styleseed
Reduces UI design debt and iteration cycles by providing battle-tested components and design rules that enforce consistency across AI-generated interfaces, c…
Design engine for Claude Code, Codex, and Cursor that teaches design judgment instead of just supplying components: 74 design rules, 48 shadcn components, and brand skins (Toss, Stripe, Linear, Vercel, Notion) built on Tailwind v4 and Radix. Aims to stop AI-generated UI from looking generic.
- Generate polished UI components that match your company's design system instantly.
- Apply Stripe or Linear brand styles to AI-generated interfaces without manual redesign.
- Build consistent dashboards using 48 pre-built shadcn components with Tailwind styling.
Reduces UI design debt and iteration cycles by providing battle-tested components and design rules that enforce consistency across AI-generated interfaces, cutting handoff friction with design teams.
Product engineers and AI tool builders shipping UIs quickly without dedicated design resources or design review bottlenecks.
https://github.com/bitjaru/styleseed
By bitjaru
How to Get It
claude plugins install bitjaru/styleseed
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Help me generate polished UI components that match my company's design system instantly
Trust Signals Auto-scanned
Community Pulse Active
Discussed on Hacker News, Reddit
- StyleSeed – Design rules that make AI coding tools produce professional UI — Hacker News · 1 pts
1 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 359 GitHub stars; contributors unknown; last commit 1d ago; license MIT.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 359 GitHub stars; contributors unknown; last commit 1d ago; license MIT.