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design-screenshot
// [Design] Use when you need to create a design based on screenshot.
// [Design] Use when you need to create a design based on screenshot.
[HINT] Download the complete skill directory including SKILL.md and all related files
| name | design-screenshot |
| version | 1.0.0 |
| description | [Design] Use when you need to create a design based on screenshot. |
| disable-model-invocation | false |
Goal: Analyze a screenshot and recreate the design as functional code.
Workflow:
ui-ux-pro-max for matching design patternsKey Rules:
ui-ux-pro-max FIRST for design intelligenceai-multimodal for detailed screenshot analysisBe 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 database (ALWAYS ACTIVATE FIRST)frontend-design - Screenshot analysis and replicationEnsure token efficiency while maintaining high quality.
ai-multimodal skills to describe super details of the screenshot (design style, trends, fonts, colors, border, spacing, elements' positions, size, shape, texture, material, light, shadow, reflection, refraction, blur, glow, image, background transparency, transition, etc.)
ui-ux-designer subagent to create a design plan following the progressive disclosure structure so the final result matches the screenshot:
## Naming section.plan.md, keep it generic, under 80 lines, and list each phase with status/progress and links.phase-XX-phase-name.md files containing sections (Context links, Overview with date/priority/statuses, Key Insights, Requirements, Architecture, Related code files, Implementation Steps, Todo list, Success Criteria, Risk Assessment, Security Considerations, Next steps)../docs/design-guidelines.md docs if needed.media-processing skill (RMBG) to remove background from generated assets if needed../docs/design-guidelines.md docs if needed.[IMPORTANT] Use
TaskCreateto 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.
Think hard to plan & start designing follow exactly this screenshot: $ARGUMENTS
Skill Variant: Variant of design skills — recreate/implement from screenshot.
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.
TaskCreate BEFORE startingfile:line evidence for every claim (confidence >80% to act)[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.