tech-stack-evaluator
Comprehensive technology stack evaluation and comparison tool with TCO analysis, security assessment, and intelligent recommendations for engineering teams
Third-Party Agent Skill: Review the code before installing. Agent skills execute in your AI assistant's environment and can access your files. Learn more about security
Installation for Agentic Skill
View all platforms →skilz install alirezarezvani/claude-code-skill-factory/tech-stack-evaluatorskilz install alirezarezvani/claude-code-skill-factory/tech-stack-evaluator --agent opencodeskilz install alirezarezvani/claude-code-skill-factory/tech-stack-evaluator --agent codexskilz install alirezarezvani/claude-code-skill-factory/tech-stack-evaluator --agent geminiFirst time? Install Skilz: pip install skilz
Works with 22+ AI coding assistants
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Extract and copy to ~/.claude/skills/ then restart Claude Desktop
git clone https://github.com/alirezarezvani/claude-code-skill-factorycp -r claude-code-skill-factory/generated-skills/tech-stack-evaluator ~/.claude/skills/Need detailed installation help? Check our platform-specific guides:
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Agentic Skill Details
- Owner
- alirezarezvani (GitHub)
- Repository
- claude-code-skill-factory
- Stars
- 325
- Forks
- 73
- Type
- Technical
- Meta-Domain
- web api
- Primary Domain
- security
- Market Score
- 0
Agent Skill Grade
C Score: 77/100 Click to see breakdown
Score Breakdown
Areas to Improve
- Description needs trigger phrases
- Single-file architecture
- Verbose content repetition
Recommendations
- Address 2 high-severity issues first
- Add trigger phrases to description for discoverability
- Add table of contents for files over 100 lines
Graded: 2026-01-24
Developer Feedback
I just looked at how you're handling tech stack evaluation—there's a solid foundation here, but I'm noticing some architectural decisions are holding back what could be a really useful skill. What made you choose to pack everything into a single 430-line file?
Links:
The TL;DR
You're at 77/100, which is solid C-grade territory. This is graded against Anthropic's skill architecture best practices—specifically around token efficiency, layered structure, and spec compliance. Your strongest area is Utility (16/20)—the framework itself is genuinely comprehensive with TCO analysis and security assessment built in. The weakest is Spec Compliance (11/15), mainly because the description lacks trigger phrases that help users discover and activate your skill.
What's Working Well
- Comprehensive evaluation framework: Your skill actually addresses a real gap. The multi-factor analysis (TCO, security, migration paths, team skill matching) is exactly what teams need when making stack decisions.
- Clear output structure: You've thoughtfully designed five different report formats (Executive Summary, Detailed Analysis, Comparison Matrix, etc.), which shows you understand different user needs.
- Good practical constraints: The skill boundaries are explicit—you handle "current popular stacks" and acknowledge limitations around bleeding-edge tech, which is honest and helpful.
- Solid examples: Your input examples show real scenarios (comparing React vs Vue, migrations from Angular), making it discoverable and immediately useful.
The Big One: Architecture is Fighting You
Your single-file design is the core issue. Everything—metrics calculations, best practices, ...
AI-Detected Topics
Extracted using NLP analysis
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