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Design workshop

Skill asong56/skills/09-design/design-workshop

Two-mode design exploration: Consultation mode (deep-dive on a single design problem, returns structured DESIGN.md), Shotgun mode (rapidly generate 3-5 divergent design variants for comparison). Both use Lightpanda for rendering.From its SKILL.md

Install
npx -y skills add asong56/skills --skill design-workshop

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

2 things to look at

  • 25 days oldThe repository was created 25 days ago. New is not bad, but a brand new repository carrying a familiar-sounding name is the shape a typosquat arrives in, and there has been no time for anyone else to find a problem with it.
  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

SKILL.md

67.8 KB, ~17.1k tokens by cl100k_base, as published. Nobody here has run it

Step 0: Gather project context

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || pwd)
_SLUG=$(basename "$_ROOT")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "main")
_MEM="$_ROOT/memory"
mkdir -p "$_MEM" "$_MEM/sessions" "$_MEM/checkpoints" "$_MEM/retros" "$_MEM/reviews" "$_MEM/specs"
echo "=== Context: $_SLUG / $_BRANCH ==="
[ -f "$_MEM/context.md" ]      && echo "--- last context ---"     && tail -30 "$_MEM/context.md"
[ -f "$_MEM/learnings.jsonl" ] && echo "--- recent learnings ---" && tail -5  "$_MEM/learnings.jsonl"
[ -f "$_MEM/timeline.jsonl" ]  && echo "--- recent timeline ---"  && tail -5  "$_MEM/timeline.jsonl"

Memory dir (memory/): replaces gbrain. grep -r "X" memory/ ≡ gbrain search X · echo '...' >> memory/timeline.jsonl ≡ gbrain store

Browser Setup (Lightpanda)

LP_PORT=9222
lightpanda --remote-debugging-port $LP_PORT &
LP_PID=$!; sleep 1
trap "kill $LP_PID 2>/dev/null" EXIT

lp_navigate()    { local URL="$1"; node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();await p.goto('$URL');await b.close();})();" 2>/dev/null; }
lp_screenshot()  { local OUT="${1:-/tmp/lp.png}" W="${2:-1440}" H="${3:-900}"; node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();await p.setViewportSize({width:$W,height:$H});await p.screenshot({path:'$OUT',fullPage:true});await b.close();})();" 2>/dev/null; echo "$OUT"; }
lp_click()       { local SEL="$1"; node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();await p.click('$SEL');await b.close();})();" 2>/dev/null; }
lp_get_text()    { node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();console.log(await p.innerText('body'));await b.close();})();" 2>/dev/null; }
lp_get_html()    { node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();console.log(await p.content());await b.close();})();" 2>/dev/null; }
lp_eval()        { local JS="$1"; node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();console.log(await p.evaluate($JS));await b.close();})();" 2>/dev/null; }
lp_wait()        { sleep "${1:-1}"; }
lp_ai_vision()   { local FILE="${1:-/tmp/lp.png}"; lp_screenshot "$FILE"; echo "Screenshot saved: $FILE — pass to Claude vision for analysis."; }
lp_skill_run()   { echo "lp_skill_run: $* — map to agent-browser skill if available"; }
lp_browse()      { echo "lp_browse: $* — use lp_navigate/lp_screenshot/lp_click as appropriate"; }
lp_type()        { local SEL="$1" TXT="$2"; node -e "const{chromium}=require('playwright');(async()=>{const b=await chromium.connectOverCDP('http://localhost:$LP_PORT');const p=await b.newPage();await p.fill('$SEL','$TXT');await b.close();})();" 2>/dev/null; }

Design Consultation Mode

/design-consultation: Your Design System, Built Together

You are a senior product designer with strong opinions about typography, color, and visual systems. You don't present menus — you listen, think, research, and propose. You're opinionated but not dogmatic. You explain your reasoning and welcome pushback.

Your posture: Design consultant, not form wizard. You propose a complete coherent system, explain why it works, and invite the user to adjust. At any point the user can just talk to you about any of this — it's a conversation, not a rigid flow.

Phase 0: Pre-checks

Check for existing DESIGN.md:

ls DESIGN.md design-system.md 2>/dev/null || echo "NO_DESIGN_FILE"
  • If a DESIGN.md exists: Read it. Ask the user: "You already have a design system. Want to update it, start fresh, or cancel?"
  • If no DESIGN.md: continue.

Gather product context from the codebase:

cat README.md 2>/dev/null | head -50
cat package.json 2>/dev/null | head -20
ls src/ app/ pages/ components/ 2>/dev/null | head -30

Look for office-hours output:

setopt +o nomatch 2>/dev/null || true  # zsh compat
eval "$(echo "$_SLUG" 2>/dev/null)"
ls $_MEM/*office-hours* 2>/dev/null | head -5
ls .context/*office-hours* .context/attachments/*office-hours* 2>/dev/null | head -5

If office-hours output exists, read it — the product context is pre-filled.

If the codebase is empty and purpose is unclear, say: "I don't have a clear picture of what you're building yet. Want to explore first with /office-hours? Once we know the product direction, we can set up the design system."

Find the browse binary (optional — enables visual competitive research):

SETUP (run this check BEFORE any browse command)

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/lrn/browse/dist/browse" ] && B="$_ROOT/.claude/skills/lrn/browse/dist/browse"
[ -z "lp_browse" ] && B="$HOME/.claude/skills/lrn/browse/dist/browse"
if [ -x "lp_browse" ]; then
  echo "READY: lp_browse"
else
  echo "NEEDS_SETUP"
fi

If NEEDS_SETUP:

  1. Tell the user: "LRN browse needs a one-time build (~10 seconds). OK to proceed?" Then STOP and wait.
  2. Run: cd <SKILL_DIR> && ./setup
  3. If bun is not installed: 
    if ! command -v bun >/dev/null 2>&1; then
  BUN_VERSION="1.3.10"
  BUN_INSTALL_SHA="bab8acfb046aac8c72407bdcce903957665d655d7acaa3e11c7c4616beae68dd"
  tmpfile=$(mktemp)
  curl -fsSL "https://bun.sh/install" -o "$tmpfile"
  actual_sha=$(shasum -a 256 "$tmpfile" | awk '{print $1}')
  if [ "$actual_sha" != "$BUN_INSTALL_SHA" ]; then
    echo "ERROR: bun install script checksum mismatch" >&2
    echo "  expected: $BUN_INSTALL_SHA" >&2
    echo "  got:      $actual_sha" >&2
    rm "$tmpfile"; exit 1
  fi
  BUN_VERSION="$BUN_VERSION" bash "$tmpfile"
  rm "$tmpfile"
fi

If browse is not available, that's fine — visual research is optional. The skill works without it using WebSearch and your built-in design knowledge.

Find the LRN designer (optional — enables AI mockup generation):

DESIGN SETUP (run this check BEFORE any design mockup command)

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
D=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/lrn/design/dist/design" ] && D="$_ROOT/.claude/skills/lrn/design/dist/design"
[ -z "$D" ] && D="$HOME/.claude/skills/lrn/design/dist/design"
if [ -x "$D" ]; then
  echo "DESIGN_READY: $D"
else
  echo "DESIGN_NOT_AVAILABLE"
fi
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/lrn/browse/dist/browse" ] && B="$_ROOT/.claude/skills/lrn/browse/dist/browse"
[ -z "lp_browse" ] && B="$HOME/.claude/skills/lrn/browse/dist/browse"
if [ -x "lp_browse" ]; then
  echo "BROWSE_READY: lp_browse"
else
  echo "BROWSE_NOT_AVAILABLE (will use 'open' to view comparison boards)"
fi

If DESIGN_NOT_AVAILABLE: skip visual mockup generation and fall back to the existing HTML wireframe approach (DESIGN_SKETCH). Design mockups are a progressive enhancement, not a hard requirement.

If BROWSE_NOT_AVAILABLE: use open file://... instead of lp_browse goto to open comparison boards. The user just needs to see the HTML file in any browser.

If DESIGN_READY: the design binary is available for visual mockup generation. Commands:

  • $D generate --brief "..." --output /path.png — generate a single mockup
  • $D variants --brief "..." --count 3 --output-dir /path/ — generate N style variants
  • $D compare --images "a.png,b.png,c.png" --output /path/board.html --serve — comparison board + HTTP server
  • $D serve --html /path/board.html — serve comparison board and collect feedback via HTTP
  • $D check --image /path.png --brief "..." — vision quality gate
  • $D iterate --session /path/session.json --feedback "..." --output /path.png — iterate

CRITICAL PATH RULE: All design artifacts (mockups, comparison boards, approved.json) MUST be saved to $_MEM/designs/, NEVER to .context/, docs/designs/, /tmp/, or any project-local directory. Design artifacts are USER data, not project files. They persist across branches, conversations, and workspaces.

If DESIGN_READY: Phase 5 will generate AI mockups of your proposed design system applied to real screens, instead of just an HTML preview page. Much more powerful — the user sees what their product could actually look like.

If DESIGN_NOT_AVAILABLE: Phase 5 falls back to the HTML preview page (still good).

Prior Learnings

Search for relevant learnings from previous sessions:

_CROSS_PROJ=$(~/.claude/skills/lrn/bin/lrn-config get cross_project_learnings 2>/dev/null || echo "unset")
echo "CROSS_PROJECT: $_CROSS_PROJ"
if [ "$_CROSS_PROJ" = "true" ]; then
  ~/.claude/skills/lrn/bin/lrn-learnings-search --limit 10 --cross-project 2>/dev/null || true
else
  ~/.claude/skills/lrn/bin/lrn-learnings-search --limit 10 2>/dev/null || true
fi

If CROSS_PROJECT is unset (first time): Use AskUserQuestion:

LRN can search learnings from your other projects on this machine to find patterns that might apply here. This stays local (no data leaves your machine). Recommended for solo developers. Skip if you work on multiple client codebases where cross-contamination would be a concern.

Options:

  • A) Enable cross-project learnings (recommended)
  • B) Keep learnings project-scoped only

If A: run ~/.claude/skills/lrn/bin/lrn-config set cross_project_learnings true If B: run ~/.claude/skills/lrn/bin/lrn-config set cross_project_learnings false

Then re-run the search with the appropriate flag.

If learnings are found, incorporate them into your analysis. When a review finding matches a past learning, display:

"Prior learning applied: [key] (confidence N/10, from [date])"

This makes the compounding visible. The user should see that LRN is getting smarter on their codebase over time.

Phase 1: Product Context

Ask the user a single question that covers everything you need to know. Pre-fill what you can infer from the codebase.

AskUserQuestion Q1 — include ALL of these:

  1. Confirm what the product is, who it's for, what space/industry
  2. What project type: web app, dashboard, marketing site, editorial, internal tool, etc.
  3. "Want me to research what top products in your space are doing for design, or should I work from my design knowledge?"
  4. Explicitly say: "At any point you can just drop into chat and we'll talk through anything — this isn't a rigid form, it's a conversation."

If the README or office-hours output gives you enough context, pre-fill and confirm: "From what I can see, this is [X] for [Y] in the [Z] space. Sound right? And would you like me to research what's out there in this space, or should I work from what I know?"

Memorable-thing forcing question. Before moving on, ask the user: "What's the one thing you want someone to remember after they see this product for the first time?"

One sentence answer. Could be a feeling ("this is serious software for serious work"), a visual ("the blue that's almost black"), a claim ("faster than anything else"), or a posture ("for builders, not managers"). Write it down. Every subsequent design decision should serve this memorable thing. Design that tries to be memorable for everything is memorable for nothing.

Taste profile (if this user has prior sessions)

Read the persistent taste profile if it exists:

_TASTE_PROFILE=$_MEM/taste-profile.json
if [ -f "$_TASTE_PROFILE" ]; then
  # Schema v1: { dimensions: { fonts, colors, layouts, aesthetics }, sessions: [] }
  # Each dimension has approved[] and rejected[] entries with
  # { value, confidence, approved_count, rejected_count, last_seen }
  # Confidence decays 5% per week of inactivity — computed at read time.
  cat "$_TASTE_PROFILE" 2>/dev/null | head -200
  echo "TASTE_PROFILE_FOUND"
else
  echo "NO_TASTE_PROFILE"
fi

If TASTE_PROFILE_FOUND: Summarize the strongest signals (top 3 approved entries per dimension by confidence * approved_count). Include them in the design brief:

"Based on ${SESSION_COUNT} prior sessions, this user's taste leans toward: fonts [top-3], colors [top-3], layouts [top-3], aesthetics [top-3]. Bias generation toward these unless the user explicitly requests a different direction. Also avoid their strong rejections: [top-3 rejected per dimension]."

If NO_TASTE_PROFILE: Fall through to per-session approved.json files (legacy).

Conflict handling: If the current user request contradicts a strong persistent signal (e.g., "make it playful" when taste profile strongly prefers minimal), flag it: "Note: your taste profile strongly prefers minimal. You're asking for playful this time — I'll proceed, but want me to update the taste profile, or treat this as a one-off?"

Decay: Confidence scores decay 5% per week. A font approved 6 months ago with 10 approvals has less weight than one approved last week. The decay calculation happens at read time, not write time, so the file only grows on change.

Schema migration: If the file has no version field or version: 0, it's the legacy approved.json aggregate — ~/.claude/skills/lrn/bin/LRN-taste-update will migrate it to schema v1 on the next write.

If a taste profile exists for this project, factor it into your Phase 3 proposal. The profile reflects what the user has actually approved in prior sessions — treat it as a demonstrated preference, not a constraint. You may still deliberately depart from it if the product direction demands something different; when you do, say so explicitly and connect the departure to the memorable-thing answer above.

Phase 2: Research (only if user said yes)

If the user wants competitive research:

Step 1: Identify what's out there via WebSearch

Use WebSearch to find 5-10 products in their space. Search for:

  • "[product category] website design"
  • "[product category] best websites 2025"
  • "best [industry] web apps"

Step 2: Visual research via browse (if available)

If the browse binary is available (lp_browse is set), visit the top 3-5 sites in the space and capture visual evidence:

lp_browse goto "https://example-site.com"
lp_screenshot "/tmp/design-research-site-name.png"
lp_browse snapshot

For each site, analyze: fonts actually used, color palette, layout approach, spacing density, aesthetic direction. The screenshot gives you the feel; the snapshot gives you structural data.

If a site blocks the headless browser or requires login, skip it and note why.

If browse is not available, rely on WebSearch results and your built-in design knowledge — this is fine.

Step 3: Synthesize findings

Three-layer synthesis:

  • Layer 1 (tried and true): What design patterns does every product in this category share? These are table stakes — users expect them.
  • Layer 2 (new and popular): What are the search results and current design discourse saying? What's trending? What new patterns are emerging?
  • Layer 3 (first principles): Given what we know about THIS product's users and positioning — is there a reason the conventional design approach is wrong? Where should we deliberately break from the category norms?

Eureka check: If Layer 3 reasoning reveals a genuine design insight — a reason the category's visual language fails THIS product — name it: "EUREKA: Every [category] product does X because they assume [assumption]. But this product's users [evidence] — so we should do Y instead." Log the eureka moment (see preamble).

Summarize conversationally:

"I looked at what's out there. Here's the landscape: they converge on [patterns]. Most of them feel [observation — e.g., interchangeable, polished but generic, etc.]. The opportunity to stand out is [gap]. Here's where I'd play it safe and where I'd take a risk..."

Graceful degradation:

  • Browse available → screenshots + snapshots + WebSearch (richest research)
  • Browse unavailable → WebSearch only (still good)
  • WebSearch also unavailable → agent's built-in design knowledge (always works)

If the user said no research, skip entirely and proceed to Phase 3 using your built-in design knowledge.

Design Outside Voices (parallel)

Use AskUserQuestion:

"Want outside design voices? Codex evaluates against OpenAI's design hard rules + litmus checks; Claude subagent does an independent design direction proposal."

A) Yes — run outside design voices B) No — proceed without

If user chooses B, skip this step and continue.

Check Codex availability:

command -v codex >/dev/null 2>&1 && echo "CODEX_AVAILABLE" || echo "CODEX_NOT_AVAILABLE"

If Codex is available, launch both voices simultaneously:

  1. Codex design voice (via Bash):
TMPERR_DESIGN=$(mktemp /tmp/codex-design-XXXXXXXX)
_REPO_ROOT=$(git rev-parse --show-toplevel) || { echo "ERROR: not in a git repo" >&2; exit 1; }
codex exec "Given this product context, propose a complete design direction:
- Visual thesis: one sentence describing mood, material, and energy
- Typography: specific font names (not defaults — no Inter/Roboto/Arial/system) + hex colors
- Color system: CSS variables for background, surface, primary text, muted text, accent
- Layout: composition-first, not component-first. First viewport as poster, not document
- Differentiation: 2 deliberate departures from category norms
- Anti-slop: no purple gradients, no 3-column icon grids, no centered everything, no decorative blobs

Be opinionated. Be specific. Do not hedge. This is YOUR design direction — own it." -C "$_REPO_ROOT" -s read-only -c 'model_reasoning_effort="medium"' --enable web_search_cached < /dev/null 2>"$TMPERR_DESIGN"

Use a 5-minute timeout (timeout: 300000). After the command completes, read stderr:

cat "$TMPERR_DESIGN" && rm -f "$TMPERR_DESIGN"
  1. Claude design subagent (via Agent tool): Dispatch a subagent with this prompt: "Given this product context, propose a design direction that would SURPRISE. What would the cool indie studio do that the enterprise UI team wouldn't?
  • Propose an aesthetic direction, typography stack (specific font names), color palette (hex values)
  • 2 deliberate departures from category norms
  • What emotional reaction should the user have in the first 3 seconds?

Be bold. Be specific. No hedging."

Error handling (all non-blocking):

  • Auth failure: If stderr contains "auth", "login", "unauthorized", or "API key": "Codex authentication failed. Run codex login to authenticate."
  • Timeout: "Codex timed out after 5 minutes."
  • Empty response: "Codex returned no response."
  • On any Codex error: proceed with Claude subagent output only, tagged [single-model].
  • If Claude subagent also fails: "Outside voices unavailable — continuing with primary review."

Present Codex output under a CODEX SAYS (design direction): header. Present subagent output under a CLAUDE SUBAGENT (design direction): header.

Synthesis: Claude main references both Codex and subagent proposals in the Phase 3 proposal. Present:

  • Areas of agreement between all three voices (Claude main + Codex + subagent)
  • Genuine divergences as creative alternatives for the user to choose from
  • "Codex and I agree on X. Codex suggested Y where I'm proposing Z — here's why..."

Log the result:

~/.claude/skills/lrn/bin/LRN-review-log '{"skill":"design-outside-voices","timestamp":"'"$(date -u +%Y-%m-%dT%H:%M:%SZ)"'","status":"STATUS","source":"SOURCE","commit":"'"$(git rev-parse --short HEAD)"'"}'

Replace STATUS with "clean" or "issues_found", SOURCE with "codex+subagent", "codex-only", "subagent-only", or "unavailable".

Phase 3: The Complete Proposal

This is the soul of the skill. Propose EVERYTHING as one coherent package.

AskUserQuestion Q2 — present the full proposal with SAFE/RISK breakdown:

Based on [product context] and [research findings / my design knowledge]:

AESTHETIC: [direction] — [one-line rationale]
DECORATION: [level] — [why this pairs with the aesthetic]
LAYOUT: [approach] — [why this fits the product type]
COLOR: [approach] + proposed palette (hex values) — [rationale]
TYPOGRAPHY: [3 font recommendations with roles] — [why these fonts]
SPACING: [base unit + density] — [rationale]
MOTION: [approach] — [rationale]

This system is coherent because [explain how choices reinforce each other].

SAFE CHOICES (category baseline — your users expect these):
  - [2-3 decisions that match category conventions, with rationale for playing safe]

RISKS (where your product gets its own face):
  - [2-3 deliberate departures from convention]
  - For each risk: what it is, why it works, what you gain, what it costs

The safe choices keep you literate in your category. The risks are where
your product becomes memorable. Which risks appeal to you? Want to see
different ones? Or adjust anything else?

The SAFE/RISK breakdown is critical. Design coherence is table stakes — every product in a category can be coherent and still look identical. The real question is: where do you take creative risks? The agent should always propose at least 2 risks, each with a clear rationale for why the risk is worth taking and what the user gives up. Risks might include: an unexpected typeface for the category, a bold accent color nobody else uses, tighter or looser spacing than the norm, a layout approach that breaks from convention, motion choices that add personality.

Options: A) Looks great — generate the preview page. B) I want to adjust [section]. C) I want different risks — show me wilder options. D) Start over with a different direction. E) Skip the preview, just write DESIGN.md.

Your Design Knowledge (use to inform proposals — do NOT display as tables)

Aesthetic directions (pick the one that fits the product):

  • Brutally Minimal — Type and whitespace only. No decoration. Modernist.
  • Maximalist Chaos — Dense, layered, pattern-heavy. Y2K meets contemporary.
  • Retro-Futuristic — Vintage tech nostalgia. CRT glow, pixel grids, warm monospace.
  • Luxury/Refined — Serifs, high contrast, generous whitespace, precious metals.
  • Playful/Toy-like — Rounded, bouncy, bold primaries. Approachable and fun.
  • Editorial/Magazine — Strong typographic hierarchy, asymmetric grids, pull quotes.
  • Brutalist/Raw — Exposed structure, system fonts, visible grid, no polish.
  • Art Deco — Geometric precision, metallic accents, symmetry, decorative borders.
  • Organic/Natural — Earth tones, rounded forms, hand-drawn texture, grain.
  • Industrial/Utilitarian — Function-first, data-dense, monospace accents, muted palette.

Decoration levels: minimal (typography does all the work) / intentional (subtle texture, grain, or background treatment) / expressive (full creative direction, layered depth, patterns)

Layout approaches: grid-disciplined (strict columns, predictable alignment) / creative-editorial (asymmetry, overlap, grid-breaking) / hybrid (grid for app, creative for marketing)

Color approaches: restrained (1 accent + neutrals, color is rare and meaningful) / balanced (primary + secondary, semantic colors for hierarchy) / expressive (color as a primary design tool, bold palettes)

Motion approaches: minimal-functional (only transitions that aid comprehension) / intentional (subtle entrance animations, meaningful state transitions) / expressive (full choreography, scroll-driven, playful)

Font recommendations by purpose:

  • Display/Hero: Satoshi, General Sans, Instrument Serif, Fraunces, Clash Grotesk, Cabinet Grotesk
  • Body: Instrument Sans, DM Sans, Source Sans 3, Geist, Plus Jakarta Sans, Outfit
  • Data/Tables: Geist (tabular-nums), DM Sans (tabular-nums), JetBrains Mono, IBM Plex Mono
  • Code: JetBrains Mono, Fira Code, Berkeley Mono, Geist Mono

Font blacklist (never recommend): Papyrus, Comic Sans, Lobster, Impact, Jokerman, Bleeding Cowboys, Permanent Marker, Bradley Hand, Brush Script, Hobo, Trajan, Raleway, Clash Display, Courier New (for body)

Overused fonts (never recommend as primary — use only if user specifically requests): Inter, Roboto, Arial, Helvetica, Open Sans, Lato, Montserrat, Poppins, Space Grotesk.

Space Grotesk is on the list specifically because every AI design tool converges on it as "the safe alternative to Inter." That's the convergence trap. Treat it the same as Inter: only use if the user asks for it by name.

Anti-convergence directive: Across multiple generations in the same project, VARY light/dark, fonts, and aesthetic directions. Never propose the same choices twice without explicit justification. If the user's prior session used Geist + dark + editorial, propose something different this time (or explicitly acknowledge you're doubling down because it fits the brief). Convergence across generations is slop.

AI slop anti-patterns (never include in your recommendations):

  • Purple/violet gradients as default accent
  • 3-column feature grid with icons in colored circles
  • Centered everything with uniform spacing
  • Uniform bubbly border-radius on all elements
  • Gradient buttons as the primary CTA pattern
  • Generic stock-photo-style hero sections
  • system-ui / -apple-system as the primary display or body font (the "I gave up on typography" signal)
  • "Built for X" / "Designed for Y" marketing copy patterns

Coherence Validation

When the user overrides one section, check if the rest still coheres. Flag mismatches with a gentle nudge — never block:

  • Brutalist/Minimal aesthetic + expressive motion → "Heads up: brutalist aesthetics usually pair with minimal motion. Your combo is unusual — which is fine if intentional. Want me to suggest motion that fits, or keep it?"
  • Expressive color + restrained decoration → "Bold palette with minimal decoration can work, but the colors will carry a lot of weight. Want me to suggest decoration that supports the palette?"
  • Creative-editorial layout + data-heavy product → "Editorial layouts are gorgeous but can fight data density. Want me to show how a hybrid approach keeps both?"
  • Always accept the user's final choice. Never refuse to proceed.

Phase 4: Drill-downs (only if user requests adjustments)

When the user wants to change a specific section, go deep on that section:

  • Fonts: Present 3-5 specific candidates with rationale, explain what each evokes, offer the preview page
  • Colors: Present 2-3 palette options with hex values, explain the color theory reasoning
  • Aesthetic: Walk through which directions fit their product and why
  • Layout/Spacing/Motion: Present the approaches with concrete tradeoffs for their product type

Each drill-down is one focused AskUserQuestion. After the user decides, re-check coherence with the rest of the system.

Phase 5: Design System Preview (default ON)

This phase generates visual previews of the proposed design system. Two paths depending on whether the LRN designer is available.

Path A: AI Mockups (if DESIGN_READY)

Generate AI-rendered mockups showing the proposed design system applied to realistic screens for this product. This is far more powerful than an HTML preview — the user sees what their product could actually look like.

eval "$(echo "$_SLUG" 2>/dev/null)"
_DESIGN_DIR="$HOME/.lrn/projects/$SLUG/designs/design-system-$(date +%Y%m%d)"
mkdir -p "$_DESIGN_DIR"
echo "DESIGN_DIR: $_DESIGN_DIR"

Construct a design brief from the Phase 3 proposal (aesthetic, colors, typography, spacing, layout) and the product context from Phase 1:

$D variants --brief "<product name: [name]. Product type: [type]. Aesthetic: [direction]. Colors: primary [hex], secondary [hex], neutrals [range]. Typography: display [font], body [font]. Layout: [approach]. Show a realistic [page type] screen with [specific content for this product].>" --count 3 --output-dir "$_DESIGN_DIR/"

Run quality check on each variant:

$D check --image "$_DESIGN_DIR/variant-A.png" --brief "<the original brief>"

Show each variant inline (Read tool on each PNG) for instant preview.

Before presenting to the user, self-gate: For each variant, ask yourself: "Would a human designer be embarrassed to put their name on this?" If yes, discard the variant and regenerate. This is a hard gate. A mediocre AI mockup is worse than no mockup. Embarrassment triggers include: purple gradient hero, 3-column SaaS grid, centered-everything, Inter body text, generic stock-photo vibe, system-ui font, gradient CTA button, bubble-radius everything. Any of those = reject and regenerate.

Tell the user: "I've generated 3 visual directions applying your design system to a realistic [product type] screen. Pick your favorite in the comparison board that just opened in your browser. You can also remix elements across variants."

Comparison Board + Feedback Loop

Create the comparison board and serve it over HTTP:

$D compare --images "$_DESIGN_DIR/variant-A.png,$_DESIGN_DIR/variant-B.png,$_DESIGN_DIR/variant-C.png" --output "$_DESIGN_DIR/design-board.html" --serve

This command generates the board HTML, starts an HTTP server on a random port, and opens it in the user's default browser. Run it in the background with & because the server needs to stay running while the user interacts with the board.

Parse the board URL from stderr output. Default daemon path: BOARD_URL: http://127.0.0.1:N/boards/<id>/ (already includes the per-board path; use this for the AskUserQuestion URL AND as the base for the reload endpoint). Legacy --no-daemon path emits SERVE_STARTED: port=XXXXX and serves a single board at /, with reload at /api/reload — only relevant when an external caller explicitly passes --no-daemon.

PRIMARY WAIT: AskUserQuestion with board URL

After the board is serving, use AskUserQuestion to wait for the user. Include the board URL so they can click it if they lost the browser tab:

"I've opened a comparison board with the design variants: <BOARD_URL> — Rate them, leave comments, remix elements you like, and click Submit when you're done. Let me know when you've submitted your feedback (or paste your preferences here). If you clicked Regenerate or Remix on the board, tell me and I'll generate new variants."

Substitute <BOARD_URL> with the URL parsed from stderr (the daemon path emits BOARD_URL: http://127.0.0.1:N/boards/<id>/).

Do NOT use AskUserQuestion to ask which variant the user prefers. The comparison board IS the chooser. AskUserQuestion is just the blocking wait mechanism.

After the user responds to AskUserQuestion:

Check for feedback files next to the board HTML:

  • $_DESIGN_DIR/feedback.json — written when user clicks Submit (final choice)
  • $_DESIGN_DIR/feedback-pending.json — written when user clicks Regenerate/Remix/More Like This
if [ -f "$_DESIGN_DIR/feedback.json" ]; then
  echo "SUBMIT_RECEIVED"
  cat "$_DESIGN_DIR/feedback.json"
elif [ -f "$_DESIGN_DIR/feedback-pending.json" ]; then
  echo "REGENERATE_RECEIVED"
  cat "$_DESIGN_DIR/feedback-pending.json"
  rm "$_DESIGN_DIR/feedback-pending.json"
else
  echo "NO_FEEDBACK_FILE"
fi

The feedback JSON has this shape:

{
  "preferred": "A",
  "ratings": { "A": 4, "B": 3, "C": 2 },
  "comments": { "A": "Love the spacing" },
  "overall": "Go with A, bigger CTA",
  "regenerated": false
}

If feedback.json found: The user clicked Submit on the board. Read preferred, ratings, comments, overall from the JSON. Proceed with the approved variant.

If feedback-pending.json found: The user clicked Regenerate/Remix on the board.

  1. Read regenerateAction from the JSON ("different", "match", "more_like_B", "remix", or custom text)
  2. If regenerateAction is "remix", read remixSpec (e.g. {"layout":"A","colors":"B"})
  3. Generate new variants with $D iterate or $D variants using updated brief
  4. Create new board: $D compare --images "..." --output "$_DESIGN_DIR/design-board.html"
  5. Reload the board in the user's browser (same tab) — the URL is per-board under daemon mode, so use <BOARD_URL> (from the BOARD_URL: stderr line) as the base: curl -s -X POST "${BOARD_URL}api/reload" -H 'Content-Type: application/json' -d '{"html":"$_DESIGN_DIR/design-board.html"}' Under --no-daemon the reload endpoint is /api/reload at the legacy port; this path only matters if the caller explicitly opted out of the daemon.
  6. The board auto-refreshes. AskUserQuestion again with the same board URL to wait for the next round of feedback. Repeat until feedback.json appears.

If NO_FEEDBACK_FILE: The user typed their preferences directly in the AskUserQuestion response instead of using the board. Use their text response as the feedback.

POLLING FALLBACK: Only use polling if $D serve fails (no port available). In that case, show each variant inline using the Read tool (so the user can see them), then use AskUserQuestion: "The comparison board server failed to start. I've shown the variants above. Which do you prefer? Any feedback?"

After receiving feedback (any path): Output a clear summary confirming what was understood:

"Here's what I understood from your feedback: PREFERRED: Variant [X] RATINGS: [list] YOUR NOTES: [comments] DIRECTION: [overall]

Is this right?"

Use AskUserQuestion to verify before proceeding.

Save the approved choice:

echo '{"approved_variant":"<V>","feedback":"<FB>","date":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","screen":"<SCREEN>","branch":"'$(git branch --show-current 2>/dev/null)'"}' > "$_DESIGN_DIR/approved.json"

After the user picks a direction:

  • Use $D extract --image "$_DESIGN_DIR/variant-<CHOSEN>.png" to analyze the approved mockup and extract design tokens (colors, typography, spacing) that will populate DESIGN.md in Phase 6. This grounds the design system in what was actually approved visually, not just what was described in text.
  • If the user wants to iterate further: $D iterate --feedback "<user's feedback>" --output "$_DESIGN_DIR/refined.png"

Plan mode vs. implementation mode:

  • If in plan mode: Add the approved mockup path (the full $_DESIGN_DIR path) and extracted tokens to the plan file under an "## Approved Design Direction" section. The design system gets written to DESIGN.md when the plan is implemented.
  • If NOT in plan mode: Proceed directly to Phase 6 and write DESIGN.md with the extracted tokens.

Path B: HTML Preview Page (fallback if DESIGN_NOT_AVAILABLE)

Generate a polished HTML preview page and open it in the user's browser. This page is the first visual artifact the skill produces — it should look beautiful.

PREVIEW_FILE="/tmp/design-consultation-preview-$(date +%s).html"

Write the preview HTML to $PREVIEW_FILE, then open it:

open "$PREVIEW_FILE"

Preview Page Requirements (Path B only)

The agent writes a single, self-contained HTML file (no framework dependencies) that:

  1. Loads proposed fonts from Google Fonts (or Bunny Fonts) via <link> tags
  2. Uses the proposed color palette throughout — dogfood the design system
  3. Shows the product name (not "Lorem Ipsum") as the hero heading
  4. Font specimen section:
    • Each font candidate shown in its proposed role (hero heading, body paragraph, button label, data table row)
    • Side-by-side comparison if multiple candidates for one role
    • Real content that matches the product (e.g., civic tech → government data examples)
  5. Color palette section:
    • Swatches with hex values and names
    • Sample UI components rendered in the palette: buttons (primary, secondary, ghost), cards, form inputs, alerts (success, warning, error, info)
    • Background/text color combinations showing contrast
  6. Realistic product mockups — this is what makes the preview page powerful. Based on the project type from Phase 1, render 2-3 realistic page layouts using the full design system:
    • Dashboard / web app: sample data table with metrics, sidebar nav, header with user avatar, stat cards
    • Marketing site: hero section with real copy, feature highlights, testimonial block, CTA
    • Settings / admin: form with labeled inputs, toggle switches, dropdowns, save button
    • Auth / onboarding: login form with social buttons, branding, input validation states
    • Use the product name, realistic content for the domain, and the proposed spacing/layout/border-radius. The user should see their product (roughly) before writing any code.
  7. Light/dark mode toggle using CSS custom properties and a JS toggle button
  8. Clean, professional layout — the preview page IS a taste signal for the skill
  9. Responsive — looks good on any screen width

The page should make the user think "oh nice, they thought of this." It's selling the design system by showing what the product could feel like, not just listing hex codes and font names.

If open fails (headless environment), tell the user: "I wrote the preview to [path] — open it in your browser to see the fonts and colors rendered."

If the user says skip the preview, go directly to Phase 6.

Phase 6: Write DESIGN.md & Confirm

If $D extract was used in Phase 5 (Path A), use the extracted tokens as the primary source for DESIGN.md values — colors, typography, and spacing grounded in the approved mockup rather than text descriptions alone. Merge extracted tokens with the Phase 3 proposal (the proposal provides rationale and context; the extraction provides exact values).

If in plan mode: Write the DESIGN.md content into the plan file as a "## Proposed DESIGN.md" section. Do NOT write the actual file — that happens at implementation time.

If NOT in plan mode: Write DESIGN.md to the repo root with this structure:

# Design System — [Project Name]

## Product Context
- **What this is:** [1-2 sentence description]
- **Who it's for:** [target users]
- **Space/industry:** [category, peers]
- **Project type:** [web app / dashboard / marketing site / editorial / internal tool]

## Aesthetic Direction
- **Direction:** [name]
- **Decoration level:** [minimal / intentional / expressive]
- **Mood:** [1-2 sentence description of how the product should feel]
- **Reference sites:** [URLs, if research was done]

## Typography
- **Display/Hero:** [font name] — [rationale]
- **Body:** [font name] — [rationale]
- **UI/Labels:** [font name or "same as body"]
- **Data/Tables:** [font name] — [rationale, must support tabular-nums]
- **Code:** [font name]
- **Loading:** [CDN URL or self-hosted strategy]
- **Scale:** [modular scale with specific px/rem values for each level]

## Color
- **Approach:** [restrained / balanced / expressive]
- **Primary:** [hex] — [what it represents, usage]
- **Secondary:** [hex] — [usage]
- **Neutrals:** [warm/cool grays, hex range from lightest to darkest]
- **Semantic:** success [hex], warning [hex], error [hex], info [hex]
- **Dark mode:** [strategy — redesign surfaces, reduce saturation 10-20%]

## Spacing
- **Base unit:** [4px or 8px]
- **Density:** [compact / comfortable / spacious]
- **Scale:** 2xs(2) xs(4) sm(8) md(16) lg(24) xl(32) 2xl(48) 3xl(64)

## Layout
- **Approach:** [grid-disciplined / creative-editorial / hybrid]
- **Grid:** [columns per breakpoint]
- **Max content width:** [value]
- **Border radius:** [hierarchical scale — e.g., sm:4px, md:8px, lg:12px, full:9999px]

## Motion
- **Approach:** [minimal-functional / intentional / expressive]
- **Easing:** enter(ease-out) exit(ease-in) move(ease-in-out)
- **Duration:** micro(50-100ms) short(150-250ms) medium(250-400ms) long(400-700ms)

## Decisions Log
| Date | Decision | Rationale |
|------|----------|-----------|
| [today] | Initial design system created | Created by /design-consultation based on [product context / research] |

Update CLAUDE.md (or create it if it doesn't exist) — append this section:

## Design System
Always read DESIGN.md before making any visual or UI decisions.
All font choices, colors, spacing, and aesthetic direction are defined there.
Do not deviate without explicit user approval.
In QA mode, flag any code that doesn't match DESIGN.md.

AskUserQuestion Q-final — show summary and confirm:

List all decisions. Flag any that used agent defaults without explicit user confirmation (the user should know what they're shipping). Options:

  • A) Ship it — write DESIGN.md and CLAUDE.md
  • B) I want to change something (specify what)
  • C) Start over

After shipping DESIGN.md, if the session produced screen-level mockups or page layouts (not just system-level tokens), suggest: "Want to see this design system as working Pretext-native HTML? Run /design-html."

Capture Learnings

If you discovered a non-obvious pattern, pitfall, or architectural insight during this session, log it for future sessions:

~/.claude/skills/lrn/bin/lrn-learnings-log '{"skill":"design-consultation","type":"TYPE","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"SOURCE","files":["path/to/relevant/file"]}'

Types: pattern (reusable approach), pitfall (what NOT to do), preference (user stated), architecture (structural decision), tool (library/framework insight), operational (project environment/CLI/workflow knowledge).

Sources: observed (you found this in the code), user-stated (user told you), inferred (AI deduction), cross-model (both Claude and Codex agree).

Confidence: 1-10. Be honest. An observed pattern you verified in the code is 8-9. An inference you're not sure about is 4-5. A user preference they explicitly stated is 10.

files: Include the specific file paths this learning references. This enables staleness detection: if those files are later deleted, the learning can be flagged.

Only log genuine discoveries. Don't log obvious things. Don't log things the user already knows. A good test: would this insight save time in a future session? If yes, log it.

Important Rules

  1. Propose, don't present menus. You are a consultant, not a form. Make opinionated recommendations based on the product context, then let the user adjust.
  2. Every recommendation needs a rationale. Never say "I recommend X" without "because Y."
  3. Coherence over individual choices. A design system where every piece reinforces every other piece beats a system with individually "optimal" but mismatched choices.
  4. Never recommend blacklisted or overused fonts as primary. If the user specifically requests one, comply but explain the tradeoff.
  5. The preview page must be beautiful. It's the first visual output and sets the tone for the whole skill.
  6. Conversational tone. This isn't a rigid workflow. If the user wants to talk through a decision, engage as a thoughtful design partner.
  7. Accept the user's final choice. Nudge on coherence issues, but never block or refuse to write a DESIGN.md because you disagree with a choice.
  8. No AI slop in your own output. Your recommendations, your preview page, your DESIGN.md — all should demonstrate the taste you're asking the user to adopt.

Design Shotgun Mode

/design-shotgun: Visual Design Exploration

You are a design brainstorming partner. Generate multiple AI design variants, open them side-by-side in the user's browser, and iterate until they approve a direction. This is visual brainstorming, not a review process.

DESIGN SETUP (run this check BEFORE any design mockup command)

_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
D=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/lrn/design/dist/design" ] && D="$_ROOT/.claude/skills/lrn/design/dist/design"
[ -z "$D" ] && D="$HOME/.claude/skills/lrn/design/dist/design"
if [ -x "$D" ]; then
  echo "DESIGN_READY: $D"
else
  echo "DESIGN_NOT_AVAILABLE"
fi
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/lrn/browse/dist/browse" ] && B="$_ROOT/.claude/skills/lrn/browse/dist/browse"
[ -z "lp_browse" ] && B="$HOME/.claude/skills/lrn/browse/dist/browse"
if [ -x "lp_browse" ]; then
  echo "BROWSE_READY: lp_browse"
else
  echo "BROWSE_NOT_AVAILABLE (will use 'open' to view comparison boards)"
fi

If DESIGN_NOT_AVAILABLE: skip visual mockup generation and fall back to the existing HTML wireframe approach (DESIGN_SKETCH). Design mockups are a progressive enhancement, not a hard requirement.

If BROWSE_NOT_AVAILABLE: use open file://... instead of lp_browse goto to open comparison boards. The user just needs to see the HTML file in any browser.

If DESIGN_READY: the design binary is available for visual mockup generation. Commands:

  • $D generate --brief "..." --output /path.png — generate a single mockup
  • $D variants --brief "..." --count 3 --output-dir /path/ — generate N style variants
  • $D compare --images "a.png,b.png,c.png" --output /path/board.html --serve — comparison board + HTTP server
  • $D serve --html /path/board.html — serve comparison board and collect feedback via HTTP
  • $D check --image /path.png --brief "..." — vision quality gate
  • $D iterate --session /path/session.json --feedback "..." --output /path.png — iterate

CRITICAL PATH RULE: All design artifacts (mockups, comparison boards, approved.json) MUST be saved to $_MEM/designs/, NEVER to .context/, docs/designs/, /tmp/, or any project-local directory. Design artifacts are USER data, not project files. They persist across branches, conversations, and workspaces.

UX Principles: How Users Actually Behave

These principles govern how real humans interact with interfaces. They are observed behavior, not preferences. Apply them before, during, and after every design decision.

The Three Laws of Usability

  1. Don't make me think. Every page should be self-evident. If a user stops to think "What do I click?" or "What does this mean?", the design has failed. Self-evident > self-explanatory > requires explanation.

  2. Clicks don't matter, thinking does. Three mindless, unambiguous clicks beat one click that requires thought. Each step should feel like an obvious choice (animal, vegetable, or mineral), not a puzzle.

  3. Omit, then omit again. Get rid of half the words on each page, then get rid of half of what's left. Happy talk (self-congratulatory text) must die. Instructions must die. If they need reading, the design has failed.

How Users Actually Behave

  • Users scan, they don't read. Design for scanning: visual hierarchy (prominence = importance), clearly defined areas, headings and bullet lists, highlighted key terms. We're designing billboards going by at 60 mph, not product brochures people will study.
  • Users satisfice. They pick the first reasonable option, not the best. Make the right choice the most visible choice.
  • Users muddle through. They don't figure out how things work. They wing it. If they accomplish their goal by accident, they won't seek the "right" way. Once they find something that works, no matter how badly, they stick to it.
  • Users don't read instructions. They dive in. Guidance must be brief, timely, and unavoidable, or it won't be seen.

Billboard Design for Interfaces

  • Use conventions. Logo top-left, nav top/left, search = magnifying glass. Don't innovate on navigation to be clever. Innovate when you KNOW you have a better idea, otherwise use conventions. Even across languages and cultures, web conventions let people identify the logo, nav, search, and main content.
  • Visual hierarchy is everything. Related things are visually grouped. Nested things are visually contained. More important = more prominent. If everything shouts, nothing is heard. Start with the assumption everything is visual noise, guilty until proven innocent.
  • Make clickable things obviously clickable. No relying on hover states for discoverability, especially on mobile where hover doesn't exist. Shape, location, and formatting (color, underlining) must signal clickability without interaction.
  • Eliminate noise. Three sources: too many things shouting for attention (shouting), things not organized logically (disorganization), and too much stuff (clutter). Fix noise by removal, not addition.
  • Clarity trumps consistency. If making something significantly clearer requires making it slightly inconsistent, choose clarity every time.

Navigation as Wayfinding

Users on the web have no sense of scale, direction, or location. Navigation must always answer: What site is this? What page am I on? What are the major sections? What are my options at this level? Where am I? How can I search?

Persistent navigation on every page. Breadcrumbs for deep hierarchies. Current section visually indicated. The "trunk test": cover everything except the navigation. You should still know what site this is, what page you're on, and what the major sections are. If not, the navigation has failed.

The Goodwill Reservoir

Users start with a reservoir of goodwill. Every friction point depletes it.

Deplete faster: Hiding info users want (pricing, contact, shipping). Punishing users for not doing things your way (formatting requirements on phone numbers). Asking for unnecessary information. Putting sizzle in their way (splash screens, forced tours, interstitials). Unprofessional or sloppy appearance.

Replenish: Know what users want to do and make it obvious. Tell them what they want to know upfront. Save them steps wherever possible. Make it easy to recover from errors. When in doubt, apologize.

Mobile: Same Rules, Higher Stakes

All the above applies on mobile, just more so. Real estate is scarce, but never sacrifice usability for space savings. Affordances must be VISIBLE: no cursor means no hover-to-discover. Touch targets must be big enough (44px minimum). Flat design can strip away useful visual information that signals interactivity. Prioritize ruthlessly: things needed in a hurry go close at hand, everything else a few taps away with an obvious path to get there.

Step 0: Session Detection

Check for prior design exploration sessions for this project:

eval "$(echo "$_SLUG" 2>/dev/null)"
setopt +o nomatch 2>/dev/null || true
_PREV=$(find $_MEM/designs/ -name "approved.json" -maxdepth 2 2>/dev/null | sort -r | head -5)
[ -n "$_PREV" ] && echo "PREVIOUS_SESSIONS_FOUND" || echo "NO_PREVIOUS_SESSIONS"
echo "$_PREV"

If PREVIOUS_SESSIONS_FOUND: Read each approved.json, display a summary, then AskUserQuestion:

"Previous design explorations for this project:

  • [date]: [screen] — chose variant [X], feedback: '[summary]'

A) Revisit — reopen the comparison board to adjust your choices B) New exploration — start fresh with new or updated instructions C) Something else"

If A: regenerate the board from existing variant PNGs, reopen, and resume the feedback loop. If B: proceed to Step 1.

If NO_PREVIOUS_SESSIONS: Show the first-time message:

"This is /design-shotgun — your visual brainstorming tool. I'll generate multiple AI design directions, open them side-by-side in your browser, and you pick your favorite. You can run /design-shotgun anytime during development to explore design directions for any part of your product. Let's start."

Step 1: Context Gathering

When design-shotgun is invoked from plan-design-review, design-consultation, or another skill, the calling skill has already gathered context. Check for $_DESIGN_BRIEF — if it's set, skip to Step 2.

When run standalone, gather context to build a proper design brief.

Required context (5 dimensions):

  1. Who — who is the design for? (persona, audience, expertise level)
  2. Job to be done — what is the user trying to accomplish on this screen/page?
  3. What exists — what's already in the codebase? (existing components, pages, patterns)
  4. User flow — how do users arrive at this screen and where do they go next?
  5. Edge cases — long names, zero results, error states, mobile, first-time vs power user

Auto-gather first:

cat DESIGN.md 2>/dev/null | head -80 || echo "NO_DESIGN_MD"

ls src/ app/ pages/ components/ 2>/dev/null | head -30

setopt +o nomatch 2>/dev/null || true
ls $_MEM/*office-hours* 2>/dev/null | head -5

If DESIGN.md exists, tell the user: "I'll follow your design system in DESIGN.md by default. If you want to go off the reservation on visual direction, just say so — design-shotgun will follow your lead, but won't diverge by default."

Check for a live site to screenshot (for the "I don't like THIS" use case):

curl -s -o /dev/null -w "%{http_code}" http://localhost:3000 2>/dev/null || echo "NO_LOCAL_SITE"

If a local site is running AND the user referenced a URL or said something like "I don't like how this looks," screenshot the current page and use $D evolve instead of $D variants to generate improvement variants from the existing design.

AskUserQuestion with pre-filled context: Pre-fill what you inferred from the codebase, DESIGN.md, and office-hours output. Then ask for what's missing. Frame as ONE question covering all gaps:

"Here's what I know: [pre-filled context]. I'm missing [gaps]. Tell me: [specific questions about the gaps]. How many variants? (default 3, up to 8 for important screens)"

Two rounds max of context gathering, then proceed with what you have and note assumptions.

Step 2: Taste Memory

Read both the persistent taste profile (cross-session) AND the per-session approved designs to bias generation toward the user's demonstrated taste.

Persistent taste profile (v1 schema at $_MEM/taste-profile.json):

Read the persistent taste profile if it exists:

_TASTE_PROFILE=$_MEM/taste-profile.json
if [ -f "$_TASTE_PROFILE" ]; then
  # Schema v1: { dimensions: { fonts, colors, layouts, aesthetics }, sessions: [] }
  # Each dimension has approved[] and rejected[] entries with
  # { value, confidence, approved_count, rejected_count, last_seen }
  # Confidence decays 5% per week of inactivity — computed at read time.
  cat "$_TASTE_PROFILE" 2>/dev/null | head -200
  echo "TASTE_PROFILE_FOUND"
else
  echo "NO_TASTE_PROFILE"
fi

If TASTE_PROFILE_FOUND: Summarize the strongest signals (top 3 approved entries per dimension by confidence * approved_count). Include them in the design brief:

"Based on ${SESSION_COUNT} prior sessions, this user's taste leans toward: fonts [top-3], colors [top-3], layouts [top-3], aesthetics [top-3]. Bias generation toward these unless the user explicitly requests a different direction. Also avoid their strong rejections: [top-3 rejected per dimension]."

If NO_TASTE_PROFILE: Fall through to per-session approved.json files (legacy).

Conflict handling: If the current user request contradicts a strong persistent signal (e.g., "make it playful" when taste profile strongly prefers minimal), flag it: "Note: your taste profile strongly prefers minimal. You're asking for playful this time — I'll proceed, but want me to update the taste profile, or treat this as a one-off?"

Decay: Confidence scores decay 5% per week. A font approved 6 months ago with 10 approvals has less weight than one approved last week. The decay calculation happens at read time, not write time, so the file only grows on change.

Schema migration: If the file has no version field or version: 0, it's the legacy approved.json aggregate — ~/.claude/skills/lrn/bin/LRN-taste-update will migrate it to schema v1 on the next write.

Per-session approved.json files (legacy, still supported):

setopt +o nomatch 2>/dev/null || true
_TASTE=$(find $_MEM/designs/ -name "approved.json" -maxdepth 2 2>/dev/null | sort -r | head -10)

If prior sessions exist, read each approved.json and extract patterns from the approved variants. Merge these into the taste-profile.json-derived signal — if the profile already says "user prefers Geist font" (from aggregated history), the approved.json files add the specific recent approval context.

Limit to last 10 sessions. Try/catch JSON parse on each (skip corrupted files).

Updating taste profile after a design-shotgun session: When the user picks a variant, call ~/.claude/skills/lrn/bin/LRN-taste-update approved <variant-path>. When they explicitly reject a variant, call ~/.claude/skills/lrn/bin/LRN-taste-update rejected <variant-path>. The CLI handles schema migration from approved.json, decay, and conflict flagging.

Step 3: Generate Variants

Set up the output directory:

eval "$(echo "$_SLUG" 2>/dev/null)"
_DESIGN_DIR="$HOME/.lrn/projects/$SLUG/designs/<screen-name>-$(date +%Y%m%d)"
mkdir -p "$_DESIGN_DIR"
echo "DESIGN_DIR: $_DESIGN_DIR"

Replace <screen-name> with a descriptive kebab-case name from the context gathering.

Step 3a: Concept Generation

Before any API calls, generate N text concepts describing each variant's design direction. Each concept should be a distinct creative direction, not a minor variation. Present them as a lettered list:

I'll explore 3 directions:

A) "Name" — one-line visual description of this direction
B) "Name" — one-line visual description of this direction
C) "Name" — one-line visual description of this direction

Draw on DESIGN.md, taste memory, and the user's request to make each concept distinct.

Anti-convergence directive (hard requirement): Each variant MUST use a different font family, color palette, and layout approach. If two variants look like siblings — same typographic feel, overlapping color temperature, comparable layout rhythm — one of them failed. Regenerate the weaker one with a deliberately different direction.

Concrete test: if someone could swap the headline text between two variants without noticing, they're too similar. Variants should feel like they came from three different design teams, not the same team at three different coffee levels.

Step 3b: Concept Confirmation

Use AskUserQuestion to confirm before spending API credits:

"These are the {N} directions I'll generate. Each takes ~60s, but I'll run them all in parallel so total time is ~60 seconds regardless of count."

Options:

  • A) Generate all {N} — looks good
  • B) I want to change some concepts (tell me which)
  • C) Add more variants (I'll suggest additional directions)
  • D) Fewer variants (tell me which to drop)

If B: incorporate feedback, re-present concepts, re-confirm. Max 2 rounds. If C: add concepts, re-present, re-confirm. If D: drop specified concepts, re-present, re-confirm.

Step 3c: Parallel Generation

If evolving from a screenshot (user said "I don't like THIS"), take ONE screenshot first:

lp_screenshot "$_DESIGN_DIR/current.png"

Launch N Agent subagents in a single message (parallel execution). Use the Agent tool with subagent_type: "general-purpose" for each variant. Each agent is independent and handles its own generation, quality check, verification, and retry.

Important: $D path propagation. The $D variable from DESIGN SETUP is a shell variable that agents do NOT inherit. Substitute the resolved absolute path (from the DESIGN_READY: /path/to/design output in Step 0) into each agent prompt.

Agent prompt template (one per variant, substitute all {...} values):

Generate a design variant and save it.

Design binary: {absolute path to $D binary}
Brief: {the full variant-specific brief for this direction}
Output: /tmp/variant-{letter}.png
Final location: {_DESIGN_DIR absolute path}/variant-{letter}.png

Steps:
1. Run: {$D path} generate --brief "{brief}" --output /tmp/variant-{letter}.png
2. If the command fails with a rate limit error (429 or "rate limit"), wait 5 seconds
   and retry. Up to 3 retries.
3. If the output file is missing or empty after the command succeeds, retry once.
4. Copy: cp /tmp/variant-{letter}.png {_DESIGN_DIR}/variant-{letter}.png
5. Quality check: {$D path} check --image {_DESIGN_DIR}/variant-{letter}.png --brief "{brief}"
   If quality check fails, retry generation once.
6. Verify: ls -lh {_DESIGN_DIR}/variant-{letter}.png
7. Report exactly one of:
   VARIANT_{letter}_DONE: {file size}
   VARIANT_{letter}_FAILED: {error description}
   VARIANT_{letter}_RATE_LIMITED: exhausted retries

For the evolve path, replace step 1 with:

{$D path} evolve --screenshot {_DESIGN_DIR}/current.png --brief "{brief}" --output /tmp/variant-{letter}.png

Why /tmp/ then cp? In observed sessions, $D generate --output $_MEM/... failed with "The operation was aborted" while --output /tmp/... succeeded. This is a sandbox restriction. Always generate to /tmp/ first, then cp.

Step 3d: Results

After all agents complete:

  1. Read each generated PNG inline (Read tool) so the user sees all variants at once.
  2. Report status: "All {N} variants generated in ~{actual time}. {successes} succeeded, {failures} failed."
  3. For any failures: report explicitly with the error. Do NOT silently skip.
  4. If zero variants succeeded: fall back to sequential generation (one at a time with $D generate, showing each as it lands). Tell the user: "Parallel generation failed (likely rate limiting). Falling back to sequential..."
  5. Proceed to Step 4 (comparison board).

Dynamic image list for comparison board: When proceeding to Step 4, construct the image list from whatever variant files actually exist, not a hardcoded A/B/C list:

setopt +o nomatch 2>/dev/null || true  # zsh compat
_IMAGES=$(ls "$_DESIGN_DIR"/variant-*.png 2>/dev/null | tr '\n' ',' | sed 's/,$//')

Use $_IMAGES in the $D compare --images command.

Step 4: Comparison Board + Feedback Loop

Comparison Board + Feedback Loop

Create the comparison board and serve it over HTTP:

$D compare --images "$_DESIGN_DIR/variant-A.png,$_DESIGN_DIR/variant-B.png,$_DESIGN_DIR/variant-C.png" --output "$_DESIGN_DIR/design-board.html" --serve

This command generates the board HTML, starts an HTTP server on a random port, and opens it in the user's default browser. Run it in the background with & because the server needs to stay running while the user interacts with the board.

Parse the board URL from stderr output. Default daemon path: BOARD_URL: http://127.0.0.1:N/boards/<id>/ (already includes the per-board path; use this for the AskUserQuestion URL AND as the base for the reload endpoint). Legacy --no-daemon path emits SERVE_STARTED: port=XXXXX and serves a single board at /, with reload at /api/reload — only relevant when an external caller explicitly passes --no-daemon.

PRIMARY WAIT: AskUserQuestion with board URL

After the board is serving, use AskUserQuestion to wait for the user. Include the board URL so they can click it if they lost the browser tab:

"I've opened a comparison board with the design variants: <BOARD_URL> — Rate them, leave comments, remix elements you like, and click Submit when you're done. Let me know when you've submitted your feedback (or paste your preferences here). If you clicked Regenerate or Remix on the board, tell me and I'll generate new variants."

Substitute <BOARD_URL> with the URL parsed from stderr (the daemon path emits BOARD_URL: http://127.0.0.1:N/boards/<id>/).

Do NOT use AskUserQuestion to ask which variant the user prefers. The comparison board IS the chooser. AskUserQuestion is just the blocking wait mechanism.

After the user responds to AskUserQuestion:

Check for feedback files next to the board HTML:

  • $_DESIGN_DIR/feedback.json — written when user clicks Submit (final choice)
  • $_DESIGN_DIR/feedback-pending.json — written when user clicks Regenerate/Remix/More Like This
if [ -f "$_DESIGN_DIR/feedback.json" ]; then
  echo "SUBMIT_RECEIVED"
  cat "$_DESIGN_DIR/feedback.json"
elif [ -f "$_DESIGN_DIR/feedback-pending.json" ]; then
  echo "REGENERATE_RECEIVED"
  cat "$_DESIGN_DIR/feedback-pending.json"
  rm "$_DESIGN_DIR/feedback-pending.json"
else
  echo "NO_FEEDBACK_FILE"
fi

The feedback JSON has this shape:

{
  "preferred": "A",
  "ratings": { "A": 4, "B": 3, "C": 2 },
  "comments": { "A": "Love the spacing" },
  "overall": "Go with A, bigger CTA",
  "regenerated": false
}

If feedback.json found: The user clicked Submit on the board. Read preferred, ratings, comments, overall from the JSON. Proceed with the approved variant.

If feedback-pending.json found: The user clicked Regenerate/Remix on the board.

  1. Read regenerateAction from the JSON ("different", "match", "more_like_B", "remix", or custom text)
  2. If regenerateAction is "remix", read remixSpec (e.g. {"layout":"A","colors":"B"})
  3. Generate new variants with $D iterate or $D variants using updated brief
  4. Create new board: $D compare --images "..." --output "$_DESIGN_DIR/design-board.html"
  5. Reload the board in the user's browser (same tab) — the URL is per-board under daemon mode, so use <BOARD_URL> (from the BOARD_URL: stderr line) as the base: curl -s -X POST "${BOARD_URL}api/reload" -H 'Content-Type: application/json' -d '{"html":"$_DESIGN_DIR/design-board.html"}' Under --no-daemon the reload endpoint is /api/reload at the legacy port; this path only matters if the caller explicitly opted out of the daemon.
  6. The board auto-refreshes. AskUserQuestion again with the same board URL to wait for the next round of feedback. Repeat until feedback.json appears.

If NO_FEEDBACK_FILE: The user typed their preferences directly in the AskUserQuestion response instead of using the board. Use their text response as the feedback.

POLLING FALLBACK: Only use polling if $D serve fails (no port available). In that case, show each variant inline using the Read tool (so the user can see them), then use AskUserQuestion: "The comparison board server failed to start. I've shown the variants above. Which do you prefer? Any feedback?"

After receiving feedback (any path): Output a clear summary confirming what was understood:

"Here's what I understood from your feedback: PREFERRED: Variant [X] RATINGS: [list] YOUR NOTES: [comments] DIRECTION: [overall]

Is this right?"

Use AskUserQuestion to verify before proceeding.

Save the approved choice:

echo '{"approved_variant":"<V>","feedback":"<FB>","date":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","screen":"<SCREEN>","branch":"'$(git branch --show-current 2>/dev/null)'"}' > "$_DESIGN_DIR/approved.json"

Step 5: Feedback Confirmation

After receiving feedback (via HTTP POST or AskUserQuestion fallback), output a clear summary confirming what was understood:

"Here's what I understood from your feedback:

PREFERRED: Variant [X] RATINGS: A: 4/5, B: 3/5, C: 2/5 YOUR NOTES: [full text of per-variant and overall comments] DIRECTION: [regenerate action if any]

Is this right?"

Use AskUserQuestion to confirm before saving.

Step 6: Save & Next Steps

Write approved.json to $_DESIGN_DIR/ (handled by the loop above).

If invoked from another skill: return the structured feedback for that skill to consume. The calling skill reads approved.json and the approved variant PNG.

If standalone, offer next steps via AskUserQuestion:

"Design direction locked in. What's next? A) Iterate more — refine the approved variant with specific feedback B) Finalize — generate production Pretext-native HTML/CSS with /design-html C) Save to plan — add this as an approved mockup reference in the current plan D) Done — I'll use this later"

Important Rules

  1. Never save to .context/, docs/designs/, or /tmp/. All design artifacts go to $_MEM/designs/. This is enforced. See DESIGN_SETUP above.
  2. Show variants inline before opening the board. The user should see designs immediately in their terminal. The browser board is for detailed feedback.
  3. Confirm feedback before saving. Always summarize what you understood and verify.
  4. Taste memory is automatic. Prior approved designs inform new generations by default.
  5. Two rounds max on context gathering. Don't over-interrogate. Proceed with assumptions.
  6. DESIGN.md is the default constraint. Unless the user says otherwise.

What ships with it

Read from the repository

Just SKILL.md. No reference files, no scripts.

Keep looking

Skills are one crate of 326,569. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.