by referodesign · MCP Server · ★ 116
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Refero Skill An agent skill that makes design research mandatory before implementation: styles-first visual research, real-screen pattern research, flow reasoning, reference locks, optional visual exploration, post-build QA, and craft guidance. When Refero MCP is available, it can use curated visual styles, 150,000+ real app screens, and 6,000+ user flows from Stripe, Linear, Notion, Figma, and the best-designed products ever built. Install Works with Claude Code, Cursor, Gemini CLI, Lovable, and any MCP-compatible agent. Craft knowledge loads immediately. No account required. Manual installation On Claude.ai, add the contents of to your project knowledge. What it does Researches styles, screens, and flows — starts with visual styles for taste and direction, then uses real screens and user flows for product patterns and journey logic when live Refero MCP tools are available. Extracts patterns — identifies specific design decisions and builds a reference list before touching code. Routes the workflow — goes directly to code for clear edits, or creates three reference-locked directions when exploration is valuable. Applies craft knowledge — u
| Stars | 116 |
| Forks | 9 |
| Category | MCP Server |
| License | MIT |
| Quality Score | 69.1970788661797/100 |
| Open Issues | 1 |
| Last Updated | 2026-06-10 |
| Created | 2026-02-05 |
| Platforms | claude-code, mcp |
| Est. Tokens | ~146k |
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refero_skill is Research-first design skill for AI agents. 150K+ real app screens and flows via Refero MCP.. It is categorized as a MCP Server with 116 GitHub stars.
You can find installation instructions and usage details in the refero_skill GitHub repository at github.com/referodesign/refero_skill. The project has 116 stars and 9 forks, indicating an active community.
refero_skill is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to refero_skill on Agent Skills Hub include claude-talk-to-figma-mcp, skillport, agnix. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.