Accessibility Compliance
Implement WCAG 2.2 compliant interfaces with mobile accessibility, inclusive design patterns…
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Browse the full catalog → Browse ready-made kits → Build your own set →AI-uretilmis "slop" tasarimi (generic hero + 3 kolonlu feature + gradient blob + stock…
Detect the 'AI slop' smell in a design: generic hero gradient blobs, three-column feature grids, stock-photo teams, lorem-ipsum verbs like 'Empower your business': and replace it with craft-driven, reference-based work. It runs a twelve-pattern audit (seven or more matches equals an AI-slop verdict), then rebuilds with real-product benchmarks instead of imagination, variable-font typography tension and a tight constraint set.
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Gradient blob hero, three icon columns, Empower and Transform in the copy: recognize it? A 12-pattern rubric scores the slop, real product screens replace imagination as the source, and one surgical fix lands per iteration until the verdict flips.
taste-skill-anti-cookie-cutter · core
core active · 6 lines
Auditing a landing page that 'looks amateur' or 'AI-generated'
Replacing a cookie-cutter hero with a craft-driven alternative
Pulling real-product benchmarks before designing from scratch
Running a three-iteration craft loop with surgical fixes
Setting a constraint config (5 colors, 2 fonts, 3 radii, 2 shadows)
Catching slop automatically in CI with a pattern-detection gate
Drag time forward. Watch what stays.
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Turn 'it looks AI-made' rejection into a measurable, fixable verdict
license: perpetualReplace imagination with real-product references so output stops reading generic
license: perpetualBuild typography tension that signals craft instead of a single dead font weight
license: perpetualCut iteration waste by catching slop before the design reaches review
license: perpetualsubscriptions expire · deeds don't
Pick a piece up. Watch it work.
A twelve-pattern detection rubric with a slop-verdict threshold
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From the field · a real case
Designers and teams who keep landing on the same generic template and need to make output read like a professional product, not AI output.
then this was forged for you.Universal by design: these run in any AI. Delivered in the open Agent Skills + MCP format (native in Claude); ChatGPT, Gemini, Cursor and Copilot adapt the same files their own way.
Exactly that. The vague 'looks AI-made' reaction gets converted into a twelve-pattern audit, gradient blobs, three-column feature grids, stock-photo teams, dead font weight, where seven or more matches equals a slop verdict. Once the problem is measurable, the rebuild path is concrete instead of another blind redesign.
By auditing patterns, not feelings. The rubric checks twelve concrete slop signatures, then rebuilds with real-product benchmarks pulled before designing, a constraint config capping the palette at 5 colors, 2 fonts, 3 radii and 2 shadows, and variable-font typography tension. A three-iteration loop with surgical fixes replaces endless full redesigns.
No. It diagnoses slop, supplies references, constraints, and the iteration discipline, but the design work still happens in your hands and tools. It also includes a CI taste-audit gate, which catches regressions automatically, yet it cannot invent a brand identity where none exists.
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