サイトは内容・動作・安全性について責任を負いません。
🎯 このSkillでできること
下記の説明文を読むと、このSkillがあなたに何をしてくれるかが分かります。Claudeにこの分野の依頼をすると、自動で発動します。
📦 インストール方法 (3ステップ)
- 1. 上の「ダウンロード」ボタンを押して .skill ファイルを取得
- 2. ファイル名の拡張子を .skill から .zip に変えて展開(macは自動展開可)
- 3. 展開してできたフォルダを、ホームフォルダの
.claude/skills/に置く- · macOS / Linux:
~/.claude/skills/ - · Windows:
%USERPROFILE%\.claude\skills\
- · macOS / Linux:
Claude Code を再起動すれば完了。「このSkillを使って…」と話しかけなくても、関連する依頼で自動的に呼び出されます。
詳しい使い方ガイドを見る →- 最終更新
- 2026-05-17
- 取得日時
- 2026-05-17
- 同梱ファイル
- 15
📖 Claude が読む原文 SKILL.md(中身を展開)
この本文は AI(Claude)が読むための原文(英語または中国語)です。日本語訳は順次追加中。
Technology Stack Evaluator
Evaluate and compare technologies, frameworks, and cloud providers with data-driven analysis and actionable recommendations.
Table of Contents
Capabilities
| Capability | Description |
|---|---|
| Technology Comparison | Compare frameworks and libraries with weighted scoring |
| TCO Analysis | Calculate 5-year total cost including hidden costs |
| Ecosystem Health | Assess GitHub metrics, npm adoption, community strength |
| Security Assessment | Evaluate vulnerabilities and compliance readiness |
| Migration Analysis | Estimate effort, risks, and timeline for migrations |
| Cloud Comparison | Compare AWS, Azure, GCP for specific workloads |
Quick Start
Compare Two Technologies
Compare React vs Vue for a SaaS dashboard.
Priorities: developer productivity (40%), ecosystem (30%), performance (30%).
Calculate TCO
Calculate 5-year TCO for Next.js on Vercel.
Team: 8 developers. Hosting: $2500/month. Growth: 40%/year.
Assess Migration
Evaluate migrating from Angular.js to React.
Codebase: 50,000 lines, 200 components. Team: 6 developers.
Input Formats
The evaluator accepts three input formats:
Text - Natural language queries
Compare PostgreSQL vs MongoDB for our e-commerce platform.
YAML - Structured input for automation
comparison:
technologies: ["React", "Vue"]
use_case: "SaaS dashboard"
weights:
ecosystem: 30
performance: 25
developer_experience: 45
JSON - Programmatic integration
{
"technologies": ["React", "Vue"],
"use_case": "SaaS dashboard"
}
Analysis Types
Quick Comparison (200-300 tokens)
- Weighted scores and recommendation
- Top 3 decision factors
- Confidence level
Standard Analysis (500-800 tokens)
- Comparison matrix
- TCO overview
- Security summary
Full Report (1200-1500 tokens)
- All metrics and calculations
- Migration analysis
- Detailed recommendations
Scripts
stack_comparator.py
Compare technologies with customizable weighted criteria.
python scripts/stack_comparator.py --help
tco_calculator.py
Calculate total cost of ownership over multi-year projections.
python scripts/tco_calculator.py --input assets/sample_input_tco.json
ecosystem_analyzer.py
Analyze ecosystem health from GitHub, npm, and community metrics.
python scripts/ecosystem_analyzer.py --technology react
security_assessor.py
Evaluate security posture and compliance readiness.
python scripts/security_assessor.py --technology express --compliance soc2,gdpr
migration_analyzer.py
Estimate migration complexity, effort, and risks.
python scripts/migration_analyzer.py --from angular-1.x --to react
References
| Document | Content |
|---|---|
references/metrics.md |
Detailed scoring algorithms and calculation formulas |
references/examples.md |
Input/output examples for all analysis types |
references/workflows.md |
Step-by-step evaluation workflows |
Confidence Levels
| Level | Score | Interpretation |
|---|---|---|
| High | 80-100% | Clear winner, strong data |
| Medium | 50-79% | Trade-offs present, moderate uncertainty |
| Low | < 50% | Close call, limited data |
When to Use
- Comparing frontend/backend frameworks for new projects
- Evaluating cloud providers for specific workloads
- Planning technology migrations with risk assessment
- Calculating build vs. buy decisions with TCO
- Assessing open-source library viability
When NOT to Use
- Trivial decisions between similar tools (use team preference)
- Mandated technology choices (decision already made)
- Emergency production issues (use monitoring tools)
同梱ファイル
※ ZIPに含まれるファイル一覧。`SKILL.md` 本体に加え、参考資料・サンプル・スクリプトが入っている場合があります。
- 📄 SKILL.md (4,348 bytes)
- 📎 assets/expected_output_comparison.json (1,953 bytes)
- 📎 assets/sample_input_structured.json (1,109 bytes)
- 📎 assets/sample_input_tco.json (1,152 bytes)
- 📎 assets/sample_input_text.json (237 bytes)
- 📎 references/examples.md (10,528 bytes)
- 📎 references/metrics.md (6,656 bytes)
- 📎 references/workflows.md (8,232 bytes)
- 📎 scripts/ecosystem_analyzer.py (16,534 bytes)
- 📎 scripts/format_detector.py (12,611 bytes)
- 📎 scripts/migration_analyzer.py (20,589 bytes)
- 📎 scripts/report_generator.py (15,891 bytes)
- 📎 scripts/security_assessor.py (17,733 bytes)
- 📎 scripts/stack_comparator.py (12,381 bytes)
- 📎 scripts/tco_calculator.py (16,153 bytes)