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frontend-design
// [Frontend] Use when you need to create distinctive, production-grade frontend interfaces with high design quality.
// [Frontend] Use when you need to create distinctive, production-grade frontend interfaces with high design quality.
[HINT] Download the complete skill directory including SKILL.md and all related files
| name | frontend-design |
| description | [Frontend] Use when you need to create distinctive, production-grade frontend interfaces with high design quality. |
Codex compatibility note:
- Invoke repository skills with
$skill-namein Codex; this mirrored copy rewrites legacy Claude/skill-namereferences.- Prefer the
plan-hardskill 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_agentsubagent(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 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-patterns-reference.md, domain-entities-reference.md, project-structure-reference.mdfrontend-patterns-reference.md, scss-styling-guide.md, design-system/README.mdfeature-docs-reference.mdintegration-test-reference.mde2e-test-reference.mdcode-review-rules.md plus domain docs above based on changed filesDo not read all docs blindly. Start from docs-index-reference.md, then open only relevant files for the task.
[BLOCKING] Execute skill steps in declared order. NEVER skip, reorder, or merge steps without explicit user approval. [BLOCKING] Before each step or sub-skill call, update task tracking: set
in_progresswhen step starts, setcompletedwhen step ends. [BLOCKING] Every completed/skipped step MUST include brief evidence or explicit skip reason. [BLOCKING] If Task tools are unavailable, create and maintain an equivalent step-by-step plan tracker with the same status transitions.
Goal: Create distinctive, production-grade frontend interfaces with high design quality, avoiding generic AI aesthetics.
Workflow:
Key Rules:
When this task involves frontend or UI changes,
Component patterns: docs/project-reference/frontend-patterns-reference.md (read directly when relevant; do not rely on hook-injected conversation text)
Styling/BEM guide: docs/project-reference/scss-styling-guide.md
Design system tokens: docs/project-reference/design-system/README.md
For screenshot inputs, extract design guidelines FIRST before coding
Never use generic fonts (Inter, Roboto, Arial) or cliched color schemes
Match implementation complexity to aesthetic vision (maximalist = elaborate, minimalist = precise)
Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).
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.
The user provides frontend requirements: a component, page, application, or interface to build. They may include context about the purpose, audience, or technical constraints.
⚠️ MUST ATTENTION READ references/design-extraction-overview.md before executing screenshot-based workflows — contains design guideline extraction protocols, analysis prompts, and visual verification methods required by the screenshot/image input workflow below. For asset generation workflows, also ⚠️ MUST ATTENTION READ references/asset-generation.md.
MANDATORY workflow for screenshot/image/design inputs:
Extract Design Guidelines using ./references/design-extraction-overview.md:
docs/design-guidelines/extracted-design.md./references/extraction-prompts.md for comprehensive analysis promptsImplement Code following extracted guidelines:
Verify Quality using ./references/visual-analysis-overview.md:
Important: Do NOT skip to implementation. Extract design guidelines FIRST, then code.
Follow "Design Thinking" process below to create original design.
Before coding, understand the context and 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 (HTML/CSS/JS, React, Vue, etc.) that is:
Focus on:
anime.js for animations: ./references/animejs.md). Focus on high-impact moments: one well-orchestrated page load with staggered reveals (animation-delay) creates more delight than scattered micro-interactions. Use scroll-triggering and hover states that surprise.ai-multimodal skills to generate the assets and media-processing skill to remove the background of generated assets if neededQuick Start: ./references/ai-multimodal-overview.md
When GENERATE new hero images, backgrounds, textures, or decorative elements that match the design aesthetic, use the ai-multimodal skill. This ensures generated assets align with the design thinking and aesthetics guidelines rather than producing generic imagery.
When user provides screenshots, photos, or design references to analyze or replicate, use ./references/design-extraction-overview.md to extract design guidelines BEFORE implementation. This is MANDATORY for screenshot inputs (see "Input Types & Workflows" above).
Workflows:
./references/asset-generation.md - Generate design-aligned visual assets./references/visual-analysis-overview.md - Analyze and verify asset quality (modular)./references/design-extraction-overview.md - Extract guidelines from inspiration (modular)./references/technical-overview.md - Optimization and best practices (modular)Each overview references detailed sub-modules for progressive disclosure.
NEVER use generic AI-generated aesthetics like overused font families (Inter, Roboto, Arial, system fonts), cliched color schemes (particularly purple gradients on white backgrounds), predictable layouts and component patterns, and cookie-cutter design that lacks context-specific character.
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 (Space Grotesk, for example) across generations.
IMPORTANT: 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. Elegance comes from executing the vision well.
Remember: Claude 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.
interface-design — Product UIs (dashboards, admin panels, SaaS apps)ui-ux-pro-maxshadcn-tailwind[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.
UI System Context — For ANY task touching
.ts,.html,.scss, or.cssfiles:MUST ATTENTION READ before implementing:
docs/project-reference/frontend-patterns-reference.md— component base classes, stores, formsdocs/project-reference/scss-styling-guide.md— BEM methodology, SCSS variables, mixins, responsivedocs/project-reference/design-system/README.md— design tokens, component inventory, iconsReference
docs/project-config.jsonfor project-specific paths.
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.
IMPORTANT MUST ATTENTION follow declared step order for this skill; NEVER skip, reorder, or merge steps without explicit user approval
IMPORTANT MUST ATTENTION for every step/sub-skill call: set in_progress before execution, set completed after execution
IMPORTANT MUST ATTENTION every skipped step MUST include explicit reason; every completed step MUST include concise evidence
IMPORTANT MUST ATTENTION if Task tools unavailable, maintain an equivalent step-by-step plan tracker with synchronized statuses
file:line evidence for every claim (confidence >80% to act)references/design-extraction-overview.md before startingreferences/asset-generation.md before starting[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using task tracking.
[IMPORTANT] Analyze how big the task is and break it into many small todo tasks systematically before starting — this is very important.
Source: .claude/hooks/lib/prompt-injections.cjs + .claude/.ck.json
$workflow-start <workflowId> for standard; sequence custom steps manually[CRITICAL] Hard-won project debugging/architecture rules. MUST ATTENTION apply BEFORE forming hypothesis or writing code.
Goal: Prevent recurrence of known failure patterns — debugging, architecture, naming, AI orchestration, environment.
Top Rules (apply always):
ExecuteInjectScopedAsync for parallel async + repo/UoW — NEVER ExecuteUowTaskwhere python/where py) — NEVER assume python/python3 resolvesExecuteInjectScopedAsync, 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).AccountUserEntityEventBusMessage = Accounts owns). Core services (Accounts, Communication) are leaders. Feature services (Growth, Talents) sending to core MUST use {CoreServiceName}...RequestBusMessage — never define own event for core to consume.HrManagerOrHrOrPayrollHrOperationsPolicy names set members, not what it 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 in behavioral idioms (FirstOrDefault, SuccessOrThrow) — expresses HAPPENS, not membership.python/python3 resolves — verify alias first. Python may not be in bash PATH under those names. Check: where python / where py. Prefer py (Windows Python Launcher) for one-liners, node if JS alternative exists.Test-specific lessons →
docs/project-reference/integration-test-reference.mdLessons Learned section. Production-code anti-patterns →docs/project-reference/backend-patterns-reference.mdAnti-Patterns section. Generic debugging/refactoring reminders → System Lessons in.claude/hooks/lib/prompt-injections.cjs.
ExecuteInjectScopedAsync, NEVER ExecuteUowTask (shared DbContext = silent data corruption){CoreServiceName}...RequestBusMessagepython/python3 resolves — run where python/where py first, use py launcher or nodeBreak work into small tasks (task tracking) before starting. Add final task: "Analyze AI mistakes & lessons learned".
Extract lessons — ROOT CAUSE ONLY, not symptom fixes:
$learn.$code-review/$code-simplifier/$security/$lint catch this?" — Yes → improve review skill instead.$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.