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Hermes Agent ☤
The self-improving AI agent built by Nous Research. It's the only agent with a built-in learning loop — it creates skills from experience, improves them during use, nudges itself to persist knowledge, searches its own past conversations, and builds a deepening model of who you are across sessions.
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The network for creativity
Join 1.25M professional creatives like you
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Creatives on Contra have earned over $150M and we are just getting started
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I built a design system generator inside Figma Make. Here's the workflow.
The problem I kept running into: every new client project meant re-explaining the brand to every AI tool from scratch. Figma Make didn't know the colors. Cursor didn't know the tokens. Claude didn't know the rules. I was the shared memory — and I kept losing things.
So I built Design System Gen. Entirely inside Figma Make. Powered by Claude API.
The workflow:
Upload brand references → Claude API analyzes them across 8 dimensions (palette, mood, typography, composition, lighting, texture, motion, UI DNA) → structured data, not vibes → generates 11 files, each formatted for a specific tool in your stack.
figma-make.md → paste once, Figma Make knows your entire design system
design-system.css → all tokens as CSS custom properties
tokens.json → W3C format, imports directly into Figma Variables
starter.tsx → React starter with tokens already bound
.cursorrules → Cursor knows your system from root
Claude.md → Claude reads it automatically every session
+ 5 more for docs, LLMs, prompts, components
Every tool gets its own context file. All consistent with each other.
The part I'm most proud of: I'm a designer. I don't write code. The entire tool — UI, API integration, file generation logic — was built and shipped inside Figma Make. No external hosting. No separate codebase.
Live at: vibecodingdsgen.figma.site
Add your Claude API key and try it with your own moodboard.
#FigmaMake #DesignSystem #VibeCoding #AI #Claude #UXUI #DesignSystems #ConfigMakeathon
As someone who constantly jumps between Figma, Claude, ChatGPT, Cursor, Lovable, and other AI tools, this problem feels very familiar 😅
The tools are getting smarter, but keeping context consistent is still surprisingly manual. Love seeing people tackle that gap.
Hiring 4,000 applicants every month isn't the hard part.
Managing them manually is.
Think about what happens when every candidate needs a response.
• Someone reviews applications.
• Someone sends interview invitations.
• Someone sends rejection emails.
• Someone assigns skills tests.
• Someone updates the CRM.
• Someone schedules interviews.
Now multiply that by thousands of applicants every month.
That's not recruitment.
Reject them? They receive a professional response while the CRM updates instantly.
Instead of relying on manual follow-ups, this recruitment workflow automates the entire process.
Approve a candidate? They automatically receive the next steps.
Reject them? They receive a professional response while the CRM updates instantly.
Need a skills assessment? It's sent automatically.
Ready for an interview? The invitation goes out without anyone writing another email.
The result isn't just faster hiring.
It's a hiring process that's consistent, scalable, and gives recruiters more time to focus on choosing the right people, not managing repetitive tasks.
The best automation isn't always the most impressive.
It's the one your team relies on every single day.
aiautomationbusinessautomationhrandrecruitmentEmail AutomationAI AutomationBusiness Workflow AutomationGo High LevelGoogle SheetsMake
This honestly saves time
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