Agent Skills: UI/UX Pro Max - Design Intelligence

Codex compatibility note:

• Invoke repository skills with $skill-name in Codex; this mirrored copy rewrites legacy Claude /skill-name references.
• Prefer the plan-hard skill for planning guidance in this Codex mirror.
• Task tracker mandate: BEFORE executing any workflow or skill step, create/update task tracking for all steps and keep it synchronized as progress changes.
• User-question prompts mean to ask the user directly in Codex.
• Ignore Claude-specific mode-switch instructions when they appear.
• Strict execution contract: when a user explicitly invokes a skill, execute that skill protocol as written.
• Subagent authorization: when a skill is user-invoked or AI-detected and its protocol requires subagents, that skill activation authorizes use of the required spawn_agent subagent(s) for that task.
• Do not skip, reorder, or merge protocol steps unless the user explicitly approves the deviation first.
• For workflow skills, execute each listed child-skill step explicitly and report step-by-step evidence.
• If a required step/tool cannot run in this environment, stop and ask the user before adapting.

Codex Project-Reference Loading (No Hooks)

Codex does not receive Claude hook-based doc injection. When coding, planning, debugging, testing, or reviewing, open project docs explicitly using this routing.

Always read:

• docs/project-config.json (project-specific paths, commands, modules, and workflow/test settings)
• docs/project-reference/docs-index-reference.md (routes to the full docs/project-reference/* catalog)
• docs/project-reference/lessons.md (always-on guardrails and anti-patterns)

Situation-based docs:

• Backend/CQRS/API/domain/entity changes: backend-patterns-reference.md, domain-entities-reference.md, project-structure-reference.md
• Frontend/UI/styling/design-system: frontend-patterns-reference.md, scss-styling-guide.md, design-system/README.md
• Spec/test-case planning or TC mapping: feature-docs-reference.md
• Integration test implementation/review: integration-test-reference.md
• E2E test implementation/review: e2e-test-reference.md
• Code review/audit work: code-review-rules.md plus domain docs above based on changed files

Do not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.

Quick Summary

Goal: Provide searchable UI/UX design intelligence -- 50 styles, 21 palettes, 50 font pairings, 20 charts, 8 stacks.

Workflow:

1. Analyze — Extract product type, style keywords, industry, and stack from user request
2. Search — Query search.py across domains: product, style, typography, color, landing, chart, UX
3. Stack Guidelines — Get stack-specific best practices (default: html-tailwind)
4. Implement — Synthesize search results into cohesive design and code

Key Rules:

• No emojis as UI icons (use SVG: Heroicons, Lucide, Simple Icons)
• All clickable elements need cursor-pointer and hover feedback
• Light mode text must have 4.5:1 minimum contrast ratio
• Test both light/dark modes and responsive breakpoints before delivery

Pre-read (project design system): When the project has a design system, load designSystem.canonicalDoc + tokenFiles from docs/project-config.json and prefer project tokens/components over the generic style intelligence database.

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

UI/UX Pro Max - Design Intelligence

Searchable database of UI styles, color palettes, font pairings, chart types, product recommendations, UX guidelines, and stack-specific best practices.

Prerequisites

Check if Python is installed:

python3 --version || python --version

If Python is not installed, install it based on user's OS:

macOS:

brew install python3

Ubuntu/Debian:

sudo apt update && sudo apt install python3

Windows:

winget install Python.Python.3.12

How to Use This Skill

When user requests UI/UX work (design, build, create, implement, review, fix, improve), follow this workflow:

Step 1: Analyze User Requirements

Extract key information from user request:

• Product type: SaaS, e-commerce, portfolio, dashboard, landing page, etc.
• Style keywords: minimal, playful, professional, elegant, dark mode, etc.
• Industry: healthcare, fintech, gaming, education, etc.
• Stack: React, Vue, Next.js, or default to html-tailwind

Step 2: Search Relevant Domains

Use search.py multiple times to gather comprehensive information. Search until you have enough context.

python3 .claude/skills/ui-ux-pro-max/scripts/search.py "<keyword>" --domain <domain> [-n <max_results>]

Recommended search order:

1. Product - Get style recommendations for product type
2. Style - Get detailed style guide (colors, effects, frameworks)
3. Typography - Get font pairings with Google Fonts imports
4. Color - Get color palette (Primary, Secondary, CTA, Background, Text, Border)
5. Landing - Get page structure (if landing page)
6. Chart - Get chart recommendations (if dashboard/analytics)
7. UX - Get best practices and anti-patterns
8. Stack - Get stack-specific guidelines (default: html-tailwind)

Step 3: Stack Guidelines (Default: html-tailwind)

If user doesn't specify a stack, default to html-tailwind.

python3 .claude/skills/ui-ux-pro-max/scripts/search.py "<keyword>" --stack html-tailwind

Available stacks: html-tailwind, react, nextjs, vue, svelte, swiftui, react-native, flutter

Search Reference

Available Domains

| Domain | Use For | Example Keywords | | ------------ | ------------------------------------ | -------------------------------------------------------- | | product | Product type recommendations | SaaS, e-commerce, portfolio, healthcare, beauty, service | | style | UI styles, colors, effects | glassmorphism, minimalism, dark mode, brutalism | | typography | Font pairings, Google Fonts | elegant, playful, professional, modern | | color | Color palettes by product type | saas, ecommerce, healthcare, beauty, fintech, service | | landing | Page structure, CTA strategies | hero, hero-centric, testimonial, pricing, social-proof | | chart | Chart types, library recommendations | trend, comparison, timeline, funnel, pie | | ux | Best practices, anti-patterns | animation, accessibility, z-index, loading | | prompt | AI prompts, CSS keywords | (style name) |

Available Stacks

| Stack | Focus | | --------------- | ---------------------------------------------- | | html-tailwind | Tailwind utilities, responsive, a11y (DEFAULT) | | react | State, hooks, performance, patterns | | nextjs | SSR, routing, images, API routes | | vue | Composition API, Pinia, Vue Router | | svelte | Runes, stores, SvelteKit | | swiftui | Views, State, Navigation, Animation | | react-native | Components, Navigation, Lists | | flutter | Widgets, State, Layout, Theming |

Example Workflow

User request: "Làm landing page cho dịch vụ chăm sóc da chuyên nghiệp"

AI should:

# 1. Search product type
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "beauty spa wellness service" --domain product

# 2. Search style (based on industry: beauty, elegant)
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "elegant minimal soft" --domain style

# 3. Search typography
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "elegant luxury" --domain typography

# 4. Search color palette
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "beauty spa wellness" --domain color

# 5. Search landing page structure
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "hero-centric social-proof" --domain landing

# 6. Search UX guidelines
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "animation" --domain ux
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "accessibility" --domain ux

# 7. Search stack guidelines (default: html-tailwind)
python3 .claude/skills/ui-ux-pro-max/scripts/search.py "layout responsive" --stack html-tailwind

Then: Synthesize all search results and implement the design.

Tips for Better Results

1. Be specific with keywords - "healthcare SaaS dashboard" > "app"
2. Search multiple times - Different keywords reveal different insights
3. Combine domains - Style + Typography + Color = Complete design system
4. Always check UX - Search "animation", "z-index", "accessibility" for common issues
5. Use stack flag - Get implementation-specific best practices
6. Iterate - If first search doesn't match, try different keywords

Common Rules for Professional UI

These are frequently overlooked issues that make UI look unprofessional:

Icons & Visual Elements

| Rule | Do | Don't | | -------------------------- | ----------------------------------------------- | -------------------------------------- | | No emoji icons | Use SVG icons (Heroicons, Lucide, Simple Icons) | Use emojis like 🎨 🚀 ⚙️ as UI icons | | Stable hover states | Use color/opacity transitions on hover | Use scale transforms that shift layout | | Correct brand logos | Research official SVG from Simple Icons | Guess or use incorrect logo paths | | Consistent icon sizing | Use fixed viewBox (24x24) with w-6 h-6 | Mix different icon sizes randomly |

Interaction & Cursor

| Rule | Do | Don't | | ---------------------- | ----------------------------------------------------- | -------------------------------------------- | | Cursor pointer | Add cursor-pointer to all clickable/hoverable cards | Leave default cursor on interactive elements | | Hover feedback | Provide visual feedback (color, shadow, border) | No indication element is interactive | | Smooth transitions | Use transition-colors duration-200 | Instant state changes or too slow (>500ms) |

Light/Dark Mode Contrast

| Rule | Do | Don't | | ------------------------- | ----------------------------------- | --------------------------------------- | | Glass card light mode | Use bg-white/80 or higher opacity | Use bg-white/10 (too transparent) | | Text contrast light | Use #0F172A (slate-900) for text | Use #94A3B8 (slate-400) for body text | | Muted text light | Use #475569 (slate-600) minimum | Use gray-400 or lighter | | Border visibility | Use border-gray-200 in light mode | Use border-white/10 (invisible) |

Layout & Spacing

| Rule | Do | Don't | | ------------------------ | ----------------------------------- | -------------------------------------- | | Floating navbar | Add top-4 left-4 right-4 spacing | Stick navbar to top-0 left-0 right-0 | | Content padding | Account for fixed navbar height | Let content hide behind fixed elements | | Consistent max-width | Use same max-w-6xl or max-w-7xl | Mix different container widths |

Pre-Delivery Checklist

Before delivering UI code, verify these items:

Visual Quality

• [ ] No emojis used as icons (use SVG instead)
• [ ] All icons from consistent icon set (Heroicons/Lucide)
• [ ] Brand logos are correct (verified from Simple Icons)
• [ ] Hover states don't cause layout shift

Interaction

• [ ] All clickable elements have cursor-pointer
• [ ] Hover states provide clear visual feedback
• [ ] Transitions are smooth (150-300ms)
• [ ] Focus states visible for keyboard navigation

Light/Dark Mode

• [ ] Light mode text has sufficient contrast (4.5:1 minimum)
• [ ] Glass/transparent elements visible in light mode
• [ ] Borders visible in both modes
• [ ] Test both modes before delivery

Layout

• [ ] Floating elements have proper spacing from edges
• [ ] No content hidden behind fixed navbars
• [ ] Responsive at 320px, 768px, 1024px, 1440px
• [ ] No horizontal scroll on mobile

Accessibility

• [ ] All images have alt text
• [ ] Form inputs have labels
• [ ] Color is not the only indicator
• [ ] prefers-reduced-motion respected

Related

• frontend-design
• interface-design — Product UIs (dashboards, admin panels, SaaS apps)
• shadcn-tailwind
• ux-designer

[IMPORTANT] Use task tracking to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.

AI Mistake Prevention — Failure modes to avoid on every task: Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.

Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.

MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.

MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

Closing Reminders

IMPORTANT MUST ATTENTION break work into small todo tasks using task tracking BEFORE starting IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act) IMPORTANT MUST ATTENTION add a final review todo task to verify work quality

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using task tracking.

Hookless Prompt Protocol Mirror (Auto-Synced)

Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json

[WORKFLOW-EXECUTION-PROTOCOL] [BLOCKING] Workflow Execution Protocol — MANDATORY IMPORTANT MUST CRITICAL. Do not skip for any reason.

1. DETECT: Match prompt against workflow catalog
2. ANALYZE: Find best-match workflow AND evaluate if a custom step combination would fit better
3. ASK (REQUIRED FORMAT): Use a direct user question with this structure:
   • Question: "Which workflow do you want to activate?"
   • Option 1: "Activate [BestMatch Workflow] (Recommended)"
   • Option 2: "Activate custom workflow: [step1 → step2 → ...]" (include one-line rationale)
4. ACTIVATE (if confirmed): Call $workflow-start <workflowId> for standard; sequence custom steps manually
5. CREATE TASKS: task tracking for ALL workflow steps
6. EXECUTE: Follow each step in sequence [CRITICAL-THINKING-MINDSET] Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination principle: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination. AI Attention principle (Primacy-Recency): Put the 3 most critical rules at both top and bottom of long prompts/protocols so instruction adherence survives long context windows.

Learned Lessons

Lessons Learned

[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.

Quick Summary

Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.

Top Rules (apply always):

• MUST ATTENTION verify ALL preconditions (config, env, DB names, DI regs) BEFORE code-layer hypothesis
• MUST ATTENTION fix responsible layer — NEVER patch symptom sites with caller-specific defensive code
• MUST ATTENTION use ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTask
• MUST ATTENTION name by PURPOSE not CONTENT — adding member forces rename = abstraction broken
• MUST ATTENTION persist sub-agent findings incrementally after each file — NEVER batch at end
• MUST ATTENTION Windows bash: verify Python alias (where python/where py) — NEVER assume python/python3 resolves

Debugging & Root Cause Reasoning

• [2026-04-11] Holistic-first: verify environment before code. Failure → list ALL preconditions (config, env vars, DB names, endpoints, DI regs, credentials, permissions, data prerequisites) → verify each via evidence (grep/cat/query) BEFORE code-layer hypothesis. Worst rabbit holes: diving nearest layer while bug sits elsewhere — e.g., hours debugging "sync timeout", real cause: test appsettings pointing wrong DB. ALWAYS cheapest check first.
• [2026-04-01] Ask "whose responsibility?" before fixing. Trace: bug caller (wrong data) or callee (wrong handling)? Fix responsible layer — NEVER patch symptom site masking real issue.
• [2026-04-01] Trace data lifecycle, not error site. Follow data: creation → transformation → consumption. Bug usually where data created wrong, not consumed.
• [2026-04-01] Code caller-agnostic. Functions/handlers/consumers don't know who invokes them. Comments/guards/messages describe business intent — NEVER reference specific callers (tests, seeders, scripts).

Architecture Invariants

• [2026-05-09] User name materialization MUST ATTENTION go through User.UpdateName(firstName, middleName, lastName). Domain method (src/Services/bravoTALENTS/Employee.Domain/AggregatesModel/User.cs:202-209) recomputes FullName as single source of truth. Three sites still manually patch user.FullName = user.GetFullName() after assigning name fields — src/Services/bravoTALENTS/Employee.Application/Factories/UserFactory.cs:50, src/Services/bravoSURVEYS/LearningPlatform.Application/ApplyPlatform/MessageBus/Consumers/AccountUserDeletedEventBusConsumer.cs:102, src/Services/bravoINSIGHTS/Analyze/Analyze.Application/MessageBus/Consumers/AccountUserDeletedEventBusConsumer.cs:66. Next time touching any: replace manual patch with user.UpdateName(...) to maintain invariant.
• [2026-03-31] ParallelAsync + repo/UoW MUST ATTENTION use ExecuteInjectScopedAsync, NEVER ExecuteUowTask. ExecuteUowTask creates new UoW but reuses outer DI scope (same DbContext) — parallel iterations sharing non-thread-safe DbContext silently corrupt data. ExecuteInjectScopedAsync creates new UoW + new DI scope (fresh repo per iteration).
• [2026-03-31] Bus message naming MUST ATTENTION include service name prefix — core services NEVER consume feature events. Prefix declares schema ownership (AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) leaders. Feature services (Growth, Talents) sending to core MUST ATTENTION use {CoreServiceName}...RequestBusMessage — NEVER define own event for core to consume.

Naming & Abstraction

• [2026-04-12] Name PURPOSE not CONTENT — "OrXxx" anti-pattern. HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what guards. Add role → rename = broken abstraction. Rule: names express DOES/GUARDS, not CONTAINS. Test: adding/removing member forces rename? YES = content-driven = bad → rename to purpose (e.g., HrOperationsAccessPolicy). Nuance: "Or" fine behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.

Environment & Tooling

• [2026-04-20] Windows bash: NEVER assume python/python3 resolves — verify alias first. Python may not be bash PATH under those names. Check: where python / where py. ALWAYS prefer py (Windows Python Launcher) one-liners, node if JS alternative exists.

Test-specific lessons → docs/project-reference/integration-test-reference.md Lessons Learned section. Production-code anti-patterns → docs/project-reference/backend-patterns-reference.md Anti-Patterns section. Generic debugging/refactoring reminders → System Lessons .claude/hooks/lib/prompt-injections.cjs.

Closing Reminders

• IMPORTANT MUST ATTENTION holistic-first: verify ALL preconditions (config, env, DB names, endpoints, DI regs) BEFORE code-layer hypothesis — cheapest check first
• IMPORTANT MUST ATTENTION fix responsible layer — NEVER patch symptom site; trace caller (wrong data) vs callee (wrong handling), fix root owner
• IMPORTANT MUST ATTENTION parallel async + repo/UoW → ALWAYS ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption)
• IMPORTANT MUST ATTENTION bus message prefix = schema ownership; feature services NEVER define events for core services — use {CoreServiceName}...RequestBusMessage
• IMPORTANT MUST ATTENTION name by PURPOSE — adding/removing member forces rename = broken abstraction
• IMPORTANT MUST ATTENTION sub-agents MUST write findings after each file/section — NEVER batch all findings into one final write
• IMPORTANT MUST ATTENTION Windows bash: NEVER assume python/python3 resolves — run where python/where py first, use py launcher or node
• IMPORTANT MUST ATTENTION every claim needs file:line evidence — confidence >80% to act, NEVER speculate

[LESSON-LEARNED-REMINDER] [BLOCKING] Task Planning & Continuous Improvement — MANDATORY. Do not skip.

Break work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".

Extract lessons — ROOT CAUSE ONLY, not symptom fixes:

1. Name the FAILURE MODE (reasoning/assumption failure), not symptom — "assumed API existed without reading source" not "used wrong enum value".
2. Generality test: does this failure mode apply to ≥3 contexts/codebases? If not, abstract one level up.
3. Write as a universal rule — strip project-specific names/paths/classes. Useful on any codebase.
4. Consolidate: multiple mistakes sharing one failure mode → ONE lesson.
5. Recurrence gate: "Would this recur in future session WITHOUT this reminder?" — No → skip $learn.
6. Auto-fix gate: "Could $code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead.
7. BOTH gates pass → ask user to run $learn. [TASK-PLANNING] [MANDATORY] BEFORE executing any workflow or skill step, create/update task tracking for all planned steps, then keep it synchronized as each step starts/completes.