skyboy ai

.github/CODEOWNERS

@@ -0,0 +1,14 @@
+# Default ownership for repository-wide changes.
+* @aijadugar
+
+# Domain ownership.
+/core/ @aijadugar
+/ai/ @aijadugar
+/ui/ @aijadugar
+/api/ @aijadugar
+/app/ @aijadugar
+/config/ @aijadugar
+/scripts/ @aijadugar
+/docs/ @aijadugar
+/tests/ @aijadugar
+/.github/ @aijadugar

README.md

@@ -1,51 +1,20 @@
-# Skyboy AI Patterns
+# Skyboy AI
 
-[![License: MIT](https://img.shields.io/badge/License-MIT-black.svg)](LICENSE) [![Stars](https://img.shields.io/github/stars/aijadugar/skyboy?style=social)](https://github.com/aijadugar/skyboy) [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-00D2FF.svg)](CONTRIBUTING.md)
+Skyboy AI is a pattern library for production AI systems. It keeps each pattern focused on working code, an architecture diagram, and references.
 
-> Production-ready patterns, architectures, and implementation guides for modern software and AI systems.
+## Development
 
-Skyboy AI Patterns is a copy-paste-first pattern library for engineers building AI systems in production. It focuses on working code, architecture diagrams, benchmarks, and tradeoffs for backend AI workflows: agents, retrieval, evaluation, deployment, MCP, and observability.
+```bash
+npm install
+npm run dev
+```
 
-<!-- screenshot -->
+Build the app with:
 
-## Quick Start
-
-1. Open [skyboy.in](https://skyboy.in) and search for the workflow you are building.
-2. Open a pattern, read the architecture and constraints, then copy the Python implementation.
-3. Adapt the code to your model provider, add the benchmark to your eval suite, and ship behind monitoring.
-
-## Why Skyboy AI Patterns?
-
-Most AI content explains concepts.
-
-Skyboy AI Patterns focuses on implementation.
-
-Every pattern includes:
-
-- Architecture diagrams
-- Production tradeoffs
-- Copy-paste code
-- Benchmarks and evaluation metrics
-- Real-world deployment guidance
-
-The goal is simple: help engineers ship AI systems faster.
-
-## Pattern Categories
-
-| Category | Count | Example |
-| --- | ---: | --- |
-| Agents | 3 | Router Agent |
-| RAG | 3 | Hybrid Search RAG |
-| Evaluations | 3 | LLM-as-Judge |
-| Fine-Tuning | 3 | LoRA Fine-Tuning |
-| Deployment | 3 | FastAPI Deployment |
-| MCP | 3 | MCP Server |
-| Observability | 3 | LLM Tracing |
-
-## Contributing
-
-Contributions should add practical patterns, benchmarks, examples, or maintenance fixes. Start with one focused change and include enough context for another engineer to validate it locally. See [CONTRIBUTING.md](CONTRIBUTING.md) for the pattern template, quality checklist, and PR process.
+```bash
+npm run build
+```
 
 ## License
 
-MIT License. Copyright 2025-2026 Skyboy AI Patterns.
+MIT