tech-stack-evaluator

579 stars 112 forks
0
C

Comprehensive technology stack evaluation and comparison tool with TCO analysis, security assessment, and intelligent recommendations for engineering teams

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#claude-ai#scoring#security#claudecode-subagents#claude-ai-skills#TCO analysis#analysis#claude-skills

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

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skilz install alirezarezvani/claude-skills/tech-stack-evaluator
skilz install alirezarezvani/claude-skills/tech-stack-evaluator --agent opencode
skilz install alirezarezvani/claude-skills/tech-stack-evaluator --agent codex
skilz install alirezarezvani/claude-skills/tech-stack-evaluator --agent gemini

First time? Install Skilz: pip install skilz

Works with 22+ AI coding assistants

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Download Agent Skill ZIP

Extract and copy to ~/.claude/skills/ then restart Claude Desktop

1. Clone the repository:
git clone https://github.com/alirezarezvani/claude-skills
2. Copy the agent skill directory:
cp -r claude-skills/engineering-team/tech-stack-evaluator ~/.claude/skills/

Need detailed installation help? Check our platform-specific guides:

Related Agentic Skills

Agentic Skill Details

Repository
claude-skills
Stars
579
Forks
112
Type
Other
Meta-Domain
Primary Domain
Market Score
0

Agent Skill Grade

C
Score: 76/100 Click to see breakdown

Score Breakdown

Spec Compliance
11/15
PDA Architecture
18/30
Ease of Use
19/25
Writing Style
6/10
Utility
16/20
Modifiers: +6

Areas to Improve

  • Description needs trigger phrases
  • Missing References Architecture
  • Missing Table of Contents

Recommendations

  • Address 1 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've been diving into how developers choose their tech stacks, and your skill's approach to systematizing that decision-making really caught my eye—though the grading suggests there's some untapped potential in how you're structuring the guidance.

Links:

The TL;DR

You're at 76/100, solidly C territory. This evaluation is based on Anthropic's Progressive Disclosure Architecture standards—the five pillars that make skills actually useful to developers. Your strongest area is Utility (16/20)—the core capability is genuinely solid. But PDA is your weak point (18/30)—you're cramming 430 lines into one file when you should be layering the complexity.

What's Working Well

  • Comprehensive coverage: You're addressing a real gap. The TCO analysis, security assessment, and migration path evaluation? That's exactly what teams need when evaluating stacks.
  • Clear metadata: Your triggers are specific ("tech stack evaluator", "run tech stack evaluator") and your description paints a picture of what this does. That's better than most.
  • Solid utility design: You've built in weighted criteria and progressive disclosure concepts—users can select analysis sections rather than getting dumped on with everything. That's thoughtful.
  • Structured sections: The progression from Use Cases through Output Formats feels logical. Navigation isn't broken, it's just... dense.

The Big One: Your Architecture is Upside Down

Here's the thing: all 430 lines live in one SKILL.md file. That's the killer for PDA. You should have:

  • SKILL.md: Lightweight entry point (~80 lines max)
  • references/metrics.md: All your metric calculations (currently ~180 lines of repetitive detail)
  • **references/exa...

AI-Detected Topics

Extracted using NLP analysis

claude-ai scoring security claudecode-subagents claude-ai-skills TCO analysis analysis claude-skills claude-code migration

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