Primary Functions
Customizable Agent Metrics: Focus your agents on specific trading strategies and metrics. Nova Agents offer unparalleled flexibility, allowing users to create trading strategies that match their specific goals and risk tolerance. Each agent can be configured to prioritize key metrics, such as smart wallets, transaction volumes, or token distribution patterns.
Personalized Insights: Adjust metrics to focus on areas like low cap tokens or trending markets.
Dynamic Settings: Adapt your agents to changing market conditions, ensuring optimal performance.
Complete Control: Define exactly how your agent analyzes data, from tracking developer activity to monitoring whale wallets.
Nova Agents give you the tools to build strategies as unique as your trading style.
use std::collections::HashMap;
// Represents trading metrics
#[derive(Debug)]
struct TradingMetrics {
smart_wallets: bool,
transaction_volume: bool,
token_distribution: bool,
developer_activity: bool,
whale_tracking: bool,
low_cap_tokens: bool,
trending_markets: bool,
}
// Trading agent with configurable strategy
struct TradingAgent {
name: String,
metrics: TradingMetrics,
risk_tolerance: f64, // Risk tolerance (0.0 = Low Risk, 1.0 = High Risk)
}
impl TradingAgent {
// Create a new trading agent
fn new(name: String, metrics: TradingMetrics, risk_tolerance: f64) -> Self {
TradingAgent {
name,
metrics,
risk_tolerance,
}
}
// Adjust metrics dynamically
fn adjust_metrics(&mut self, updated_metrics: TradingMetrics) {
self.metrics = updated_metrics;
println!(
"Updated metrics for agent '{}': {:?}",
self.name, self.metrics
);
}
// Analyze data based on selected metrics
fn analyze(&self) {
println!("Analyzing data for agent '{}':", self.name);
if self.metrics.smart_wallets {
println!(" Focusing on smart wallets.");
}
if self.metrics.transaction_volume {
println!(" Monitoring transaction volumes.");
}
if self.metrics.token_distribution {
println!(" Evaluating token distribution patterns.");
}
if self.metrics.developer_activity {
println!(" Tracking developer activity.");
}
if self.metrics.whale_tracking {
println!(" Monitoring whale wallet activities.");
}
if self.metrics.low_cap_tokens {
println!(" Analyzing low-cap tokens.");
}
if self.metrics.trending_markets {
println!(" Following trending markets.");
}
}
// Adjust risk tolerance dynamically
fn set_risk_tolerance(&mut self, risk: f64) {
self.risk_tolerance = risk;
println!(
"Risk tolerance for agent '{}' set to {:.2}.",
self.name, self.risk_tolerance
);
}
}
fn main() {
// Define initial metrics
let metrics = TradingMetrics {
smart_wallets: true,
transaction_volume: true,
token_distribution: false,
developer_activity: true,
whale_tracking: true,
low_cap_tokens: false,
trending_markets: true,
};
// Create a trading agent
let mut agent = TradingAgent::new("NovaBot".to_string(), metrics, 0.3);
// Analyze data based on initial configuration
agent.analyze();
// Update metrics dynamically
let updated_metrics = TradingMetrics {
smart_wallets: false,
transaction_volume: true,
token_distribution: true,
developer_activity: false,
whale_tracking: true,
low_cap_tokens: true,
trending_markets: false,
};
agent.adjust_metrics(updated_metrics);
// Re-analyze data based on updated metrics
agent.analyze();
// Update risk tolerance
agent.set_risk_tolerance(0.5);
}
Real-Time Execution: Leverage Nova Bot's speed for instant trade execution. Timing is everything in crypto trading, and Nova Agents ensure you’re never left behind. By integrating with Nova Bot’s lightning-fast infrastructure, agents execute trades in real time, eliminating delays and capitalizing on fleeting opportunities.
Precision Execution: Trades are processed instantly, minimizing slippage and securing the best prices.
Sniping Capability: Get into new token launches the moment they go live.
Seamless Automation: Agents act on pre-defined conditions, executing trades even when you’re not actively monitoring the market.
With Nova Agents, your trades move as fast as the market does.
use std::time::SystemTime;
// Represents a trade order
#[derive(Debug)]
struct TradeOrder {
token: String,
amount: f64,
price_limit: Option<f64>, // Optional price limit for precision execution
}
// Real-time trade execution agent
struct TradeAgent {
name: String,
sniping_mode: bool, // Enable sniping for token launches
automated_trading: bool, // Enable automation for pre-defined conditions
}
impl TradeAgent {
// Create a new trade agent
fn new(name: String, sniping_mode: bool, automated_trading: bool) -> Self {
TradeAgent {
name,
sniping_mode,
automated_trading,
}
}
// Execute a trade instantly
fn execute_trade(&self, order: TradeOrder) {
let timestamp = SystemTime::now();
println!(
"[{}] Executing trade for {}:\n Amount: {:.2} | Price Limit: {:?}\n Timestamp: {:?}",
self.name, order.token, order.amount, order.price_limit, timestamp
);
if let Some(limit) = order.price_limit {
println!(
" Precision execution: Ensuring price <= {:.2}.",
limit
);
}
println!(" Trade executed successfully.");
}
// Snipe a token launch
fn snipe_token(&self, token: &str) {
if self.sniping_mode {
println!(
"[{}] Sniping token launch for {}: Instant buy initiated!",
self.name, token
);
self.execute_trade(TradeOrder {
token: token.to_string(),
amount: 100.0, // Default amount for sniping
price_limit: None,
});
} else {
println!("Sniping mode is disabled.");
}
}
// Automate trades based on a condition
fn automate_trading(&self, condition: bool, order: TradeOrder) {
if self.automated_trading && condition {
println!("[{}] Automated condition met. Executing trade.", self.name);
self.execute_trade(order);
} else if !self.automated_trading {
println!("Automated trading is disabled.");
} else {
println!("Condition not met. No action taken.");
}
}
}
fn main() {
// Create a trade agent
let agent = TradeAgent::new("NovaAgent".to_string(), true, true);
// Instant trade execution
let order = TradeOrder {
token: "TokenX".to_string(),
amount: 500.0,
price_limit: Some(1.5), // Execute only if price <= 1.5
};
agent.execute_trade(order);
// Sniping a token launch
agent.snipe_token("NewTokenY");
// Automating trades
let automated_order = TradeOrder {
token: "TokenZ".to_string(),
amount: 300.0,
price_limit: None,
};
let market_condition = true; // Example condition
agent.automate_trading(market_condition, automated_order);
}
In-Depth Market Analysis: Access comprehensive insights into market trends and wallet activities. Nova Agents provide a complete view of the crypto landscape, offering actionable insights through powerful analytics. From token performance to market sentiment, you’ll have all the data you need to make informed decisions.
Comprehensive Data: Analyze on-chain activity, social trends, and liquidity to get the full picture.
Trend Spotting: Detect market shifts early, positioning yourself ahead of the competition.
Actionable Insights: Use deep analysis to identify undervalued assets or tokens poised for growth.
This feature turns complex market data into strategies you can trust.
use std::collections::HashMap;
// Market data structure
#[derive(Debug)]
struct MarketData {
token: String,
on_chain_activity: f64, // Transactions in the last 24 hours
social_mentions: u32, // Mentions across social platforms
liquidity: f64, // Available liquidity in the market
price_change: f64, // Price change percentage
}
// Nova Agent for market analysis
struct MarketAnalysisAgent {
name: String,
market_data: HashMap<String, MarketData>, // Token to market data mapping
}
impl MarketAnalysisAgent {
// Initialize the agent
fn new(name: String) -> Self {
MarketAnalysisAgent {
name,
market_data: HashMap::new(),
}
}
// Add or update market data
fn update_market_data(&mut self, data: MarketData) {
self.market_data.insert(data.token.clone(), data);
}
// Analyze comprehensive market data
fn analyze_market(&self) {
println!("[{}] Comprehensive Market Analysis:", self.name);
for (token, data) in &self.market_data {
println!(
"Token: {}\n On-Chain Activity: {:.2}\n Social Mentions: {}\n Liquidity: {:.2}\n Price Change: {:.2}%",
token, data.on_chain_activity, data.social_mentions, data.liquidity, data.price_change
);
if data.price_change > 10.0 {
println!(" Trend Spotting: Significant positive price movement detected!");
} else if data.price_change < -10.0 {
println!(" Trend Spotting: Potential bearish trend identified.");
}
if data.social_mentions > 1000 {
println!(" Actionable Insight: Token is trending on social platforms.");
}
if data.liquidity > 1_000_000.0 {
println!(" Actionable Insight: Token has high liquidity for secure trades.");
}
if data.on_chain_activity > 5000.0 && data.price_change < 5.0 {
println!(" Actionable Insight: Token shows high activity but limited price movement, possibly undervalued.");
}
}
}
}
fn main() {
// Initialize the market analysis agent
let mut agent = MarketAnalysisAgent::new("NovaAnalyzer".to_string());
// Example market data
agent.update_market_data(MarketData {
token: "TokenA".to_string(),
on_chain_activity: 8000.0,
social_mentions: 1500,
liquidity: 1_200_000.0,
price_change: 12.5,
});
agent.update_market_data(MarketData {
token: "TokenB".to_string(),
on_chain_activity: 3000.0,
social_mentions: 750,
liquidity: 500_000.0,
price_change: -8.0,
});
agent.update_market_data(MarketData {
token: "TokenC".to_string(),
on_chain_activity: 6000.0,
social_mentions: 2000,
liquidity: 2_000_000.0,
price_change: 3.0,
});
// Perform market analysis
agent.analyze_market();
}
Copy Trading: Follow and replicate the strategies of top traders. Trading like a pro has never been easier. Nova Agents simplify the process of following successful strategies by enabling users to replicate the trades of whales, influencers, or KOLs (Key Opinion Leaders).
Follow the Leaders: Select high-performing wallets or traders to mirror their strategies.
Adjustable Settings: Customize how closely your agent follows the chosen wallet’s activity.
Risk Mitigation: Use filters to avoid overly risky trades while still gaining exposure to high-potential opportunities.
Copy trading with Nova Agents democratizes access to elite trading strategies.
use std::collections::HashMap;
// Represents a trade made by a leader
#[derive(Debug)]
struct Trade {
token: String,
amount: f64,
price: f64,
timestamp: u64,
}
// Represents a leader's wallet
#[derive(Debug)]
struct LeaderWallet {
name: String,
trades: Vec<Trade>,
risk_level: f64, // Risk level (0.0 = low risk, 1.0 = high risk)
}
// Copy Trading Agent
struct CopyTradingAgent {
name: String,
followed_leaders: HashMap<String, LeaderWallet>, // Leader name to wallet data
risk_tolerance: f64, // User-defined risk tolerance
}
impl CopyTradingAgent {
// Create a new copy trading agent
fn new(name: String, risk_tolerance: f64) -> Self {
CopyTradingAgent {
name,
followed_leaders: HashMap::new(),
risk_tolerance,
}
}
// Follow a leader
fn follow_leader(&mut self, leader: LeaderWallet) {
self.followed_leaders.insert(leader.name.clone(), leader);
println!("[{}] Now following leader '{}'.", self.name, leader.name);
}
// Adjust risk tolerance dynamically
fn set_risk_tolerance(&mut self, risk: f64) {
self.risk_tolerance = risk;
println!(
"[{}] Risk tolerance set to {:.2}.",
self.name, self.risk_tolerance
);
}
// Replicate trades based on leader activity
fn replicate_trades(&self) {
println!("[{}] Replicating trades from followed leaders:", self.name);
for (leader_name, wallet) in &self.followed_leaders {
println!(" Leader: {}", leader_name);
for trade in &wallet.trades {
if wallet.risk_level <= self.risk_tolerance {
println!(
" Executing trade: Token: {} | Amount: {:.2} | Price: {:.2} | Timestamp: {}",
trade.token, trade.amount, trade.price, trade.timestamp
);
} else {
println!(
" Skipping trade: Token: {} | Risk level {:.2} exceeds tolerance {:.2}.",
trade.token, wallet.risk_level, self.risk_tolerance
);
}
}
}
}
}
fn main() {
// Initialize the copy trading agent
let mut agent = CopyTradingAgent::new("NovaCopyTrader".to_string(), 0.5);
// Example leader wallets
let leader1 = LeaderWallet {
name: "Whale123".to_string(),
trades: vec![
Trade {
token: "TokenA".to_string(),
amount: 1000.0,
price: 1.5,
timestamp: 1672531200,
},
Trade {
token: "TokenB".to_string(),
amount: 500.0,
price: 0.75,
timestamp: 1672531300,
},
],
risk_level: 0.4,
};
let leader2 = LeaderWallet {
name: "KOL456".to_string(),
trades: vec![
Trade {
token: "TokenC".to_string(),
amount: 1500.0,
price: 2.5,
timestamp: 1672531400,
},
Trade {
token: "TokenD".to_string(),
amount: 700.0,
price: 1.2,
timestamp: 1672531500,
},
],
risk_level: 0.7,
};
// Follow leaders
agent.follow_leader(leader1);
agent.follow_leader(leader2);
// Replicate trades
agent.replicate_trades();
// Adjust risk tolerance
agent.set_risk_tolerance(0.6);
// Replicate trades again with updated tolerance
agent.replicate_trades();
}
Automated Alerts: Receive notifications on significant market shifts and opportunities. Never miss an opportunity with Nova Agents’ automated alert system. Stay informed with instant notifications about market movements, wallet activities, or triggered conditions.
Custom Triggers: Set alerts for price changes, volume spikes, or new token launches.
Real-Time Updates: Receive notifications the moment critical conditions are met.
Actionable Info: Use alerts to react quickly, whether it’s entering a trade or pulling out of a position.
With automated alerts, Nova Agents keep you in the loop 24/7.
use std::time::{SystemTime, UNIX_EPOCH};
// Alert types
enum AlertType {
PriceChange { token: String, percentage: f64 },
VolumeSpike { token: String, threshold: f64 },
NewTokenLaunch { token: String },
}
// Represents an alert
struct Alert {
alert_type: AlertType,
triggered: bool,
timestamp: Option<u64>,
}
// Automated Alerts System
struct AlertSystem {
alerts: Vec<Alert>,
}
impl AlertSystem {
// Initialize the alert system
fn new() -> Self {
AlertSystem { alerts: Vec::new() }
}
// Add a new alert
fn add_alert(&mut self, alert_type: AlertType) {
self.alerts.push(Alert {
alert_type,
triggered: false,
timestamp: None,
});
}
// Check and trigger alerts based on market data
fn check_alerts(&mut self, market_data: &MarketData) {
for alert in &mut self.alerts {
match &alert.alert_type {
AlertType::PriceChange { token, percentage } => {
if &market_data.token == token
&& market_data.price_change.abs() >= *percentage
{
self.trigger_alert(alert);
}
}
AlertType::VolumeSpike { token, threshold } => {
if &market_data.token == token && market_data.volume >= *threshold {
self.trigger_alert(alert);
}
}
AlertType::NewTokenLaunch { token } => {
if &market_data.token == token && market_data.is_new_token {
self.trigger_alert(alert);
}
}
}
}
}
// Trigger an alert
fn trigger_alert(&mut self, alert: &mut Alert) {
if !alert.triggered {
alert.triggered = true;
alert.timestamp = Some(
SystemTime::now()
.duration_since(UNIX_EPOCH)
.unwrap()
.as_secs(),
);
self.display_alert(alert);
}
}
// Display the alert
fn display_alert(&self, alert: &Alert) {
match &alert.alert_type {
AlertType::PriceChange { token, percentage } => {
println!(
"🚨 Price Change Alert: {} has changed by {:.2}%!",
token, percentage
);
}
AlertType::VolumeSpike { token, threshold } => {
println!(
"🚨 Volume Spike Alert: {} has exceeded a volume of {:.2}!",
token, threshold
);
}
AlertType::NewTokenLaunch { token } => {
println!("🚨 New Token Launch Alert: {} is now available!", token);
}
}
if let Some(timestamp) = alert.timestamp {
println!("Triggered at: {}", timestamp);
}
}
}
// Market data structure
struct MarketData {
token: String,
price_change: f64, // Price change percentage
volume: f64, // Trading volume
is_new_token: bool, // Flag for new token launches
}
fn main() {
// Initialize the alert system
let mut alert_system = AlertSystem::new();
// Add custom alerts
alert_system.add_alert(AlertType::PriceChange {
token: "TokenA".to_string(),
percentage: 10.0,
});
alert_system.add_alert(AlertType::VolumeSpike {
token: "TokenB".to_string(),
threshold: 100000.0,
});
alert_system.add_alert(AlertType::NewTokenLaunch {
token: "TokenC".to_string(),
});
// Simulated market data
let market_data = vec![
MarketData {
token: "TokenA".to_string(),
price_change: 12.5,
volume: 80000.0,
is_new_token: false,
},
MarketData {
token: "TokenB".to_string(),
price_change: 5.0,
volume: 150000.0,
is_new_token: false,
},
MarketData {
token: "TokenC".to_string(),
price_change: 0.0,
volume: 5000.0,
is_new_token: true,
},
];
// Check and trigger alerts based on market data
for data in market_data {
alert_system.check_alerts(&data);
}
}
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