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+# @ruvector/tiny-dancer
+
+Neural router for AI agent orchestration - FastGRNN-based intelligent routing with circuit breaker, uncertainty estimation, and hot-reload.
+
+## Features
+
+- **FastGRNN Neural Routing**: Efficient gated recurrent network for fast inference
+- **Uncertainty Estimation**: Know when the router is confident vs. uncertain
+- **Circuit Breaker**: Automatic fallback when routing fails repeatedly
+- **Hot-Reload**: Update models without restarting the application
+- **SIMD Optimized**: Native Rust performance with SIMD acceleration
+- **Multi-Platform**: Works on Linux, macOS, and Windows
+
+## Installation
+
+```bash
+npm install @ruvector/tiny-dancer
+```
+
+The package automatically installs the correct native binary for your platform.
+
+## Quick Start
+
+```typescript
+import { Router } from '@ruvector/tiny-dancer';
+
+// Create router with configuration
+const router = new Router({
+  modelPath: './models/fastgrnn.safetensors',
+  confidenceThreshold: 0.85,
+  maxUncertainty: 0.15,
+  enableCircuitBreaker: true,
+  circuitBreakerThreshold: 5
+});
+
+// Route a query to the best candidate
+const response = await router.route({
+  queryEmbedding: new Float32Array([0.1, 0.2, 0.3, ...]),
+  candidates: [
+    { id: 'gpt-4', embedding: new Float32Array([...]), successRate: 0.95 },
+    { id: 'claude-3', embedding: new Float32Array([...]), successRate: 0.92 },
+    { id: 'gemini', embedding: new Float32Array([...]), successRate: 0.88 }
+  ]
+});
+
+// Get the best routing decision
+const best = response.decisions[0];
+console.log(`Route to: ${best.candidateId}`);
+console.log(`Confidence: ${best.confidence}`);
+console.log(`Use lightweight: ${best.useLightweight}`);
+console.log(`Inference time: ${response.inferenceTimeUs}μs`);
+```
+
+## API Reference
+
+### `Router`
+
+Main class for neural routing.
+
+#### Constructor
+
+```typescript
+new Router(config: RouterConfig)
+```
+
+**RouterConfig:**
+| Property | Type | Default | Description |
+|----------|------|---------|-------------|
+| `modelPath` | string | required | Path to FastGRNN model file |
+| `confidenceThreshold` | number | 0.85 | Minimum confidence for routing |
+| `maxUncertainty` | number | 0.15 | Maximum uncertainty allowed |
+| `enableCircuitBreaker` | boolean | true | Enable fault tolerance |
+| `circuitBreakerThreshold` | number | 5 | Failures before circuit opens |
+| `enableQuantization` | boolean | true | Enable memory-efficient quantization |
+| `databasePath` | string | undefined | Optional persistence path |
+
+#### Methods
+
+##### `route(request: RoutingRequest): Promise<RoutingResponse>`
+
+Route a query to the best candidate.
+
+```typescript
+const response = await router.route({
+  queryEmbedding: new Float32Array([...]),
+  candidates: [{ id: 'model-1', embedding: new Float32Array([...]) }],
+  metadata: '{"context": "user-query"}'
+});
+```
+
+##### `reloadModel(): Promise<void>`
+
+Hot-reload the model from disk.
+
+```typescript
+await router.reloadModel();
+```
+
+##### `circuitBreakerStatus(): boolean | null`
+
+Check if the circuit breaker is closed (healthy) or open (unhealthy).
+
+```typescript
+const isHealthy = router.circuitBreakerStatus();
+```
+
+### Types
+
+#### `Candidate`
+
+```typescript
+interface Candidate {
+  id: string;                    // Unique identifier
+  embedding: Float32Array;       // Vector embedding
+  metadata?: string;             // JSON metadata
+  createdAt?: number;            // Timestamp
+  accessCount?: number;          // Usage count
+  successRate?: number;          // Historical success (0-1)
+}
+```
+
+#### `RoutingDecision`
+
+```typescript
+interface RoutingDecision {
+  candidateId: string;           // Which candidate to use
+  confidence: number;            // Confidence score (0-1)
+  useLightweight: boolean;       // Use fast/lightweight model
+  uncertainty: number;           // Uncertainty estimate (0-1)
+}
+```
+
+#### `RoutingResponse`
+
+```typescript
+interface RoutingResponse {
+  decisions: RoutingDecision[];  // Ranked decisions
+  inferenceTimeUs: number;       // Inference time (μs)
+  candidatesProcessed: number;   // Number processed
+  featureTimeUs: number;         // Feature engineering time (μs)
+}
+```
+
+## Use Cases
+
+### LLM Model Routing
+
+Route queries to the most appropriate language model:
+
+```typescript
+const router = new Router({ modelPath: './models/llm-router.safetensors' });
+
+const response = await router.route({
+  queryEmbedding: await embedQuery("Explain quantum computing"),
+  candidates: [
+    { id: 'gpt-4', embedding: gpt4Embedding, successRate: 0.95 },
+    { id: 'gpt-3.5-turbo', embedding: gpt35Embedding, successRate: 0.85 },
+    { id: 'claude-instant', embedding: claudeInstantEmbedding, successRate: 0.88 }
+  ]
+});
+
+// Use lightweight model for simple queries
+if (response.decisions[0].useLightweight) {
+  return callModel('gpt-3.5-turbo', query);
+} else {
+  return callModel(response.decisions[0].candidateId, query);
+}
+```
+
+### Agent Orchestration
+
+Route tasks to specialized AI agents:
+
+```typescript
+const agents = [
+  { id: 'code-agent', embedding: codeEmbedding, successRate: 0.92 },
+  { id: 'research-agent', embedding: researchEmbedding, successRate: 0.89 },
+  { id: 'creative-agent', embedding: creativeEmbedding, successRate: 0.91 }
+];
+
+const best = (await router.route({ queryEmbedding, candidates: agents })).decisions[0];
+await agents[best.candidateId].execute(task);
+```
+
+## Platform Support
+
+| Platform | Architecture | Package |
+|----------|--------------|---------|
+| Linux | x64 | `@ruvector/tiny-dancer-linux-x64-gnu` |
+| Linux | ARM64 | `@ruvector/tiny-dancer-linux-arm64-gnu` |
+| macOS | x64 | `@ruvector/tiny-dancer-darwin-x64` |
+| macOS | ARM64 | `@ruvector/tiny-dancer-darwin-arm64` |
+| Windows | x64 | `@ruvector/tiny-dancer-win32-x64-msvc` |
+
+## Performance
+
+- **Inference**: < 100μs per routing decision
+- **Throughput**: 10,000+ routes/second
+- **Memory**: ~10MB base + model size
+
+## Related Packages
+
+- [`@ruvector/core`](https://www.npmjs.com/package/@ruvector/core) - Vector database
+- [`@ruvector/gnn`](https://www.npmjs.com/package/@ruvector/gnn) - Graph Neural Networks
+- [`@ruvector/graph-node`](https://www.npmjs.com/package/@ruvector/graph-node) - Hypergraph database
+
+## License
+
+MIT