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Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications. Generates creative, polished code that avoids generic AI aesthetics. Do NOT use for design review or audit (use web-design-guidelines or web-quality-audit).
| name | frontend-design |
| description | Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, artifacts, posters, or applications. Generates creative, polished code that avoids generic AI aesthetics. Do NOT use for design review or audit (use web-design-guidelines or web-quality-audit). |
| metadata | {"author":"Impeccable (Paul Bakaus), based on Anthropic frontend-design","version":"1.0.0"} |
| source | https://github.com/pbakaus/impeccable |
This skill guides creation of distinctive, production-grade frontend interfaces that avoid generic "AI slop" aesthetics. Implement real working code with exceptional attention to aesthetic details and creative choices.
Commit to a BOLD aesthetic direction:
CRITICAL: Choose a clear conceptual direction and execute it with precision. Bold maximalism and refined minimalism both work—the key is intentionality, not intensity.
Then implement working code that is:
→ Consult typography reference for scales, pairing, and loading strategies.
Choose fonts that are beautiful, unique, and interesting. Pair a distinctive display font with a refined body font.
DO: Use a modular type scale with fluid sizing (clamp) DO: Vary font weights and sizes to create clear visual hierarchy DON'T: Use overused fonts—Inter, Roboto, Arial, Open Sans, system defaults DON'T: Use monospace typography as lazy shorthand for "technical/developer" vibes DON'T: Put large icons with rounded corners above every heading—they rarely add value and make sites look templated
→ Consult color reference for OKLCH, palettes, and dark mode.
Commit to a cohesive palette. Dominant colors with sharp accents outperform timid, evenly-distributed palettes.
DO: Use modern CSS color functions (oklch, color-mix, light-dark) for perceptually uniform, maintainable palettes DO: Tint your neutrals toward your brand hue—even a subtle hint creates subconscious cohesion DON'T: Use gray text on colored backgrounds—it looks washed out; use a shade of the background color instead DON'T: Use pure black (#000) or pure white (#fff)—always tint; pure black/white never appears in nature DON'T: Use the AI color palette: cyan-on-dark, purple-to-blue gradients, neon accents on dark backgrounds DON'T: Use gradient text for "impact"—especially on metrics or headings; it's decorative rather than meaningful DON'T: Default to dark mode with glowing accents—it looks "cool" without requiring actual design decisions
→ Consult spatial reference for grids, rhythm, and container queries.
Create visual rhythm through varied spacing—not the same padding everywhere. Embrace asymmetry and unexpected compositions. Break the grid intentionally for emphasis.
DO: Create visual rhythm through varied spacing—tight groupings, generous separations DO: Use fluid spacing with clamp() that breathes on larger screens DO: Use asymmetry and unexpected compositions; break the grid intentionally for emphasis DON'T: Wrap everything in cards—not everything needs a container DON'T: Nest cards inside cards—visual noise, flatten the hierarchy DON'T: Use identical card grids—same-sized cards with icon + heading + text, repeated endlessly DON'T: Use the hero metric layout template—big number, small label, supporting stats, gradient accent DON'T: Center everything—left-aligned text with asymmetric layouts feels more designed DON'T: Use the same spacing everywhere—without rhythm, layouts feel monotonous
DO: Use intentional, purposeful decorative elements that reinforce brand DON'T: Use glassmorphism everywhere—blur effects, glass cards, glow borders used decoratively rather than purposefully DON'T: Use rounded elements with thick colored border on one side—a lazy accent that almost never looks intentional DON'T: Use sparklines as decoration—tiny charts that look sophisticated but convey nothing meaningful DON'T: Use rounded rectangles with generic drop shadows—safe, forgettable, could be any AI output DON'T: Use modals unless there's truly no better alternative—modals are lazy
→ Consult motion reference for timing, easing, and reduced motion.
Focus on high-impact moments: one well-orchestrated page load with staggered reveals creates more delight than scattered micro-interactions.
DO: Use motion to convey state changes—entrances, exits, feedback DO: Use exponential easing (ease-out-quart/quint/expo) for natural deceleration DO: For height animations, use grid-template-rows transitions instead of animating height directly DON'T: Animate layout properties (width, height, padding, margin)—use transform and opacity only DON'T: Use bounce or elastic easing—they feel dated and tacky; real objects decelerate smoothly
→ Consult interaction reference for forms, focus, and loading patterns.
Make interactions feel fast. Use optimistic UI—update immediately, sync later.
DO: Use progressive disclosure—start simple, reveal sophistication through interaction (basic options first, advanced behind expandable sections; hover states that reveal secondary actions) DO: Design empty states that teach the interface, not just say "nothing here" DO: Make every interactive surface feel intentional and responsive DON'T: Repeat the same information—redundant headers, intros that restate the heading DON'T: Make every button primary—use ghost buttons, text links, secondary styles; hierarchy matters
→ Consult responsive reference for mobile-first, fluid design, and container queries.
DO: Use container queries (@container) for component-level responsiveness DO: Adapt the interface for different contexts—don't just shrink it DON'T: Hide critical functionality on mobile—adapt the interface, don't amputate it
→ Consult ux-writing reference for labels, errors, and empty states.
DO: Make every word earn its place DON'T: Repeat information users can already see
Critical quality check: If you showed this interface to someone and said "AI made this," would they believe you immediately? If yes, that's the problem.
A distinctive interface should make someone ask "how was this made?" not "which AI made this?"
Review the DON'T guidelines above—they are the fingerprints of AI-generated work from 2024-2025.
User says: "Build a landing page for a developer tools product, something that doesn't look like every other SaaS." Actions: Pick a bold direction (e.g. brutalist or editorial); choose a distinctive type pairing and a cohesive palette; implement with fluid spacing and one clear focal point; avoid cards-in-cards and hero-metric clichés. Result: A single-page layout with clear hierarchy, memorable typography, and no generic AI tells (no purple gradients, no rounded cards with thick accent borders).
User says: "Create a dashboard for viewing analytics with a dark theme." Actions: Commit to a specific dark aesthetic (e.g. refined dark with tinted neutrals, not default glow-on-black); use container queries for panels; add one considered motion moment (e.g. staggered list load); ensure empty states are helpful. Result: Functional dashboard that feels intentionally designed—distinct palette, no cyan/purple glow, clear data hierarchy and responsive behavior.
User says: "Make a poster for a conference talk about frontend performance." Actions: Choose a strong typographic or visual concept; use a modular type scale and limited palette; avoid generic stock-photo + headline layout. Result: A poster that could stand alone as a designed artifact—memorable type and composition, not a template fill-in.
Match implementation complexity to the aesthetic vision. Maximalist designs need elaborate code with extensive animations and effects. Minimalist or refined designs need restraint, precision, and careful attention to spacing, typography, and subtle details.
Interpret creatively and make unexpected choices that feel genuinely designed for the context. No design should be the same. Vary between light and dark themes, different fonts, different aesthetics. NEVER converge on common choices across generations.
Remember: the AI is capable of extraordinary creative work. Don't hold back—show what can truly be created when thinking outside the box and committing fully to a distinctive vision.
Apply modern web development best practices for security, compatibility, and code quality. Use when asked to "apply best practices", "security audit", "modernize code", "code quality review", or "check for vulnerabilities". Do NOT use for accessibility (use web-accessibility), SEO (use seo), performance (use core-web-vitals), or comprehensive multi-area audits (use web-quality-audit).
Detects anemic domain models, validates and refactors them into rich domain models, and enforces tactical DDD patterns (Entities, Value Objects, Aggregates, Domain Services, Domain Events). Use when the user asks to validate, review, or check domain models or DDD code; detect anemia; refactor domain objects; improve encapsulation; or mentions terms like "anemic model", "rich domain", "aggregate", "value object", "domain event", "ubiquitous language", "is this good DDD", "does this follow DDD", or "check my domain". Do NOT use for module or service boundary design, architectural decomposition, strategic DDD context mapping, or code outside the domain layer (DTOs, controllers, infrastructure adapters).
Runs a sequenced monolith-to-modular pipeline that sizes and inventories components, finds shared domain duplication, addresses flattening and hierarchy issues, analyzes coupling, then groups components into candidate domain-aligned units, with optional embedded DDD strategic analysis for bounded contexts. Use when asking how to split a monolith, size components before extraction, find duplicated domain logic, clean up module hierarchy, measure coupling between modules, or group components into services. Do NOT use for phased extraction roadmaps or prioritization without the prior analysis steps (use decomposition-planning-roadmap after this pipeline), end-to-end legacy migration strategy writeups (use legacy-migration-planner), pure infrastructure capacity sizing, or when you only need DDD without the structural pipeline (install domain-analysis standalone).
Technology-agnostic guidance for modular systems: bounded contexts, clear boundaries, composability, state isolation, explicit contracts, failure containment, scaffolding workflows, split/merge criteria, sub-units inside a context, and compliance review signals. Use when designing or reviewing module structure, service boundaries, package layout, cross-cutting dependencies, "how should we split this?", modularity assessments, coupling between domains, greenfield context design, or architecture discussions without assuming a specific framework, language, or repository layout. Do NOT use for executing the full Patterns 1–5 repo decomposition pipeline or per-pattern inventories (use modular-decomposition), phased extraction roadmaps as the main deliverable (use decomposition-planning-roadmap), or end-to-end legacy migration strategy (use legacy-migration-planner).
Project and feature planning with 4 adaptive phases - Specify, Design, Tasks, Execute. Auto-sizes depth by complexity. Creates atomic tasks with verification criteria, atomic git commits, requirement traceability, and persistent memory across sessions. Stack-agnostic. Use when (1) Starting new projects (initialize vision, goals, roadmap), (2) Working with existing codebases (map stack, architecture, conventions), (3) Planning features (requirements, design, task breakdown), (4) Implementing with verification and atomic commits, (5) Quick ad-hoc tasks (bug fixes, config changes), (6) Tracking decisions/blockers/deferred ideas across sessions, (7) Pausing/resuming work. Triggers on "initialize project", "map codebase", "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "quick fix", "quick task", "pause work", "resume work". Do NOT use for architecture decomposition analysis (use architecture skills) or technical design docs (use create-technical-design-doc).
When the user wants to build an AI-powered outreach system, write cold emails, improve deliverability, or scale personalized outreach. Also use when the user mentions 'cold email,' 'cold outreach,' 'outreach automation,' 'Instantly,' 'Smartlead,' 'Clay,' 'email sequences,' 'deliverability,' 'personalization at scale,' 'reply rate,' or 'outreach stack.' This skill covers the complete AI cold outreach system from signal detection through conversion. Do NOT use for technical implementation, code review, or software architecture.
