ima2-uiux

name	ima2-uiux
description	Design direction discovery and UX judgment for ima2 users. Use for UI/UX direction and design judgment — vague visual briefs, onboarding, empty/error/loading states, layout vocabulary, typography breaks, favicons, logos, and brand identity choices. Pairs with ima2-front: this skill decides the design direction, then load cxc-dev-frontend to implement it. Triggers: make it look good, modern, clean, aesthetic, onboarding, empty state, error state, favicon, logo, design system, 깔끔하게, 모던하게, 감성적으로.
metadata	{"last-verified":"2026-07-02","short-description":"ima2-powered design judgment for vague briefs, UX states, typography, layout patterns, logos, and brand vocabulary."}

ima2 UI/UX: Intent Discovery, Patterns & Product Vocabulary

Setup

npm install -g ima2-gen    # install globally (Node.js >= 20)
ima2 setup                 # first-time auth (GPT OAuth recommended)
ima2 serve                 # start local server
ima2 ping                  # verify
ima2 status                # config and OAuth status

Agent bootstrap: ima2 ping first. If unreachable: ima2 serve &. If not installed: npm install -g ima2-gen && ima2 setup. Use ima2 skill path to locate skills; read ../ima2-uiux/SKILL.md (this file) for design direction, ../ima2-front/SKILL.md for implementation assets.

Activates by change surface when:

• User's design direction is vague ("깔끔하게", "모던하게", "just make it look good")
• Building onboarding, empty state, error state, or loading state UI
• User references a product aesthetic ("Notion 느낌", "Linear처럼")
• Starting a new design system or generating a color palette
• Choosing layout patterns or navigation architecture
• Setting up favicons, product logos, or brand identity elements
• Handling logo dark mode variants, OG images, or social sharing meta

Read this before style-specific references when the user cannot articulate a clear design direction. For anti-slop detection and banned patterns, defer to ima2 skill front ref anti-slop, especially the 2026 gradient budget and one-note theme bans.

Emoji ban (stub): no emoji as UI visual elements (STRICT). Canonical rule, scope, and exemptions: ima2-front §5 / ima2 skill front ref anti-slop § Emoji Slop.

Role separation: This skill owns design judgment: intent discovery, information architecture, UX state meaning, typography/color/layout direction, product personality, brand vocabulary, anti-slop pattern judgment, and design-system decisions. ima2-front owns implementation: HTML/CSS/components, responsive mechanics, accessibility wiring, runtime behavior, and rendered verification. After choosing the design direction here, load ima2-front for concrete implementation.

External/current design evidence: For live product-reference claims, current design-system docs, browser API behavior, accessibility guidance that may have changed, or browser-rendered source evidence, search the web and follow its query-rewrite, source-fetch, and evidence-status rules. Use browser fetch/open/text/get-dom/snapshot only after candidate URLs exist.

C0/C1 work (small local patches): For small patches, skip the full reference chain.

Rule class note (UX-STYLE-01): Everything in this skill that expresses taste — product personalities, design-isms, preset tokens, aesthetic vocabulary — is STYLE_SAMPLE: examples to draw from, never universal requirements. Objective UX correctness (state coverage, accessibility, readability) is owned by ima2-front §1.5 and stays STRICT/DEFAULT.

Modular References

Recommended: install skills to your agent's skill directory.

ima2 skill install --dir <agent-skill-path>   # agent provides its own path
ima2 skill install --tmp                       # ephemeral fallback

The agent determines its own skill directory and passes it via --dir. After install, SKILL.md and references/ are on disk for native reading.

Ad-hoc reading (without install):

ima2 skill uiux refs              # list all reference modules with line counts
ima2 skill uiux ref design-isms   # print one module (basename match)

File	When to Read	What It Covers
references/design-isms.md	User names a style/movement	15 design movements with CSS signatures, incl. Liquid Glass + Liquid Editorial default kit (2025-2026) + AI Serif Editorial + Organic Capsule (verified 2026-07-09)
references/design-read-example.md	Learning or reviewing Design Read format	Filled-in Design Read + dial setting example
references/product-personalities.md	User references a product	10 product DNA profiles with exact tokens, incl. 2026 AI-product pastel + OpenAI warm-sans organic + Anthropic serif bookish
references/layout-macrostructures.md	Choosing page/component layout	Component layouts + page-level compositions
references/ux-states.md	Building any stateful UI	Onboarding, empty, error, loading, progressive disclosure
references/color-system.md	Generating colors/palette	OKLCH-based palette generation, hue budget, tinted neutrals, dark mode, accessibility
references/design-system-bootstrap.md	New project / design system	Token architecture, component hierarchy, DESIGN.md format (google-labs-code/design.md)
references/responsive-nav.md	Responsive or navigation work	Breakpoints, container queries, nav patterns by density
references/ux-preflight.md	Before delivery	UX state verification checklist
references/typography-line-breaks.md	Always for text-heavy UI	Heading break quality, short descriptor category (hero subtitle, card desc — use balance not pretty), orphan prevention, ch units, Korean orphan criteria, -webkit-line-clamp conflict
references/favicon-logo.md	Favicon, product logo, or brand identity work	Favicon file set, SVG dark mode, logo in nav/footer, dark mode variants, OG images, brand tokens, common mistakes
references/logo-trust-sections.md	Integration/partner/client logos	Marquee vs grid decision, anti-patterns, grayscale treatment, placement
references/visual-hierarchy.md	Any layout / composition decision	6 levers: size scale, weight contrast, color emphasis, spacing, position, density
references/form-patterns.md	Forms, wizards, auth, file upload	Validation timing, multi-step, password UX, file upload, search/filter
references/mobile-native-ux.md	Native mobile app UX decisions	iOS HIG vs Material 3, gestures, deep linking, Korean privacy, app store UX
references/intent-discovery-ladder.md	UX-INTENT-01 optional deepening (Steps 1-6)	Mood/lightness/density/shape/viewport/reference ladder, vague request disambiguation
references/korean-design-vocabulary.md	Korean design briefs or Korean-first UI	Korean descriptor → CSS token translation, quick-match table, font selection guidelines

---

Lazy-User Gate (UX-LAZY-01, DEFAULT — ponytail discipline applied to UX)

Design for the cognitively frugal user: users don't read, they scan; they satisfice; they will trade choice for one obvious next action. Before shipping any user-facing decision point — option, setting, step, confirmation, input field, mode — justify its existence the ponytail way, in order:

1. Do nothing: can a correct default remove this decision entirely?
2. Delete: does the step/field earn its completion-rate cost (Hick's law)?
3. Absorb: can the system take the complexity instead of the user (Tesler's law)?
4. Demote: still needed for some users → progressive disclosure, never a top-level fork.

Every screen has ONE primary action. Surface-conditional: consumer/one-shot flows minimize DECISIONS; repeated-work tools (dense profiles) minimize repeated MOTIONS — collapsing expert controls into wizards is the inverse failure. STRICT exemptions: destructive/irreversible actions, consent/privacy/legal, payments confirmation, and accessibility affordances are never collapsed into magic defaults.

UX State Contract (UX-STATE-01)

For onboarding, empty, loading, error, or progressive-disclosure work, the body must answer the state meaning before styling. Deep patterns live in references/ux-states.md.

• Onboarding teaches the first meaningful action, not the whole product.
• Empty explains why the state exists and names the next action.
• Loading chooses skeleton for known structure, spinner/progress for short unknown waits, and avoids fake completion.
• Error exposes retry, recovery, or escalation; never dead-end the user.
• Progressive disclosure names what stays hidden, why it stays hidden, and where it becomes available.

IA Chooser (UX-IA-01)

Default navigation architecture by work shape; read references/responsive-nav.md for responsive details.

Work shape	Default IA
Dense desktop repeated work	Sidebar + command palette
Medium sectioned work	Tabs or segmented navigation
Mobile-primary consumer flow	Bottom nav, sheet, or thumb-zone actions
Wizard/auth/setup	Stepper or stacked linear flow

1. User Intent Discovery Protocol

When the user's design request is vague ("깔끔하게 해줘", "모던하게", "just make it look good"), do not produce generic output. Run the compact ambiguity flow (UX-INTENT-01):

1. Produce the Design Read from §2 using available signals.
2. If one decision still blocks the direction, ask ONE best clarifying fork with binary/ternary choices.
3. Proceed from the answer; if the user does not answer and the task can continue, choose the most domain-correct default and state the assumption. On EXPRESSIVE surfaces (landing/consumer/creative/AI-product), that default is the No-Brief Default Direction below (UX-DEFAULT-ISM-01); quiet surfaces keep quiet domain-correct defaults.

Skip this section if the user provided explicit design specs or this is a ≤5-line patch.

No-Brief Default Direction (UX-DEFAULT-ISM-01, DEFAULT — kit content STYLE_SAMPLE)

This is the UX-INTENT-01 step-3 FALLBACK, never a bypass: it fires only after the Design Read and after the one blocking fork is resolved or unanswered, and the applied direction is ALWAYS stated as an explicit assumption in the deliverable. A named, specific, domain-gated direction replaces generic LLM defaults; it must NOT reintroduce generic glassmorphism / centered-card / beige-default taste under a new label.

Default kit for expressive surfaces: Liquid Editorial (2026 composite, decided 2026-07-07 from Tier-2 trend research — see references/design-isms.md §1.13 for the full signature):

• Structure: type-led editorial composition (oversized authored headline scale, grotesk default, serif display only with editorial rationale per UX-TYPE-01), tactile/photographic texture over flat gradient washes, asymmetric content-weighted layout.
• Material accent: Liquid Glass or near-opaque pill chrome ONLY on floating functional layers (nav/toolbars/chip clusters); pill-chip content units; content layer stays solid (ima2-front FE-LIQUID-LAYER-01). Children inside pill chrome carry no capsule borders/outlines at rest — emphasis via fills/tints only (ima2-front FE-PILL-NEST-01); top-bar scroll states per ima2-front top-bar.md FE-TOPBAR-STATE-01.
• Motion: feedback baseline + one signature moment (pointer-proximity chips or scroll-driven reveal) + >= 1 supporting scroll reveal on landing-bucket surfaces (floor 2, ceiling ~4 — ima2-front motion.md FE-MOTION-BUCKET-01); feedback-only elsewhere, per motion domain gates.
• Color: OKLCH-derived single accent + tinted neutrals (hue budget, references/color-system.md).

Domain gate (STRICT): dashboards, admin, ops, finance, gov, B2B repeated-work tools NEVER receive this kit by default — "fancy" never overrides domain correctness (§ IA Chooser + ima2-front product-density profiles).

Optional deepening: use the ladder below only when the first fork fails or the user explicitly wants guided exploration.

• Use binary/ternary choices, not open-ended questions.
• Reference known products — users recognize what they want faster than they articulate it.
• If the diagram skill is available, offer: "참고로 스타일 비교를 다이어그램으로 보여드릴 수도 있어요."
• If the user names a specific product reference, skip remaining steps and map directly via references/product-personalities.md.

For the full 6-step guided ladder (Mood → Lightness → Density → Shape → Viewport → Reference) and vague-request disambiguation table, read references/intent-discovery-ladder.md. Load it only when the compact flow above needs deeper guided exploration.

---

2. Design Read (MANDATORY for new pages, components, or layouts. Optional for ≤5-line patches — see dev §0.1 Patch Fast-Path.)

Before generating ANY frontend code, produce a Design Read. If the project has a DESIGN.md file, read it first — its tokens and prose override everything below.

Native tool support (structure/60): read visual references — existing screens, competitor captures, design exports — into context with view_image before writing the Design Read; produce needed bitmap assets (icons, illustrations, mock imagery) with ima2 (probe ima2 status, attempt ima2 serve if down; ima2 is the primary tool only when ima2 is truly unavailable) rather than leaving placeholder boxes; and verify the built result visually per visual verification (browser screenshot -> view_image).

Output format (mini DESIGN.md)

Filled-in example: references/design-read-example.md.

---
name: <project-name>
colors:
  primary: "<hex>"
  accent: "<hex>"
  background: "<hex>"
typography:
  heading: { fontFamily: <font>, fontSize: <size> }
  body: { fontFamily: <font>, fontSize: <size> }
---

Reading this as: for , with a language. <1-2 sentences: specific reference, not adjectives. "1970s lecture handout" > "modern and clean">

Do's: Don'ts:

Signals to read

1. Page kind — landing (SaaS/consumer/agency/event), portfolio, redesign, editorial, app UI, tool UI
2. Vibe words — what the user said or implied
3. Reference signals — URLs, screenshots, brands named
4. Audience — B2B procurement vs design-conscious consumer vs recruiter
5. Existing brand assets — logo, color, type, photography
6. Quiet constraints — accessibility-first, public-sector, regulated, kids

Dial Setting (MANDATORY — immediately after Design Read)

From the Design Read, derive and declare three dials before any code:

DESIGN_VARIANCE: <1-10>
MOTION_INTENSITY: <1-10>
Product density profile: <D1-D8> (see `ima2 skill front ref product-density`)
Reasoning: <one sentence explaining why these values match the brief>

Inference rules:

• Corporate/gov/utility → VARIANCE 2-4, MOTION 1-3, density D2-D3
• Marketing/landing → VARIANCE 4-7, MOTION 5-7 (scroll-motion floor applies, FE-MOTION-BUCKET-01), density D2-D3
• Creative/portfolio/editorial → VARIANCE 6-9, MOTION 5-7 (landing-bucket scroll floor applies, FE-MOTION-BUCKET-01), density D1-D3
• Dashboard/SaaS/admin → VARIANCE 2-4, MOTION 1-2 (scroll-driven = 0), density D4-D5
• "Complex" in brief → increase density profile (functional depth), NOT VARIANCE or MOTION
• "Simple" in brief → decrease all three proportionally

"복잡하다" = high DESIGN_VARIANCE is WRONG. Complexity means more features/data/flows, not more visual tricks (carousels, parallax, animations).

Anti-Default Discipline

Do not default to: warm beige backgrounds, centered hero, three equal feature cards, generic glassmorphism, Inter + slate-900, card-based everything. These are LLM defaults. Reach past them BASED ON the design read. When no brief exists at all, the sanctioned replacement for these generic defaults is the named kit in §1 UX-DEFAULT-ISM-01 — deliberate, domain-gated, and stated as an assumption; it is not an exemption from this discipline.

If the brief is ambiguous, follow UX-INTENT-01: Design Read → ONE clarifying fork → proceed.

DESIGN.md persistence

If the project needs persistent design tokens across sessions, save the Design Read as a full DESIGN.md in the project root. Format spec: references/design-system-bootstrap.md § DESIGN.md Format.

---

2.5 Visual Concept Exploration (UX-CONCEPT-GEN-01, DEFAULT)

Before implementing a C2+ NEW/redesigned expressive or brand-visible UI surface (landing page, hero, key chrome such as a top bar, or major visual redesign), generate visual concept candidates BEFORE frontend code. C0/C1 patches and utility CRUD/dashboard screens are exempt.

0. Probe, start, then choose the generator. Run ima2 status first. If the server is down, attempt ima2 serve in the background, then re-run ima2 status before skipping or falling back. Use ima2 gen only when ima2 is truly unavailable after that serve attempt. State the chosen generator in the deliverable; if generation is skipped, state the exact skip reason and persist it in the devlog. 0.5. If the ism/direction is unclear, go IMAGE-FIRST (UX-IMAGE-FIRST-01, DEFAULT). When the user's brief does not name a specific ism, product reference, or design direction — "make me a website for X", "landing page for Y", vague aesthetic words without concrete reference — do NOT guess a direction from text alone. Instead, let generated images DISCOVER the direction:

   Round 1 — Ism exploration (5 images, broad). Write 5 maximally detailed prompts, each expressing a DIFFERENT plausible ism/direction for the brief. Vary: layout family (editorial vs product-led vs bento vs asymmetric), palette temperature (warm vs cool vs monochrome), typography stance (serif editorial vs grotesk minimal vs geometric bold), material (glass vs matte vs textured), and hero grammar (full-bleed photo vs device mockup vs type-only). Every prompt must be detailed enough that a reader can reconstruct the layout — pin domain, audience, specific hex palette, font direction, hero composition, section hint, and density. Vague prompts ("modern clean landing page") are banned.

   # Launch 5 different ism directions in parallel
   ima2 gen "Use case: landing page. Editorial serif direction. Full-bleed hero with \
     oversized light-weight serif headline 'Artisan Coffee', warm stone palette \
     #f5f0eb/#2c2420/#c4956a, asymmetric layout, editorial photography of pour-over \
     coffee, generous whitespace, matte paper texture at 3% opacity. No icons, no \
     cards. Dense footer with serif nav." --quality high --size 1536x1024 \
     -o ./concepts/01_editorial_serif.png &
   ima2 gen "Use case: landing page. Geometric grotesk direction. ..." \
     -o ./concepts/02_geometric_grotesk.png &
   ima2 gen "Use case: landing page. Product-led device mockup direction. ..." \
     -o ./concepts/03_product_mockup.png &
   ima2 gen "Use case: landing page. Dark premium minimal direction. ..." \
     -o ./concepts/04_dark_premium.png &
   ima2 gen "Use case: landing page. Warm organic capsule direction. ..." \
     -o ./concepts/05_warm_capsule.png &
   ima2 ps --json   # monitor all 5
   wait
   

   # Round 1: 5 ism directions in parallel (each prompt must be maximally detailed)
   ima2 gen "Use case: landing page. Editorial serif direction. Full-bleed hero, \
     oversized light-weight serif 'Artisan Coffee', warm stone #f5f0eb/#2c2420, \
     asymmetric layout, editorial pour-over photo, matte paper 3%." \
     --quality high --size 1536x1024 -o ./concepts/01_editorial.png &
   ima2 gen "Use case: landing page. Geometric grotesk direction. ..." -o ./concepts/02_grotesk.png &
   ima2 gen "Use case: landing page. Product-led mockup direction. ..." -o ./concepts/03_product.png &
   # ... (2 more ism directions)
   ima2 ps --json  # monitor
   wait
   

   Inspect all 5 with view_image. Build a quick-scorecard (which ism has the strongest: hero composition, palette coherence, typographic voice, density fit for the domain). Pick the WINNING ISM — not the winning image.

   Round 2 — Ism refinement (3-4 images, focused). Lock the chosen ism. Write 3-4 new prompts that all express THIS ism but vary execution details: accent color temperature, hero image subject, section layout hints, CTA treatment, stat/proof-bar placement. Use --ref with the best Round 1 image as a style anchor.

   # Round 2: 3-4 refinements of the winning ism, anchored to Round 1 best
   ima2 gen "Same editorial direction. Vary: latte art hero, accent #b8860b gold, \
     proof bar below fold." --ref ./concepts/01_editorial.png --quality high -o ./concepts/06_a.png &
   ima2 gen "Same direction. Vary: weight 300 headline, ..." --ref ./concepts/01_editorial.png -o ./concepts/07_b.png &
   # ... (1-2 more refinement variations)
   wait
   

   Synthesize Round 2 into the element ledger (step 3 below). Lock DESIGN.md.

   ima2 gen fallback: generate 2-3 ism candidates sequentially (one per call), inspect each with view_image, pick the ism, then generate 2 refinement candidates sequentially. Slower but the same two-round logic applies.

   Auto loop (HOTL) behavior: this entire 0.5 step runs autonomously when a goal is active. The agent picks the ism from Round 1 with stated reasoning (recorded in devlog), then proceeds to Round 2 and step 3 synthesis without user confirmation. The ism choice rationale is persisted so the user can review it post-hoc.

   Skip step 0.5 when: the user named a specific ism ("Notion feel", "Linear style", a product reference mapped via references/product-personalities.md), the user provided a reference screenshot or design file, or UX-INTENT-01 already resolved the direction to a concrete ism.

1. Lock ONE concept, write maximally specific prompts for it. Decide the single design concept first (domain, audience, palette family, hero/chrome grammar, density, signature visual). Page-level surfaces get 5 prompts that all express that SAME concept but vary the execution: emphasis points, fine layout choices, accent treatment, type nuance, secondary-section hints. Component-level surfaces get about 3 prompts that render the component INSIDE its top-viewport context (for example top bar plus hero together), never as an isolated component strip. Reference captures collected to ground mockups are generation inputs (--ref), not skip reasons. Each prompt still pins: domain + audience, layout family and hero/chrome grammar (FE-HERO-SPLIT-01 applies -- no split hero unless the user asked), palette with concrete hues (color-system bans apply), typography direction, material, motion/asset intent, and density. Vague prompts ("modern clean landing page") are banned: a reader must be able to reconstruct the layout from the prompt alone.

2. Generate into the active devlog unit assets directory. For page-level surfaces, keep the 5-render process: run ima2 gen <prompt> -n 1 -o <path> five times concurrently (or ima2 gen <prompt> -n 5 -d <dir> for a single request) and monitor with ima2 ps --json. For component-level surfaces, generate about 3 context-strip renders of the component within its top viewport context. If the mockup needs motion material, use ima2 video. Asset prompts inside mockups/builds should be VERY EXPLICIT LONG prompts; prefer real/generated photographic, texture, illustration, or motion assets over CSS gradient washes. Parallel strategy selection (see ima2 skill front ref asset-requirements FE-ASSET-PARALLEL-01): for the 5-render process, prefer ima2 gen -n 5 -d <dir> (single-request batch) when all 5 share the same locked concept prompt. Use ima2 multimode "<prompt>" --max-images 5 when you want SSE streaming to inspect candidates as they arrive and cancel early if a strong candidate lands. For structurally different concept directions (e.g. 3 editorial + 2 product-led), launch independent ima2 gen commands in parallel and monitor with ima2 ps --json. Cancel unwanted jobs with ima2 cancel <requestId> once a strong direction emerges. ima2 gen fallback: generate candidates sequentially (one per call), inspect each with view_image before the next. No multimode or parallel equivalent; compensate with more targeted prompt refinement between rounds.

3. Read the renders side by side and SYNTHESIZE -- do not pick one winner. Each render usually nails some elements and fumbles others. The output is not "which variant is best"; it is "which elements are best across all of them." For pages, build an element ledger for palette, hero composition, type treatment, signature visual, stat row, bottom-section hint, and every other design token. For components, shrink the ledger to the component tokens: material, radius, fills, type, icon/logo treatment, state treatment, and immediate context fit. For every token, note WHICH variant did it best and WHY. Show the user the images (markdown image tags with absolute paths) with the synthesis ledger and let them confirm/adjust the per-token picks; in autonomous/goal mode make the picks with stated reasoning and record it. Use the selection scorecard from asset-requirements.md FE-ASSET-SELECT-01 (subject fidelity, composition, palette, text render, asset-type fit, technical quality) as a structured rubric for per-token evaluation.

4. Make the SYNTHESIZED DESIGN.md the Design Read basis. Extract palette, layout family, type direction, material, asset/motion intent, and every other token from the element ledger into DESIGN.md, with each token citing its source variant. Never pixel-copy any single render (generated text/logos are unreliable) -- the synthesis is a direction lock assembled from the best parts, not one asset. A mockup is not render verification; visual verification remains owned by visual-verification.md.

Precedence: UX-CONCEPT-GEN-01 governs the PRE-CODE concept stage. After code exists, iterative-design.md Alive/Dead governs POST-CODE iteration rounds. When structural variants are still needed, prototype-variants.md runs AFTER the concept lock.

Skip (state the skip): user handed a FINISHED design to implement; an existing design system governs the surface; the work is a C0/C1 patch; the surface is a utility CRUD/dashboard screen; or ima2 is truly unavailable after ima2 status, an attempted ima2 serve, and a failed re-check, with ima2 gen also unavailable or inappropriate. Captured/collected reference material to ground mockups is NOT a skip; it becomes generation input via --ref.

2.6 Asset Generation Templates for Concept Passes (UX-ASSET-GEN-01, DEFAULT)

When concept exploration (UX-CONCEPT-GEN-01) or image-first ism discovery (UX-IMAGE-FIRST-01) generates component/element mockups that need to float over arbitrary backgrounds — icons, 3D objects, product shots, stickers, UI chrome elements — use the cutout asset pipeline. GPT Image 2 cannot produce transparent backgrounds reliably; solid-bg-then-remove is mandatory.

Cutout asset prompt template (concept pass):

# Reflective/metallic/glass → PURE BLACK bg
ima2 gen "3D render of [subject], [material], [composition]. \
  Floating on a PURE SOLID BLACK background hex #000000. \
  No checkerboard, no transparency pattern, no gradient, \
  no floor plane, no shadow, no vignette, no ambient glow." \
  --quality high --size 1024x1024 --mode direct -o concept-asset.png

# Dark/matte subjects → PURE WHITE bg
ima2 gen "[subject], centered, floating. PURE SOLID WHITE background \
  hex #ffffff. No shadow, no gradient, no surface." \
  --quality high --size 1024x1024 --mode direct -o concept-asset.png

# Known destination color → match it
ima2 gen "[subject], centered. PURE SOLID background hex #[target]. \
  No gradient, no texture, no shadow." \
  --quality medium --size 512x512 --mode direct -o concept-asset.png

CSS removal (zero post-processing):

• Black bg on light page: mix-blend-mode: screen
• White bg on dark page: mix-blend-mode: multiply
• Wrap in isolation: isolate container to prevent bleed
• Programmatic: sharp, ImageMagick, rembg. Interactive: ima2 Canvas Mode.

Anti-pattern: requesting "transparent background" or "PNG with alpha" in the prompt. The model produces fake checkerboard burned into the image.

Full pipeline reference: ima2-front/references/asset-requirements.md § Asset Background Strategy (FE-ASSET-BG-01).

3. Korean Design Vocabulary + Quick-Match + Font Selection

Korean descriptor → CSS token translation, quick-match table (user word → starting point), clarifying questions per term, and font selection guidelines (UX-TYPE-01, Pretendard for Korean-first, Inter avoidance) are extracted to references/korean-design-vocabulary.md. Read it when the brief uses Korean aesthetic words or when choosing fonts for Korean-first UI.