award-design
Award Design
Build websites that score 8+ on Awwwards. AI-generated designs are immediately recognizable to experienced judges and score poorly — this skill exists to beat that.
Workflow
- Understand the brief: What is being built? For whom? What must it communicate? What's the one thing someone will remember? If
-u <url>was passed, readreferences/brand-extraction.mdfirst and reverse-engineer a DESIGN.md observation from the live site — that observation seeds the archetype recommendation in step 2, it doesn't replace the brief. - Recommend an archetype: Analyze the brief and recommend the single best archetype from the table below. Present it with:
- The archetype name and its signature trait
- Why it fits this brief specifically (not generic reasoning)
- The default Density/Variance/Motion scores
- Ask the user to validate before proceeding. Do not continue until confirmed.
- If the user wants to explore alternatives, present all 9 archetypes as a compact list:
- Minimalist — extreme whitespace, typography carries everything
- Brutalist — thick borders, flat colors, deliberate anti-polish
- Editorial — serif + sans-serif pairing, magazine grids, pull quotes
- Bold / Maximal — organized chaos, kinetic typography as art
- Immersive / Cinematic — full-screen video, WebGL 3D, dark backgrounds
- Experimental — bespoke, no template, creative coding, mixed media
More from coroboros/agent-skills
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19design-system
Govern the DESIGN.md — Google's open standard for design tokens (YAML frontmatter + eight prose sections). Auto-activates during UI edits to enforce token-only sourcing for colors, typography, spacing, and corner radius. Also exposes six CLI-backed subcommands — audit (lint + fix proposals), diff (regression check), export (Tailwind / DTCG), spec (canonical spec emission), migrate (port from legacy Stitch format), init (minimal scaffold). When a UI/UX change is requested, DESIGN.md is updated first, audited, then code propagates.
4write-clear-readme
Author, audit, or polish a project README — clarity, structure (Pattern A grouped collapse / Pattern B per-entry collapse), wording concision, anchor integrity. Reads the repo first, proposes diffs, applies on approval.
4humanize-en
Strip AI writing tells from English prose — em-dash overuse, rule of three, negative parallelisms, AI vocabulary (delve, tapestry, crucial, pivotal, underscore, showcase), vague attributions, promotional tone, conjunctive padding (moreover, furthermore, indeed), hedging, signposting, chatbot artifacts. Preserves meaning, structure, code blocks, links, anchors, and frontmatter — rewrites only the flagged phrasing. Operates on inline text or a prose file path. Optionally loads a `BRAND-VOICE.md` via `-f` (produced by `/brand-voice`) to apply brand-specific rules on top of the universal patterns. Based on Wikipedia's Signs of AI writing (canonical taxonomy) with pattern extensions and the voice-calibration approach from github.com/blader/humanizer.
3fix-grammar
Fix grammar, spelling, and typos in files while preserving formatting, meaning, and technical terms. Corrections only — no rephrasing, no style improvements, no translation.
3apex
Systematic implementation using APEX methodology (Analyze-Plan-Execute-eXamine) with parallel subagents and self-validation. Use when implementing features, fixing bugs, or making code changes that benefit from structured workflow.
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