Tech Stack Evaluator

Q: Why use Tech Stack Evaluator on TypingMind?

Because you install it once and use it with any model. Tech Stack Evaluator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

Q: How do I install Tech Stack Evaluator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yezannnnn/agentGroup/tree/master/jarvis/skills/engineering-team/tech-stack-evaluator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Q: Which AI models can use Tech Stack Evaluator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

Q: How many AI models can I use with Tech Stack Evaluator?

As many as you like. As long as a model supports skills, you can use Tech Stack Evaluator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Q: Is the Tech Stack Evaluator AI skill free?

Yes. It is published on GitHub by yezannnnn under the MIT license. You only pay your own AI provider for the tokens you use.

Q: What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

Q: How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

Community

yezannnnn

tech-stack-evaluator

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.

Overview

Publisher	yezannnnn
Repository	`agentGroup`
Skill name	`tech-stack-evaluator`
Stars	149
Forks	49
Bundled files	14
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
14 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by yezannnnn on GitHub. Read the source before you install it.

Installation

Install the Tech Stack Evaluator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/yezannnnn/agentGroup/tree/master/jarvis/skills/engineering-team/tech-stack-evaluator

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/yezannnnn/agentGroup.git /tmp/agentGroup
mkdir -p .claude/skills
cp -r /tmp/agentGroup/jarvis/skills/engineering-team/tech-stack-evaluator .claude/skills/tech-stack-evaluator

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tech Stack Evaluator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Tech Stack Evaluator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Tech Stack Evaluator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Technology Stack Evaluator

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

Capabilities
Quick Start
Input Formats
Analysis Types
Scripts
References

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

yaml
comparison:
  technologies: ["React", "Vue"]
  use_case: "SaaS dashboard"
  weights:
    ecosystem: 30
    performance: 25
    developer_experience: 45

JSON - Programmatic integration

json
{
  "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.

bash
python scripts/stack_comparator.py --help

tco_calculator.py

Calculate total cost of ownership over multi-year projections.

bash
python scripts/tco_calculator.py --input assets/sample_input_tco.json

ecosystem_analyzer.py

Analyze ecosystem health from GitHub, npm, and community metrics.

bash
python scripts/ecosystem_analyzer.py --technology react

security_assessor.py

Evaluate security posture and compliance readiness.

bash
python scripts/security_assessor.py --technology express --compliance soc2,gdpr

migration_analyzer.py

Estimate migration complexity, effort, and risks.

bash
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)

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

assets/expected_output_comparison.json2 KB
assets/sample_input_structured.json1 KB
assets/sample_input_tco.json1 KB
assets/sample_input_text.json1 KB
references/examples.md10 KB
references/metrics.md7 KB
references/workflows.md8 KB
scripts/ecosystem_analyzer.py16 KB
scripts/format_detector.py12 KB
scripts/migration_analyzer.py20 KB
scripts/report_generator.py16 KB
scripts/security_assessor.py17 KB
scripts/stack_comparator.py12 KB
scripts/tco_calculator.py16 KB

Frequently asked questions

What does the Tech Stack Evaluator AI skill do?

Why use Tech Stack Evaluator on TypingMind?

Because you install it once and use it with any model. Tech Stack Evaluator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Tech Stack Evaluator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yezannnnn/agentGroup/tree/master/jarvis/skills/engineering-team/tech-stack-evaluator. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Tech Stack Evaluator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Tech Stack Evaluator?

As many as you like. As long as a model supports skills, you can use Tech Stack Evaluator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Tech Stack Evaluator AI skill free?

Yes. It is published on GitHub by yezannnnn under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Tech Stack Evaluator

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Technology Stack Evaluator

Table of Contents

Capabilities

Quick Start

Compare Two Technologies

Calculate TCO

Assess Migration

Input Formats

Analysis Types

Quick Comparison (200-300 tokens)

Standard Analysis (500-800 tokens)

Full Report (1200-1500 tokens)

Scripts

stack_comparator.py

tco_calculator.py

ecosystem_analyzer.py

security_assessor.py

migration_analyzer.py

References

Confidence Levels

When to Use

When NOT to Use

Bundled files

Frequently asked questions

Set up your own AI workspace now

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Technology Stack Evaluator

Table of Contents

Capabilities

Quick Start

Compare Two Technologies

Calculate TCO

Assess Migration

Input Formats

Analysis Types

Quick Comparison (200-300 tokens)

Standard Analysis (500-800 tokens)

Full Report (1200-1500 tokens)

Scripts

stack_comparator.py

tco_calculator.py

ecosystem_analyzer.py

security_assessor.py

migration_analyzer.py

References

Confidence Levels

When to Use

When NOT to Use

Bundled files

Frequently asked questions

Related AI Skills

Set up your own AI workspace now