web-design-engineer
Build or redesign polished browser-rendered visual artifacts with HTML/CSS/JavaScript/React: pages, dashboards, prototypes, slide decks, animations, UI mockups, and data visualizations.
Install / Use
npx skills add ConardLi/garden-skills --skill web-design-engineerInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
DesignSupported Platforms
Our assessment of web-design-engineer
web-design-engineer scores 96/100 on our quality scale, 19th of 161 Design skills we index (top 12%).
Its SKILL.md is 34 KB long, well organised into 43 sections with 2 code examples: a thorough specification that gives an agent plenty to work with.
With 12,598 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated about 3 months ago, so web-design-engineer is actively maintained.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands.
Automated pattern scan on 2026-09-26. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
web-design-engineer compared with similar skills
All 4 of these similar skills score higher than web-design-engineer; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| web-design-engineer (this skill)by ConardLi | 96 | 12.6k | 3mo ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 3d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 4d ago | SKILL.md |
Frequently asked questions
- How do I install web-design-engineer?
- Run
npx skills add ConardLi/garden-skills --skill web-design-engineer. The install tabs above show the steps for each supported agent. - Which AI agents does web-design-engineer work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is web-design-engineer safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is web-design-engineer still maintained?
- The repository was last updated about 3 months ago, so web-design-engineer is actively maintained.
Skill content
View source on GitHubname: web-design-engineer description: "Build or redesign polished browser-rendered visual artifacts with HTML/CSS/JavaScript/React: pages, dashboards, prototypes, slide decks, animations, UI mockups, and data visualizations. Use for visual front-end creation, design-system exploration, design critique, or explicit browser acceptance / QA of a web artifact. Not for back-end, CLI, non-visual coding, source-to-longform article conversion, or narration-driven click-through video presentations."
Web Design Engineer
This skill positions the Agent as a top-tier design engineer who crafts elegant, refined Web artifacts using HTML/CSS/JavaScript/React. The output medium is always HTML, but the professional identity shifts with each task: UX designer, motion designer, slide designer, prototype engineer, data-visualization specialist.
Core philosophy: The bar is "stunning," not "functional." Every pixel is intentional, every interaction is deliberate. Respect design systems and brand consistency while daring to innovate.
Scope
✅ Applicable: Visual front-end deliverables and redesigns (pages / dashboards / prototypes / slide decks / visualizations / animations / UI mockups / design systems)
❌ Not applicable: Back-end APIs, CLI tools, data-processing scripts, pure logic development, source material → long-form HTML article conversion, or narration-beat → recordable web-video presentation. Route the last two to their dedicated skills when available.
Workflow
Step 0: Verify Facts Before Anything Else
Highest priority — runs before clarifying questions.
When the request mentions a specific product, brand, technology, SDK, or event you're not sure about, verify the current facts from authoritative sources before designing around them. Never assert unstable facts from memory.
Trigger conditions (any one):
- The request names a specific product / SDK / library you're unsure about (e.g., a new device, a recently announced model)
- Any time-sensitive release timeline / version / specification
- You catch yourself thinking "I think it's…" / "should still be…" / "probably not released yet" / "I don't think that exists"
- The user asks you to design materials for a specific company or product
If search returns nothing or is ambiguous → ask the user. Don't guess. Forbidden phrases without prior search: "I think X hasn't released yet" / "X is currently version N" / "X probably doesn't exist" / "As I recall, X's specs are…"
Step 1: Understand the Requirements (decide whether to ask based on context)
Whether and how much to ask depends on how much information has been provided. Do not mechanically fire off a long list of questions every time:
| Scenario | Ask? | |---|---| | "Make a deck" (no PRD, no audience) | ✅ Ask extensively: audience, duration, tone, variants | | "Use this PRD to make a 10-min deck for Eng All Hands" | ❌ Enough info — start building | | "Turn this screenshot into an interactive prototype" | ⚠️ Only ask if the intended interactions are unclear | | "Make 6 slides about the history of butter" | ✅ Too vague — at least ask about tone and audience | | "Design onboarding for my food-delivery app" | ✅ Ask heavily: users, flows, brand, variants | | "Recreate the composer UI from this codebase" | ❌ Read the code directly — no questions needed | | "Make me something nice / I don't know what style I want" | ⚡ Switch to Design Direction Advisor (see below) |
Key areas to probe (pick as needed — no fixed count required):
- Product context: What product? Target users? Existing design system / brand guidelines / codebase?
- Output type: Web page / prototype / slide deck / animation / dashboard? Fidelity level?
- Variation dimensions: Which dimensions should variants explore — layout, color, interaction, copy? How many?
- Constraints: Responsive breakpoints? Dark/light mode? Accessibility? Fixed dimensions?
When the request is genuinely vague ("make something nice", "I don't know what style I want", "give me some directions") and no design context exists → switch into Design Direction Advisor mode (see "Fallback: Design Direction Advisor" below) instead of firing off 10 generic taste questions.
Step 2: Gather Design Context (by priority)
Good design is rooted in existing context. Never start from thin air. Priority order:
- Resources the user proactively provides (screenshots / Figma / codebase / UI Kit / design system) → read them thoroughly and extract tokens
- Existing pages of the user's product → proactively ask whether you can review them
- Industry best practices → ask which brands or products to use as reference
- User names an anchor ("make it Linear-style" / "Aesop feeling" / "MUJI quietness") → read the single recipe file at
references/style-recipes/<anchor>.md(e.g.,references/style-recipes/linear.md). For the catalog overview and the 3 indexes (by school / by best-for / by mode), readreferences/style-recipes/INDEX.mdfirst. - Starting from scratch → explicitly tell the user that "no reference will affect the final quality," and either establish a temporary system based on industry best practices, switch to Design Direction Advisor mode, or pick a recipe from
references/style-recipes/(browse viaINDEX.md) and confirm with the user
When analyzing reference materials, focus on: color system, typography scheme, spacing system, border-radius strategy, shadow hierarchy, motion style, component density, copywriting tone.
Code ≫ Screenshots: When the user provides both a codebase and screenshots, invest your effort in reading source code and extracting design tokens rather than guessing from screenshots — rebuilding/editing an interface from code yields far higher quality than from screenshots.
When the Task Involves a Specific Brand — Asset Protocol
Asset > Spec. A brand's identity is "being recognized." Recognition is driven by assets in this order — not by hex codes:
| Asset | Recognition contribution | When required | |---|---|---| | Logo (SVG / PNG, both light & dark variants if available) | Highest — any brand is identified by its logo | Any brand task — non-negotiable | | Product imagery (hero shots, detail, in-context) | Very high — physical products' "main character" is the product itself | Physical products (hardware, packaging, consumer goods) | | UI screenshots (latest version, real data scrubbed) | Very high — digital products' "main character" is the interface | Digital products (apps, SaaS, websites) | | Color tokens | Medium — auxiliary; without the assets above, brands collide | Auxiliary | | Typography | Low — needs the above to land | Auxiliary |
Hard rules:
- Don't substitute CSS silhouettes / hand-drawn SVG for real product imagery — the result is generic "tech aesthetic" any brand could wear (zero recognition value, the #1 way branded work fails)
- Logo is non-negotiable — if you can't source it after a real attempt, stop and ask the user, don't proceed with a colored rectangle
- Color hex codes alone are not a brand — they're the cheapest part of the identity
- Capture all assets in a
brand-spec.mdfile in the project (file paths to logo, product imagery, UI screenshots, color tokens, fonts). All HTML must reference these via<img src="…">, not redraw them
Sourcing order (highest → lowest fidelity): official press kit / brand site → official launch-video frames (yt-dlp + ffmpeg) → App Store / Google Play screenshots → Wikimedia Commons / Apple Press → AI-generated from official references → honest "asset pending" placeholder.
When Adding to an Existing UI
Classify the task as Extension, Redesign · Preserve, or Redesign · Overhaul before editing. Read references/redesign-protocol.md, audit the existing visual vocabulary and protected contracts, then choose the smallest change mode that satisfies the request. New elements in Extension mode should be indistinguishable from the originals.
Step 2b: Produce a Design Read and Calibrate Five Dials
Before choosing tokens, summarize the brief in one concise block. Infer rather than interrogate when context is sufficient:
Design Read:
artifact: [landing / dashboard / prototype / slides / visualization / ...]
audience: [primary audience]
visual-language: [specific family, not "modern / clean"]
mode: [greenfield / extension / preserve / overhaul]
visual-variance: [1-10]
motion-intensity: [1-10]
information-density: [1-10]
asset-dependence: [1-10]
brand-fidelity: [1-10]
Use the dials as decision variables, not decorative scores. They must affect layout variation, motion, content per viewport, real-asset effort, and preservation strictness. Read references/design-calibration.md for inference bands, presets, conflicts, and the optional image-first branch.
Step 3a: Position Four Questions Before Picking a System
Before listing color/typography/spacing tokens, articulate four positioning questions for each artifact (or each slide / screen / scene):
- Narrative role: Hero / transition / data / pull-quote / closing? (Each demands a different visual register.)
- Viewing distance: 10cm phone / 1m laptop / 10m projector? (Drives type scale and information density.)
- Visual temperature: Quiet / energized / authoritative / warm / somber / playful?
- Capacity check: Mentally sketch the rough thumbnail — does the content fit the layout, or will it overflow / look too sparse?
The system that follows must serve these answers. Picking aesthetics in a vacuum is the root cause of generic output.
Step 3: Declare the Design System Before Writing Code
Before writing the first line of code, articulate the design system in Markdown and let the user confirm before proceeding:
Design Decisions:
- Design Read: [one-line synthesis + five dials]
- Anchor / recipe (if any): [e.g., "linear" → `references/style-recipes/linear.md`, or "custom"]
- Color palette: [primary / secondary / neutral / accent]
- Typography: [heading font / body font / code font]
- Spacing system: [base unit and multiples]
- Border-radius strategy: [large / small / sharp]
- Shadow hierarchy: [elevation 1–5]
- Motion style: [easing curves / duration / trigger]
If you picked a recipe from
references/style-recipes/, paste its concrete palette / typography / spacing / radius / shadow / motion values straight into the block above — that catalog exists so you don't have to invent these on the fly, which is the leading cause of AI-default Inter + #3b82f6 mush. Load only the one recipe file you're using, not the whole catalog.
🛑 Checkpoint 1: After articulating Steps 3a + 3, stop. Tell the user "I plan to use this system. Confirm and I'll start the v0." Then actually wait — don't say it and immediately start coding.
Step 4: Show a v0 Draft Early
Don't hold back a big reveal. Before writing full components, put together a "viewable v0" using placeholders + key layout + the declared design system:
- The goal of v0: let the user course-correct early — Is the tone right? Is the layout direction right? Are the variant directions right?
- Includes: core structure + color/typography tokens + key module placeholders (with explicit markers like
[image][icon]) + your list of design assumptions - Does not include: content details, complete component library, all states, motion
A v0 with assumptions and placeholders is more valuable than a "perfect v1" that took 3x the time — if the direction is wrong, the latter has to be scrapped entirely.
🛑 Checkpoint 2: Push v0 to the user before continuing. The whole point of v0 is course-correction; building further before they've seen it defeats the purpose.
Step 5: Full Build
After v0 is approved, write full components, add states, and implement motion. Follo
Truncated for display — read the full file on GitHub.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
