/neural-network
Train and deploy neural networks in distributed sandboxes
$ npx -y skills add ruvnet/agentic-flow --agent claude-codeHow it fires
How this command gets triggered: by you, by Claude, or both.
- Fires itselfClaude auto-loads it when your prompt matches the work.
- You can call itInvoke it directly when you want it.
- Slash command
/neural-network
Context preview
What this command does when you run it.
Train and deploy neural networks in distributed sandboxes
Command definition
neural-network.mdname: flow-nexus-neural
description: Train and deploy neural networks in distributed sandboxes
Flow Nexus Neural Networks
Train custom neural networks with distributed computing.
Train Model
mcp__flow-nexus__neural_train({
config: {
architecture: {
type: "feedforward", // lstm, gan, autoencoder, transformer
layers: [
{ type: "dense", units: 128, activation: "relu" },
{ type: "dropout", rate: 0.2 },
{ type: "dense", units: 10, activation: "softmax" }
]
},
training: {
epochs: 100,
batch_size: 32,
learning_rate: 0.001,
optimizer: "adam"
}
},
tier: "small" // nano, mini, small, medium, large
})Run Inference
mcp__flow-nexus__neural_predict({
model_id: "model_id",
input: [[0.5, 0.3, 0.2], [0.1, 0.8, 0.1]],
user_id: "your_id"
})Use Templates
// List templates
mcp__flow-nexus__neural_list_templates({
category: "classification", // regression, nlp, vision, anomaly
tier: "free",
limit: 20
})
// Deploy template
mcp__flow-nexus__neural_deploy_template({
template_id: "sentiment-analysis",
custom_config: {
training: { epochs: 50 }
}
})Distributed Training
// Initialize cluster
mcp__flow-nexus__neural_cluster_init({
name: "training-cluster",
architecture: "transformer",
topology: "mesh",
consensus: "proof-of-learning",
wasmOptimization: true
})
// Deploy nodes
mcp__flow-nexus__neural_node_deploy({
cluster_id: "cluster_id",
node_type: "worker", // parameter_server, aggregator
model: "large",
capabilities: ["training", "inference"]
})
// Start training
mcp__flow-nexus__neural_train_distributed({
cluster_id: "cluster_id",
dataset: "mnist",
epochs: 100,
federated: true // Enable federated learning
})Model Management
// List your models
mcp__flow-nexus__neural_list_models({
user_id: "your_id",
include_public: true
})
// Benchmark performance
mcp__flow-nexus__neural_performance_benchmark({
model_id: "model_id",
benchmark_type: "comprehensive"
})
// Publish as template
mcp__flow-nexus__neural_publish_template({
model_id: "model_id",
name: "My Custom Model",
description: "Highly accurate classifier",
category: "classification",
price: 0 // Free template
})Common Patterns
Image Classification
mcp__flow-nexus__neural_train({
config: {
architecture: { type: "cnn" },
training: { epochs: 50, batch_size: 64 }
},
tier: "medium"
})Time Series Prediction
mcp__flow-nexus__neural_train({
config: {
architecture: { type: "lstm" },
training: { epochs: 100, learning_rate: 0.01 }
},
tier: "small"
})Read more
name: flow-nexus-neural description: Train and deploy neural networks in distributed sandboxes
Flow Nexus Neural Networks
Train custom neural networks with distributed computing.
Train Model
mcp__flow-nexus__neural_train({
config: {
architecture: {
type: "feedforward", // lstm, gan, autoencoder, transformer
layers: [
{ type: "dense", units: 128, activation: "relu" },
{ type: "dropout", rate: 0.2 },
{ type: "dense", units: 10, activation: "softmax" }
]
},
training: {
epochs: 100,
batch_size: 32,
learning_rate: 0.001,
optimizer: "adam"
}
},
tier: "small" // nano, mini, small, medium, large
})Run Inference
mcp__flow-nexus__neural_predict({
model_id: "model_id",
input: [[0.5, 0.3, 0.2], [0.1, 0.8, 0.1]],
user_id: "your_id"
})Use Templates
// List templates
mcp__flow-nexus__neural_list_templates({
category: "classification", // regression, nlp, vision, anomaly
tier: "free",
limit: 20
})
// Deploy template
mcp__flow-nexus__neural_deploy_template({
template_id: "sentiment-analysis",
custom_config: {
training: { epochs: 50 }
}
})Distributed Training
// Initialize cluster
mcp__flow-nexus__neural_cluster_init({
name: "training-cluster",
architecture: "transformer",
topology: "mesh",
consensus: "proof-of-learning",
wasmOptimization: true
})
// Deploy nodes
mcp__flow-nexus__neural_node_deploy({
cluster_id: "cluster_id",
node_type: "worker", // parameter_server, aggregator
model: "large",
capabilities: ["training", "inference"]
})
// Start training
mcp__flow-nexus__neural_train_distributed({
cluster_id: "cluster_id",
dataset: "mnist",
epochs: 100,
federated: true // Enable federated learning
})Model Management
// List your models
mcp__flow-nexus__neural_list_models({
user_id: "your_id",
include_public: true
})
// Benchmark performance
mcp__flow-nexus__neural_performance_benchmark({
model_id: "model_id",
benchmark_type: "comprehensive"
})
// Publish as template
mcp__flow-nexus__neural_publish_template({
model_id: "model_id",
name: "My Custom Model",
description: "Highly accurate classifier",
category: "classification",
price: 0 // Free template
})Common Patterns
Image Classification
mcp__flow-nexus__neural_train({
config: {
architecture: { type: "cnn" },
training: { epochs: 50, batch_size: 64 }
},
tier: "medium"
})Time Series Prediction
mcp__flow-nexus__neural_train({
config: {
architecture: { type: "lstm" },
training: { epochs: 100, learning_rate: 0.01 }
},
tier: "small"
})Production-ready AI agent orchestration with 66 self-learning agents, 213 MCP tools, and autonomous multi-agent swarms.
Repo: ruvnet/agentic-flow
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