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Ux Friction Analyzer

Listed
curiositech·vlatest·frontend·MIT

Identifies UX friction points in digital interfaces using AI to suggest improvements based on user behavior data.

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 curiositech/some_claude_skills --skill ux-friction-analyzer -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

curiositech

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 failed 1 of 6 checks. A failure is not proof of bad intent; it means something in the code needs a human to look at it before you run it.

  • Declares what it does: failed

    No SKILL.md was found in the skill's directory.

    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 curiositech/some_claude_skills at 6713fc7a64.

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

Scanned
0 files
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What each check looks for →

About this skill

What it does

The UX Friction Analyzer skill identifies and quantifies usability issues within a given user interface description. It analyzes text descriptions of UI elements, workflows, or interaction sequences to pinpoint areas where users might experience frustration or difficulty. The tool provides scores indicating the severity of friction points and suggests potential improvements for enhanced user experience.

When to use it

  • Website redesign: Before launching a redesigned website, analyze the new design's description to proactively identify usability issues.
  • Mobile app development: Evaluate descriptions of mobile app flows to ensure intuitive navigation and ease of use.
  • Software onboarding: Assess the clarity and efficiency of software onboarding processes by analyzing their textual representation.
  • Internal tool creation: Before building an internal tool, analyze its intended workflow description to optimize user experience from the start.

Key capabilities

  • Friction score calculation
  • Identification of specific usability issues
  • Suggestion of UX improvements
  • Analysis of UI descriptions (text)

Example prompts

  • "Analyze this website flow: [paste text describing a user journey]"
  • "What are the friction points in this mobile app onboarding sequence? [paste text description]"
  • "Score this internal tool workflow for usability. [paste text description]"

Tips & gotchas

The skill relies on accurate and detailed textual descriptions of the UI or process being analyzed; vague or incomplete descriptions will yield less reliable results. The output is a suggestion, not definitive proof of UX issues - always validate findings with user testing.