* skill: drop quality tiers, keep the real brand-craft guardrails Codex's craft/brand pass introduced fast/ship/showpiece "quality bars" plus brand-specific build gates, asset ledgers, sub-agent review, and self-graded fallback labels. In practice those tiers became escape hatches rather than craft pressure: the final output should always be 10/10, and the real decision points are splashiness and maximalism, not quality. Removed: - All quality-bar / showpiece / fast / ship framing in shape.md and craft.md - Standalone Brand Direction (#4) and Asset Requirements (#10) sections in shape's brief; renumbered back to 1-10 - The Brand hard rules section in brand.md (folded its real prohibitions into the existing Imagery and Brand bans sections) - Brand-specific build-gate item, mock-fidelity bullet, production-bar bullet, present-step bullet in craft.md - Asset ledger ceremony in craft Step 4 - Review-only sub-agents and "self-reviewed fallback, not independently validated" machinery in craft.md and polish.md - The For brand surfaces, assess hard failures subsection in polish.md and the brand checklist row - tests/brand-showpiece-reference.test.mjs (and its package.json wiring) Kept (the real nuggets): - Asset-substitution prohibition: image-led briefs ship real/generated assets or canvas/SVG/WebGL, not generic CSS panels, cards, bullets, or copy - Repeated tiny uppercase tracked kicker labels as a brand ban - Detector/QA output is defect evidence only, never proof of quality - "What visual assets are real content here?" discovery question - Inspect each major section individually for brand and long-form work - repeated-section-kickers detection rule + fixture - CLI improvements (JSON to stdout, -json/-fast aliases, severity field) - critique.md: npx impeccable detect --json fix Harness output dirs refreshed via bun run build. Full test suite (186) passes. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * skill: strip gate ceremony; require shape pause; allow compact briefs The setup gate table and IMPECCABLE_PREFLIGHT banner pushed every craft run through ritual restatement (PRODUCT.md → original prompt → round 1 → round 2 → 70-line "confirmed brief" → critique → summary, all saying the same thing). Replaced with imperative prose that still demands the same work but skips the user-facing telemetry. Specifically: SKILL.md - Drop the Setup gate table and IMPECCABLE_PREFLIGHT banner. - Keep the imperative steps explicitly: load context, identify register and load brand.md or product.md, AND load the matching command reference (craft.md / shape.md / etc.) when a sub-command is invoked. The command-reference step is non-negotiable; without craft.md loaded the agent skips the shape-and-confirm pause. craft.md - Drop the Build Gate / Craft Contract formal sections; replace with one paragraph stating prerequisites. - Step 1 explicitly requires ending the response after presenting the shape output; the user must confirm before any code lands. Allows a compact 3-5 bullet brief when the prompt + PRODUCT.md already pin direction (full 10-section structure reserved for genuinely ambiguous tasks). - Step 3 image gate skips silently when image generation isn't natively available; no user-facing announcement. - Step 6 explicitly legitimizes "first pass clean, shipping" as a valid endpoint and bans inventing fake defects to demonstrate iteration. shape.md - Cap discovery at 1 round by default; second round only when first leaves material gaps. - Adds an "assert-then-confirm, not menu-with-escape" rule: when PRODUCT.md and the prompt make one option obvious, name it and ask for confirm or override instead of enumerating "Restrained / Committed / Or something else?" as a real choice. - Phase 2 brief has two forms now: compact (default for clear briefs) and full structured (genuinely ambiguous). Open Questions can't double as leading-with-Recommend; if you'd write "Recommend: X", decide X. - Image gate same as craft.md. Validated end-to-end with a Haiku skill-on observability run: agent loads craft.md plus the brief's recommended implementation refs, pauses for one productive question (accent color, trace fidelity, CTA), and ships an artifact with zero side-tab violations vs. the original v1 baseline. Cost trades up modestly for that quality. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * craft.md Step 6: Reading the screenshot is the inspection, not taking it A v4 eval run took 4 targeted screenshots (hero, mobile, tablet, query-section) and then never Read any of them back. The agent treated browser_screenshot itself as "I inspected" and shipped without the multimodal feedback loop ever closing. Detector caught the resulting slop (5+ side-tab violations) on adjacent runs that did the same thing. Step 6 now spells out the pattern explicitly: take the screenshot, then Read the resulting PNG so its image content enters the conversation as multimodal input, then critique what you actually see in the image. With a check: "if your critique could have been written without looking at the image, you didn't look at the image." Validated with v5b: agent took 6 screenshots, Read all 6 back, and shipped with zero detector findings (vs the previous greenfield runs that hit 1-12 findings each). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * craft + brand: framework foundation, build-pipeline respect, image verification Three closely-linked additions surfaced by an eval-harness session investigating why the agent always shipped flat single-file HTML and zero imagery on greenfield brand briefs. 1. craft.md gains a new Step 0 "Project Foundation" before Shape. Detects existing framework / component library / icon set and uses what's there. Greenfield: ask the user via AskUserQuestion with sensible defaults framed by the brief (Astro for content/ brand sites, SvelteKit/Next/Nuxt for app surfaces, single index.html only for one-shot demos). Skipping the framework decision and writing flat HTML "to satisfy the spec" produces work that reads as a 2018 prototype regardless of visual quality. 2. craft.md Step 5 production bar gains two bullets: - Respect the build pipeline. Edit source files and run the project's `npm run build`; do not write to build/ / dist/ / .next/ directly with cat/heredoc/Bash redirects. Bypassing the pipeline skips asset hashing, image optimization, code splitting, and CSS extraction. - Verify external image URLs before referencing them. Use an image-search MCP, web-fetch tool, or browser if available; guessed photo IDs ship as broken-image placeholders. 3. brand.md "Imagery" section: - Generalizes the Unsplash URL guidance to "verify URLs before referencing them" with a hierarchy: image-search MCP > web-fetch > confidence-restricted manual selection > fewer photos. - Tightens the tech/dev-tool exception. Old line "zero imagery can be correct" gave models a permission slip. New framing keeps the underlying truth (typography + code + diagrams primarily carry voice) but raises the floor: imagery still earns its place when it serves the brief, and skipping it requires naming the typographic/diagrammatic move that's carrying the visual weight instead. "Zero imagery is the failure mode of laziness, not restraint." Eval-harness corpus that prompted this: 19/19 brand landing tasks shipped 0 images each, including ones where Opus had taste enough to break the dev-tool color default lane. The skill needs to teach both halves of the decision; the harness shouldn't have to nudge. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * detector: body-text-viewport-edge rule + OKLCH/var-resolution + anchor-inherit FP fixes New rule: body-text-viewport-edge flags body paragraphs that render flush against the left/right viewport edges (no container padding). Tested via the new tests/fixtures/antipatterns/body-text-viewport-edge.html fixture (3 flag cases, 5 pass cases) and the test in detect-antipatterns-browser. False-positive class fixes — all jsdom-mode only (real browsers resolve the cascade correctly so these gates stay inert there). Five related gaps that compounded into ~14× spurious contrast findings on Tailwind v4 pages with OKLCH color tokens: • OKLCH parser. jsdom returns the literal "oklch(...)" string from getComputedStyle; the detector now converts to sRGB via Björn Ottosson's matrices. Handles Tailwind v4's compact minified form "oklch(21.5%.02 50)" (no space after %). • var() resolution. resolveBackground + checkElementColors now accept the existing customPropMap and parse `var(--color-paper)` etc. as proper RGB via the new parseColorResolved helper. • bg-color before bg-image. The old order bailed on any gradient ancestor before checking for a solid background-color underneath, causing the body's decorative paper-grain gradient to be measured against instead of the page's actual `bg-paper` cream. • body/html-level gradient → white fallback. When the only opaque ancestor we can read is body/html with a gradient overlay (and jsdom can't decompose `background: var(--paper) gradient` to extract the solid color), return white instead of falling through to resolveGradientStops — which was picking up paper-grain noise colors and using them as the bg. • Anchor-inherit workaround for jsdom :link UA specificity. Tailwind v4's preflight declares `a { color: inherit }` (0,0,1). jsdom's UA stylesheet has `:link { color: blue }` at (0,1,1) and wins the cascade. Real Chrome wraps :link in :where() (0,0,0) so the page rule wins. When the page declares the inherit rule AND we see jsdom's default `rgb(0,0,238)` on an anchor, walk to the nearest non-anchor ancestor and use its color. • Alpha-fallback safety gate. When text has alpha<1 AND we couldn't find an opaque ancestor (effectiveBg null), skip the contrast finding. Covers any remaining FP class the deeper fixes miss. Verified end-to-end against an Opus iter-1 artifact on Tailwind v4 with 14 cream/cream FPs + 2 blue-link UA FPs before; 0 findings after, while the color.html fixture's 12 real low-contrast cases continue to flag (verified via direct detectHtml calls). cli/engine/detect-antipatterns-browser.js is the generated browser distribution — regenerated from .mjs via scripts/build-browser-detector.js (no manual edits to the generated file). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * craft.md: tighten verbose passages, de-codex Step 6, cut redundancies Cumulative reduction: 218 → 155 lines (-29%). Step 0: drop the "Why this matters" paragraph at the end. The body of Step 0 already makes the framework-pick point; the paragraph just re-explains it with extra rhetoric. Step 1: replace the 4-sentence "you must end your response" block with a single line. The original said the same thing three different ways. Step 3: trim the conditional / defensive scaffolding (Purpose subsection, "do not skip because the eventual UI is semantic..." paragraph, duplicated approval-loop guidance). Mock fidelity inventory preserved. Step 4: drop the "keep UI text semantic" sentence; it duplicates Step 5's "Semantic first" rule. The rasterized-vs-semantic decision rule stays. Step 5: tighten each production-bar bullet to bold-lead + specifics format. All 15 rules preserved (real content, mock ingredients, semantic first, spacing/alignment, typography, state coverage, interaction quality, icon set, build pipeline, image URL verification, optimized imagery, premium motion, maintainability, technical cleanliness, ask-when-uncertain). Step 6: rewrite around "look at what you built like a designer would — your eyes are whatever the harness gives you." Drops Codex-specific "In Codex, use browser-use" bias. Drops the verbose 3-step Read pattern (condensed to one sentence). Drops the 1-8 numbered checklist (replaced by a tight paragraph). Keeps the load-bearing rules: read the PNG, don't fabricate iteration, mock fidelity reference, exit bar = studio defensibility. Step 7: drop the closing "Iterate based on feedback. Good design is rarely right on the first pass" preachy filler. All em-dashes converted to semicolons / colons / periods to satisfy the skill prose validator. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * build: native subagent pipeline + Codex-only asset producer Adds an agent cross-compile pipeline alongside the existing skill pipeline. Sources live at skill/agents/*.md; providers that declare agentFormat (codex-toml, claude-md) emit native subagent files. An optional providers: <list> field on an agent gates which harnesses get a copy; default (no field) ships everywhere. The impeccable-asset-producer agent is opt-in to Codex only. It's useful for Codex's native image generation path and is untested elsewhere; Claude has no native image gen anyway. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * brand: inverse-test + cultural-symbol palette guardrail Two additions to the brand register reference: - Inverse slop test: describe the page the way a competitor would describe theirs. If that sentence fits the modal landing page in the category, restart. - Palette guardrail: when a cultural-symbol palette is the obvious pull, reach past it. Let cultural reading come from typography, imagery, and copy. Harness mirrors regenerated; some also catch up to the image- verification paragraph frome3ad2efthat hadn't been re-synced. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * PRODUCT.md: widen audience beyond developers Designers, product managers, and engineers all use AI coding tools and want better design output. Keeping the audience narrow to "frontend and full-stack developers" understates who the skill is actually for. Also retitles "developer" to "user/builder" in the purpose statement. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * site + build: bump rule count to 29, strip changelog from detector check Two changes: - site/pages/index.astro: three live mentions of "28 rules / checks" bumped to 29 after the body-text-viewport-edge rule landed inb9bf496. - scripts/build.js: the detection-count validator was reading the unstripped content, so historical counts inside changelog entries (e.g. "28 rules" from an older release note) were flagging against the current detector total. The command-count check already strips the changelog ul; the detection check now does the same. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> * test: align hero-eyebrow-chip fixture with relaxed rule gatesb9bf496intentionally relaxed two gates in checkHeroEyebrow: - removed the heading-size ≥ 48px anchor (modern hero h1s use clamp/vw/var that jsdom can't resolve) - raised the eyebrow text ceiling from 30 to 60 chars Two fixture cases that satisfied the negative side of the old gates now match the rule: - "Body-Sized Heading Below Eyebrow" — 24px h1 with tracked-caps label above. Per the rule's stated intent ("a tiny tan label directly above any h1 is the antipattern regardless of how big the h1 ends up"), this is a flag. - "Long Uppercase Sentence Above Hero" — 46-char tracked-caps label is under the new 60-char ceiling, so still eyebrow-shaped. Both cases moved from the should-pass column to should-flag, with case descriptions rewritten to explain the gate they exercise. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Paul Bakaus <paulbakaus@pauls-mbp-3.lan> Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Shape the UX and UI for a feature before any code is written. This command produces a design brief: a structured artifact that guides implementation through discovery, not guesswork.
Scope: Design planning only. This command does NOT write code. It produces the thinking that makes code good.
Output: A design brief that can be handed off to {{command_prefix}}impeccable craft, or directly to {{command_prefix}}impeccable for freeform implementation. When visual direction probes are used, the images are supporting artifacts, not the primary output.
Philosophy
Most AI-generated UIs fail not because of bad code, but because of skipped thinking. They jump to "here's a card grid" without asking "what is the user trying to accomplish?" This command inverts that: understand deeply first, so implementation is precise.
Phase 1: Discovery Interview
Do NOT write any code or make any design decisions during this phase. Your only job is to understand the feature deeply enough to make excellent design decisions later.
This is a required interaction, not optional guidance. Ask these questions in conversation, adapting based on answers. Don't dump them all at once; have a natural dialogue. {{ask_instruction}}
Interview cadence
Discovery includes at least one user-answer round unless PRODUCT.md, DESIGN.md, or an already-confirmed brief directly answers the needed inputs. With a sparse prompt, do not synthesize a complete brief for confirmation on the first response.
- Use the harness's structured question tool when one exists. Otherwise, ask directly in chat and stop.
- Ask 2-3 questions per round, then wait for answers.
- Treat PRODUCT.md and DESIGN.md as anchors; they reduce repeated questions but do not replace shape for craft. Shape is task-specific.
- One round is the default. Add a second only if the first answers leave material gaps. Don't run a second round just to feel thorough.
- Round 1 should clarify purpose, audience/context, content/scope, and (for brand) visual direction.
- Round 2, when needed, fills in whatever's still genuinely missing.
Assert-then-confirm, not menu-with-escape. When PRODUCT.md and the user's prompt make one option obvious, name it and ask the user to confirm or override. Don't enumerate "Restrained / Committed / Or something else?" as a real choice; "This reads as Restrained, confirm?" beats a four-option menu when the answer is already clear.
Purpose & Context
- What is this feature for? What problem does it solve?
- Who specifically will use it? (Not "users"; be specific: role, context, frequency)
- What does success look like? How will you know this feature is working?
- What's the user's state of mind when they reach this feature? (Rushed? Exploring? Anxious? Focused?)
Content & Data
- What content or data does this feature display or collect?
- What are the realistic ranges? (Minimum, typical, maximum, e.g., 0 items, 5 items, 500 items)
- What are the edge cases? (Empty state, error state, first-time use, power user)
- Is any content dynamic? What changes and how often?
- What visual assets are real content here? Note required images, product shots, illustrations, maps, textures, diagrams, generated objects, or existing project assets.
Design Direction
Force a visual decision on three fronts. Skip anything PRODUCT.md or DESIGN.md already answers; ask only what's missing.
- Color strategy for this surface. Pick one: Restrained / Committed / Full palette / Drenched. Can override the project default if the surface earns it (e.g. a drenched hero inside an otherwise Restrained product).
- Theme via scene sentence. Write one sentence of physical context for this surface: who uses it, where, under what ambient light, in what mood. The sentence forces dark vs light. If it doesn't, add detail until it does.
- Two or three named anchor references. Specific products, brands, objects. Not adjectives like "modern" or "clean."
Scope
Always ask. Sketch quality and shipped quality are different outputs; don't guess between them.
- Fidelity. Sketch / mid-fi / high-fi / production-ready?
- Breadth. One screen / a flow / a whole surface?
- Interactivity. Static visual / interactive prototype / shipped-quality component?
- Time intent. Quick exploration, or polish until it ships?
Scope answers are task-scoped. Don't write them to PRODUCT.md or DESIGN.md; carry them through the design brief only.
Constraints
- Are there technical constraints? (Framework, performance budget, browser support)
- Are there content constraints? (Localization, dynamic text length, user-generated content)
- Mobile/responsive requirements?
- Accessibility requirements beyond WCAG AA?
Anti-Goals
- What should this NOT be? What would be a wrong direction?
- What's the biggest risk of getting this wrong?
Phase 1.5: Visual Direction Probe (Capability-Gated)
After the discovery interview, generate a small set of visual direction probes before writing the final brief when all of these are true:
- The work is net-new or directionally ambiguous enough that visual exploration will clarify the brief.
- The requested fidelity is mid-fi, high-fi, or production-ready. Skip for sketch-only planning.
- The current harness gives you native image generation (Codex's
image_gen, an equivalent MCP tool, or similar). Don't ask the user to install APIs or tooling.
When those conditions are met, this step is mandatory. If image generation isn't natively available, skip silently and proceed; don't announce the skip.
Use probes to explore visual lanes, not to replace the brief.
Do not skip probes because the final UI will be semantic, editable, code-native, responsive, or accessible. Those are implementation requirements, not reasons to avoid visual exploration.
What to generate
Generate 2 to 4 distinct direction probes based on the discovery answers, especially:
- Color strategy
- Theme scene sentence
- Named anchor references
- Scope and fidelity
The probes should differ in primary visual direction (hierarchy, topology, density, typographic voice, or color strategy), not just palette tweaks.
How to use the probes
- Treat them as direction tests, not final designs.
- Use them to pressure-test whether the brief is pointing at the right lane.
- Ask the user which direction feels closest, what feels off, and what should carry forward.
- If the probes reveal a mismatch, revise the brief inputs before finalizing the brief.
Important limits
- Do not skip discovery because image generation is available.
- Do not treat generated imagery as final UX specification, final copy, or final accessibility behavior.
- Do not use this step for minor refinements of existing work. It's for shaping a new surface or clarifying a big directional choice.
If image generation isn't natively available, skip this phase silently and proceed.
Phase 2: Design Brief
After the interview and any required probes, present a brief and end your response. The user must confirm before any implementation runs. Do not present a brief and then continue to code in the same response, even if the brief feels obvious to you. The user's confirmation is the gate.
Choose the brief shape based on how clear the answers are:
- Compact form (3-5 bullets) when discovery was crisp and the original prompt + PRODUCT.md already pinned scope, content, and direction. State what you're building, the visual lane, and end with one or two specific questions or a clear "confirm or override?" prompt. This is the default for typical craft requests with a clear prompt.
- Full structured form (sections below) when the task is genuinely ambiguous, multi-screen, or when the user asked for shape as a standalone step. Use this when the discipline of structure earns its weight.
Don't pad a clear brief into a long one to look thorough. A 70-line brief restating answers the user just gave is noise, not rigor. Equally, don't skip the confirmation pause to look efficient: the pause is the point.
If the user already said "approved" or "go" during discovery for the exact direction you'd present, that counts as confirmation; you may proceed without asking again. But if your brief adds anything the user hasn't seen and approved, you must stop and confirm.
Brief Structure
1. Feature Summary (2-3 sentences) What this is, who it's for, what it needs to accomplish.
2. Primary User Action The single most important thing a user should do or understand here.
3. Design Direction Color strategy (Restrained / Committed / Full palette / Drenched) + the theme scene sentence + 2–3 named anchor references. Reference PRODUCT.md and DESIGN.md where they already answer, and note any per-surface overrides.
If you ran the Visual Direction Probe step, name which probe direction won and what changed in the brief because of it.
4. Scope Fidelity, breadth, interactivity, and time intent from the Scope section of the interview. Task-scoped; these don't persist beyond the brief.
5. Layout Strategy High-level spatial approach: what gets emphasis, what's secondary, how information flows. Describe the visual hierarchy and rhythm, not specific CSS.
6. Key States List every state the feature needs: default, empty, loading, error, success, edge cases. For each, note what the user needs to see and feel.
7. Interaction Model How users interact with this feature. What happens on click, hover, scroll? What feedback do they get? What's the flow from entry to completion?
8. Content Requirements What copy, labels, empty state messages, error messages, and microcopy are needed. Note any dynamic content and its realistic ranges. For image-led surfaces, also list the required image/media roles and their likely source (project asset, generated raster, semantic SVG/CSS, canvas/WebGL, icon library, or accepted omission).
9. Recommended References Based on the brief, list which impeccable reference files would be most valuable during implementation (e.g., spatial-design.md for complex layouts, motion-design.md for animated features, interaction-design.md for form-heavy features).
10. Open Questions
Anything genuinely unresolved. Don't list "open questions" you've already recommended a default for; assert the default and move on. If you'd write Recommend: X next to a question, just decide X.
{{ask_instruction}}
If the user disagrees with any part, revisit the relevant discovery questions. A shape run is incomplete until the user confirms direction (or the user already gave a clear go during discovery, which counts).
Once confirmed, the brief is complete. The user can now hand it to {{command_prefix}}impeccable, or use it to guide any other implementation approach. (If the user wants the full discovery-then-build flow in one step, they should use {{command_prefix}}impeccable craft instead, which runs this command internally.)