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Perfect Ux

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lcsxu
perfect-ux

Beta research-backed UX engineering skill for auditing, mapping, improving, and judging product experiences so real users can complete important jobs with clarity, confidence, accessibility, recovery, and measurable friction reduction. Use when Codex works on UX flows, IA, forms, onboarding, dashboards, commerce, AI tools, CRUD, editors, settings, service design, microcopy, accessibility, usability testing, or any interface that must feel effortless instead of merely attractive. Composes with perfect-design, no-slop, and reality-skill.

Overview

Publisherlcsxu
Repositoryzero-slop
Skill nameperfect-ux
Stars
13
Forks
1
Bundled files
23
LicenseApache-2.0
Links
  • 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.

  • 23 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by lcsxu on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/lcsxu/zero-slop/tree/main/skills/perfect-ux
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/lcsxu/zero-slop.git /tmp/zero-slop
mkdir -p .claude/skills
cp -r /tmp/zero-slop/skills/perfect-ux .claude/skills/perfect-ux
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Perfect Ux 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 Perfect Ux 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 Perfect Ux 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.

Perfect UX

Status: beta.

Perfect UX is the user-success layer. perfect-design makes the interface coherent and product-specific; no-slop blocks generic AI residue; reality-skill makes workflows real. Perfect UX asks: can the intended user understand what to do, finish the job, recover from problems, trust the system, and get faster over time?

Command Interface

Use references/command-interface.md.

Primary commands:

bash
perfect-ux --contract [brief-or-target]
perfect-ux --map [brief-or-target]
perfect-ux --audit [target]
perfect-ux --fix [target]
perfect-ux --harden [target]
perfect-ux --judge [target]
perfect-ux --verify [target]
perfect-ux -e --audit [target]

Short flags:

  • -c, --contract: write the UX Contract before code.
  • -m, --map: map jobs, entry points, decisions, states, and recovery paths.
  • -a, --audit: find UX friction, ambiguity, accessibility blockers, trust gaps, and missing evidence.
  • -f, --fix: make the smallest coherent UX improvement pass.
  • --harden: add resilience, edge states, keyboard paths, recovery, and proof.
  • -j, --judge: run the strict UX judge panel.
  • --verify: prove the primary journey with build, tests, browser, accessibility, and task evidence.
  • -e, --economy: disable live subagent judges only when the user explicitly accepts a lower-cost review.

Default mode:

  • Existing UI target: --audit.
  • Editable request on an existing target: --fix.
  • Brief without target: --contract.

First Action

Load steps/step-00-command-router.md.

Step 00 parses command flags, discovers the product surface, resolves UX dials, loads only relevant references, and routes to contract, map, audit, fix, harden, judge, or verify.

Core References

Load only what the task needs:

  • references/command-interface.md: grammar, precedence, output contracts.
  • references/dials-and-presets.md: UX dials, presets, and pass thresholds.
  • references/research-synthesis.md: compressed research from NN/g, W3C/WAI, WCAG, GOV.UK, Apple HIG, Material, Fluent, Baymard, web.dev, design systems, and Human-AI guidance.
  • references/research-source-ledger.md: source map and what each source contributes.
  • references/ux-contract.md: pre-code contract and rejection rules.
  • references/ux-gates.md: the hard UX gates used for audit, fix, harden, and judge.
  • references/journey-playbook.md: jobs, IA, flow mapping, decision paths, onboarding, dashboards, commerce, AI tools, and expert use.
  • references/interaction-playbook.md: controls, forms, feedback, validation, recovery, keyboard, motion, mobile, and performance feel.
  • references/content-and-trust.md: UX writing, labels, claims, AI uncertainty, empty states, errors, consent, and trust boundaries.
  • references/measurement-and-research.md: usability testing, analytics, task metrics, research method choice, and evidence loops.
  • references/ecosystem-contract.md: ownership and composition with sibling skills.
  • references/judge-system.md: judge protocol and gate formula.
  • references/verification-playbook.md: build/browser/accessibility/task verification.
  • references/self-coaching.md: internal checklist for stuck or ambiguous UX decisions.

Non-Negotiables

  • Always write or infer a UX Contract before changing UX.
  • Always identify the primary user, job, start point, completion condition, decision moments, risks, recovery paths, and evidence needed.
  • Inspect existing routes, state, data, forms, controls, labels, errors, focus behavior, analytics hooks, tests, and design-system primitives before editing.
  • Prefer reducing friction over adding explanatory chrome. If users need instructions, first simplify the object, flow, label, layout, or feedback.
  • Do not accept a pretty screen as UX evidence. Use task completion, state coverage, keyboard access, error recovery, performance feel, and trust as gates.
  • Do not hide hard choices behind generic labels like Get started, Submit, Continue, Learn more, or AI powered when the next action or risk can be named.
  • Do not ship dead ends, ambiguous disabled controls, form loss after errors, invisible focus, keyboard traps, unexplained waits, fake progress, fake certainty, or unsupported claims.
  • For AI tools, expose input constraints, model boundaries, sources when available, confidence or uncertainty where appropriate, user control, review/edit paths, and failure recovery.
  • For dashboards, organize around decisions and operational questions, not decorative metrics.
  • For commerce and checkout, prioritize price clarity, availability, shipping, returns, comparison, validation, and trust over persuasion effects.
  • For forms, preserve input, validate near the field, keep focus manageable, explain recovery, and avoid placeholder-only labels.
  • Compose with reality-skill when actions, data, persistence, or integrations must be real. Compose with perfect-design when visual direction changes. Compose with no-slop before and after material UI work.
  • Judge with subagents by default. If live judges are unavailable and economy mode is false, mark JUDGE_PANEL_UNAVAILABLE; never claim a full pass.
  • Iterate until the UX gate passes. If blocked, name the exact blocker and the user harm.

Required State

Maintain this state throughout the workflow:

text
command:
target:
mode:
economy_mode:
preset:
dials:
project_type:
primary_user:
primary_job:
start_point:
completion_condition:
journey_map:
ux_contract:
friction_score_before:
ux_score_before:
blocking_gates:
research_evidence:
files_changed:
implementation_strategy:
judge_panel:
judge_gate:
verification:
ux_score_after:
remaining_risk:
ship_decision:

UX Contract

Before editing, write or infer a compact contract:

text
User:
Context:
Primary job:
Starting point:
Completion condition:
Decision moments:
Inputs required:
System feedback required:
Failure/recovery paths:
Accessibility constraints:
Mobile/responsive constraints:
Performance constraints:
Trust/safety constraints:
Evidence to verify:
Forbidden friction:

Ask the user only when multiple high-impact jobs conflict and a wrong choice would waste the implementation. Otherwise infer conservatively from code and product context.

Local CLI Helper

For deterministic prechecks:

bash
python skills/perfect-ux/scripts/perfect_ux_cli.py --audit <target>
python skills/perfect-ux/scripts/perfect_ux_cli.py --contract "brief text"
python skills/perfect-ux/scripts/perfect_ux_cli.py --json --audit <target>
python skills/perfect-ux/scripts/perfect_ux_cli.py --preset ai-tool --dial ERROR_RECOVERY=10 --audit <target>

The CLI catches common UX risk signals. It is not a replacement for reading code, rendered browser walkthroughs, usability evidence, sibling skills, or live judge panels.

Done Means

  • The primary job can be understood and completed.
  • The path has clear entry, decision, action, feedback, completion, and recovery states.
  • Labels, copy, and IA reveal the system model without filler explanation.
  • Forms and controls are accessible, keyboard-operable, responsive, and resilient to messy input.
  • Important waits, failures, empty states, disabled states, and success states are visible and actionable.
  • Trust-sensitive claims are supported, scoped, disabled, or rewritten honestly.
  • Performance does not create perceptual friction through layout shift, sluggish interaction, or unstable content.
  • Verification ran, or the exact blocker and unverified risk are stated.

Bundled files

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

Frequently asked questions

What does the Perfect Ux AI skill do?

Beta research-backed UX engineering skill for auditing, mapping, improving, and judging product experiences so real users can complete important jobs with clarity, confidence, accessibility, recovery, and measurable friction reduction. Use when Codex works on UX flows, IA, forms, onboarding, dashboards, commerce, AI tools, CRUD, editors, settings, service design, microcopy, accessibility, usability testing, or any interface that must feel effortless instead of merely attractive. Composes with perfect-design, no-slop, and reality-skill.

Why use Perfect Ux on TypingMind?

Because you install it once and use it with any model. Perfect Ux 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 Perfect Ux in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/lcsxu/zero-slop/tree/main/skills/perfect-ux. 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 Perfect Ux?

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 Perfect Ux?

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

Is the Perfect Ux AI skill free?

Yes. It is published on GitHub by lcsxu under the Apache-2.0 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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