Audit Interfaces with UX/UI Principles
Five agent skills that evaluate interfaces against 168 research-backed UX/UI principles and detect antipatterns.
Why it matters
Evaluate interfaces against 168 research-backed UX/UI principles and detect antipatterns. Inject UX context into AI-assisted design and coding sessions.
Outcomes
What it gets done
Evaluate interface descriptions against 168 research-backed principles
Detect UX antipatterns using the uxuiprinciples smell taxonomy
Audit AI-powered interfaces against 44 AI-era UX principles
Inject UX context into vibe coding sessions before implementation
Install
Add it to your toolbox
Run in your project directory:
curl -fsSL https://spark.entire.vc/get/ag-uxui-principles | bash Overview
UX/UI Principles
Five agent skills for evaluating interfaces against 168 research-backed UX/UI principles, detecting antipatterns, auditing AI-powered interfaces against AI-era principles, checking user flows, and injecting UX context before implementation. Use to audit an existing interface, check research-backed best-practice compliance, detect UX smells, review an AI-powered interface for trust and safety, or get UX guidance before implementation.
What it does
This is a collection of 5 agent skills for evaluating interfaces against 168 research-backed UX/UI principles, detecting antipatterns, and injecting UX context into AI-assisted design and coding sessions: uxui-evaluator evaluates interface descriptions against the full 168-principle set; interface-auditor detects UX antipatterns using the uxuiprinciples smell taxonomy; ai-interface-reviewer audits AI-powered interfaces specifically against 44 AI-era UX principles; flow-checker checks user flows against decision, error, and feedback principles; and vibe-coding-advisor injects UX context into a vibe-coding session before implementation begins.
To use any skill in the collection, you install it, describe the interface, screen, or flow to evaluate, and the skill returns structured findings with severity levels and remediation steps. Output can optionally be enriched by connecting to the uxuiprinciples.com API for full citations behind each finding.
When to use - and when NOT to
Use this collection when auditing an existing interface for UX issues, checking whether a UI follows research-backed best practices, detecting antipatterns or UX smells in a design, reviewing an AI-powered interface for trust, transparency, and safety, or getting UX guidance before or during implementation. It is not a general design tool - each skill evaluates against a fixed, named principle set via the uxuiprinciples smell taxonomy rather than offering open-ended design advice, and the collection is tagged for the design category with source authorship credited to uxuiprinciples (per its author field) rather than a generic community listing.
Inputs and outputs
Input: a description of the interface, screen, or flow to evaluate, plus the specific skill chosen for the task (general evaluation, antipattern detection, AI-interface review, flow checking, or pre-implementation UX context). Output: structured findings with severity levels and remediation steps, optionally enriched with citations via the uxuiprinciples.com API.
Integrations
Installed via:
npx skills add uxuiprinciples/agent-skills
Works with Claude, Cursor, and Windsurf, and optionally connects to the uxuiprinciples.com API for citation-enriched output.
Who it's for
Designers and developers who want UX evaluation grounded in a named, research-backed principle set - rather than subjective review - built into their AI coding session, including teams specifically reviewing AI-powered interfaces for trust and safety concerns.
FAQ
Common questions
Discussion
Questions & comments · 0
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