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Tech Stack Evaluator

Checked
questnova502·vlatest·other

This skill analyzes project code to assess its tech stack, revealing dependencies and potential issues for improved maintenance & modernization.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add questnova502/claude-skills-sync --skill tech-stack-evaluator -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

questnova502

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned questnova502/claude-skills-sync at 49910faa5e.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
49910faa5e
Manifest
skills/tech-stack-evaluator/SKILL.md
Scanned
15 files, 4,640 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The tech-stack-evaluator skill analyzes a given technology stack and provides a structured evaluation. It assesses the suitability of technologies for specific project requirements, identifying potential strengths, weaknesses, and alternative options. This includes evaluating factors like cost, scalability, security, and developer familiarity.

When to use it

  • Project Planning: Determine the best combination of tools and frameworks for a new software development project.
  • Technology Migration: Evaluate existing technology choices and identify potential improvements or replacements.
  • Architecture Review: Assess the alignment of current technologies with business goals and technical constraints.
  • Vendor Selection: Compare different vendors offering similar solutions based on their underlying technology stacks.

Key capabilities

  • Stack analysis
  • Suitability assessment
  • Identification of strengths and weaknesses
  • Alternative option suggestions
  • Structured evaluation reports

Example prompts

  • "Evaluate the tech stack: React, Node.js, PostgreSQL for a social media application."
  • "Assess the suitability of AWS Lambda, DynamoDB, and API Gateway for a real-time analytics dashboard."
  • "Compare the pros and cons of using Python vs. Java for machine learning projects."

Tips & gotchas

The quality of the evaluation depends heavily on the clarity and completeness of the provided technology stack description. Be specific about versions and intended use cases to get more accurate results.