🚀 MoCo Prompts — Curated Prompt Library for Developers & Creators
Modern, web-based prompt library built to help developers, designers, analysts, and creators find the right prompt, faster.
🌍 The Problem
AI tools like ChatGPT, Claude, Cursor, and Lovable are rapidly evolving, becoming smarter and easier to use. But for complex, long-term, or specialized tasks, users still need well-engineered, reusable prompts.
The challenge:
- Scattered prompt resources across forums and docs.
- Poorly structured, hard-to-search collections.
- No easy way for professionals to quickly find high-quality prompts tailored to real workflows.
💡 The Solution — MoCo Prompts
MoCo Prompts is a modern, web-based prompt library built to help developers, designers, analysts, and creators find the right prompt, faster.
Curated Collections
100+ prompts across domains like Python Development, Data Analysis, Marketing, UX/Product Design, and Visual AI.
Smart Categorization
Task-based, role-based, and domain-specific tags.
Minimalist Design
Built with React + Vite + Tailwind for a lightweight, fast, and clean interface.
One-Click Copy
Prompts are instantly usable across any AI tool.
🎯 Target Users
MoCo Prompts is designed for:
Software Developers
Debugging, refactoring, code generation.
Data Analysts & BI Teams
SQL queries, dashboards, statistical modeling.
Marketing & Content Teams
Campaign copy, SEO, social posts.
Product & UX Designers
Wireframes, personas, UX copywriting.
AI Creators & Innovators
Visual storytelling, multimodal exploration.
📂 Categorization Strategy
To ensure ease of discovery, prompts are structured under:
By Domain
Development, Data, Marketing, UX, Visual AI.
By Task
Debugging, Analysis, Ideation, Content Creation, Research.
By Skill Level
Beginner-friendly → Advanced use cases.
By Context
Quick daily tasks → Deep project workflows.
🔧 My Role & Approach
This project allowed me to combine my design thinking and vibe coding skills into a fast prototype.
UX Design
Information architecture, categorization framework, and microcopy.
UI Design
Clean bento-grid inspired layouts, Apple-style typography, and lightweight interactions.
Development
React + Vite + Tailwind CSS with attention to performance and accessibility.
Problem Solving
Mapping user needs to structured workflows for effective prompt retrieval.
✨ Key Features
Quick Search & Filters
Instantly locate prompts by tags or categories.
Pre-Built Collections
Task-based sets for Python, SQL, UX, and Marketing.
One-Click Copy
No clutter, just copy-paste and go.
Modern UI
Minimal, responsive, with a clean grid-based layout.
⚙️ Behind the Scenes - Admin & System Features
Building a scalable prompt library required thoughtful admin tools and system design.
Copy Abuse Protection
Rate limiting and monitoring to prevent misuse of the copy feature.
Community Requests
User-driven prompt requests and community curation features.
📊 Impact
By bridging AI accessibility and real workflow needs, MoCo Prompts:
- •Saves time for professionals across domains.
- •Encourages better reuse of knowledge instead of reinventing prompts.
- •Demonstrates the power of design + coding in solving emerging AI usability challenges.
🌟 Reflection
This project taught me how prompt engineering itself requires UX thinking. A prompt is a product. Organizing, categorizing, and making them discoverable is just as important as writing them well.
MoCo Prompts was my experiment in building something that's not just functional, but delightful to use.