Customizable Agent Analytics

Each Nova Agent can be tailored to focus on specific metrics, offering deep insights and actionable data:

• Smart Wallets Track the activity of influential wallets, such as top holders, whales, and insiders. Analyze their transaction patterns to predict market trends and gain insights into their strategies.

use std::collections::HashMap;

// Represents a wallet with its activity
#[derive(Debug, Clone)]
struct SmartWallet {
    address: String,
    total_received: f64,
    total_sent: f64,
    transaction_count: u32,
    last_active: u64,
}

// Represents a transaction
#[derive(Debug)]
struct Transaction {
    from: String,
    to: String,
    amount: f64,
    timestamp: u64,
}

// Tracks and analyzes smart wallets
struct SmartWalletTracker {
    wallets: HashMap<String, SmartWallet>,
    transactions: Vec<Transaction>,
}

impl SmartWalletTracker {
    // Create a new tracker
    fn new() -> Self {
        SmartWalletTracker {
            wallets: HashMap::new(),
            transactions: Vec::new(),
        }
    }

    // Add a transaction and update relevant wallets
    fn add_transaction(&mut self, transaction: Transaction) {
        self.transactions.push(transaction.clone());

        // Update the sender's wallet
        self.update_wallet(
            transaction.from.clone(),
            -transaction.amount,
            transaction.timestamp,
        );

        // Update the receiver's wallet
        self.update_wallet(
            transaction.to.clone(),
            transaction.amount,
            transaction.timestamp,
        );
    }

    // Update or create a wallet record
    fn update_wallet(&mut self, address: String, amount: f64, timestamp: u64) {
        let wallet = self.wallets.entry(address.clone()).or_insert(SmartWallet {
            address,
            total_received: 0.0,
            total_sent: 0.0,
            transaction_count: 0,
            last_active: 0,
        });

        if amount > 0.0 {
            wallet.total_received += amount;
        } else {
            wallet.total_sent += -amount;
        }

        wallet.transaction_count += 1;
        wallet.last_active = timestamp;
    }

    // Analyze wallet activity for patterns
    fn analyze_wallets(&self) {
        println!("Analyzing smart wallet activities...\n");
        for (_, wallet) in &self.wallets {
            println!(
                "Wallet: {}\n  Total Received: {:.2}\n  Total Sent: {:.2}\n  Transactions: {}\n  Last Active: {}\n",
                wallet.address,
                wallet.total_received,
                wallet.total_sent,
                wallet.transaction_count,
                wallet.last_active
            );
        }
    }

    // Identify top wallets based on activity
    fn identify_top_wallets(&self) {
        println!("Top Smart Wallets (by transaction count):\n");
        let mut top_wallets: Vec<_> = self.wallets.values().collect();
        top_wallets.sort_by_key(|wallet| -(wallet.transaction_count as i32));

        for wallet in top_wallets.iter().take(5) {
            println!(
                "  Wallet: {}\n    Transactions: {}\n    Total Received: {:.2}\n    Total Sent: {:.2}\n",
                wallet.address,
                wallet.transaction_count,
                wallet.total_received,
                wallet.total_sent
            );
        }
    }
}

fn main() {
    let mut tracker = SmartWalletTracker::new();

    // Simulate transactions
    tracker.add_transaction(Transaction {
        from: "wallet1".to_string(),
        to: "wallet2".to_string(),
        amount: 200.0,
        timestamp: 1633036800,
    });

    tracker.add_transaction(Transaction {
        from: "wallet2".to_string(),
        to: "wallet3".to_string(),
        amount: 150.0,
        timestamp: 1633036900,
    });

    tracker.add_transaction(Transaction {
        from: "wallet3".to_string(),
        to: "wallet4".to_string(),
        amount: 300.0,
        timestamp: 1633037000,
    });

    tracker.add_transaction(Transaction {
        from: "wallet4".to_string(),
        to: "wallet1".to_string(),
        amount: 100.0,
        timestamp: 1633037100,
    });

    // Analyze and identify patterns
    tracker.analyze_wallets();
    tracker.identify_top_wallets();
}

• Transaction Volume Monitor token trading volumes in real-time to identify market interest, spot pumps, and detect potential breakout tokens.

use std::collections::HashMap;

// Represents trading volume data for a token
#[derive(Debug)]
struct TokenVolume {
    token: String,
    volume: f64,
}

// Tracker for real-time token trading volumes
struct TokenVolumeTracker {
    volumes: HashMap<String, f64>,
}

impl TokenVolumeTracker {
    // Initialize the tracker
    fn new() -> Self {
        TokenVolumeTracker {
            volumes: HashMap::new(),
        }
    }

    // Update token volume with a new trade
    fn update_volume(&mut self, token: String, amount: f64) {
        *self.volumes.entry(token).or_insert(0.0) += amount;
    }

    // Detect tokens with sudden volume spikes (pump detection)
    fn detect_pumps(&self, threshold: f64) -> Vec<&String> {
        self.volumes
            .iter()
            .filter(|(_, &volume)| volume > threshold)
            .map(|(token, _)| token)
            .collect()
    }

    // Display current token volumes
    fn display_volumes(&self) {
        println!("Current Trading Volumes:");
        for (token, volume) in &self.volumes {
            println!("  Token: {}, Volume: {:.2}", token, volume);
        }
    }
}

fn main() {
    let mut tracker = TokenVolumeTracker::new();

    // Simulated trades
    tracker.update_volume("TokenA".to_string(), 1200.0);
    tracker.update_volume("TokenB".to_string(), 800.0);
    tracker.update_volume("TokenA".to_string(), 500.0);
    tracker.update_volume("TokenC".to_string(), 3000.0);

    // Display trading volumes
    tracker.display_volumes();

    // Detect and display tokens with a pump
    let pumps = tracker.detect_pumps(1000.0);
    if !pumps.is_empty() {
        println!("Detected Potential Pumps: {:?}", pumps);
    }
}

• Holder Distribution Examine how tokens are distributed among holders, from whales to smaller wallets. A balanced distribution often indicates a healthier token ecosystem.

use std::collections::HashMap;

// Represents a token holder
#[derive(Debug)]
struct Holder {
    address: String,
    balance: f64,
}

// Tracker for token distribution among holders
struct TokenDistributionTracker {
    holders: HashMap<String, f64>, // Address to balance mapping
}

impl TokenDistributionTracker {
    // Initialize the tracker
    fn new() -> Self {
        TokenDistributionTracker {
            holders: HashMap::new(),
        }
    }

    // Update or add a holder's balance
    fn update_balance(&mut self, address: String, balance: f64) {
        self.holders.insert(address, balance);
    }

    // Analyze distribution and categorize holders
    fn analyze_distribution(&self) {
        let mut whales = 0;
        let mut mids = 0;
        let mut smalls = 0;

        for &balance in self.holders.values() {
            if balance > 1000.0 {
                whales += 1; // Whales: balances > 1000
            } else if balance > 100.0 {
                mids += 1; // Mid-tier: 100 < balance ≤ 1000
            } else {
                smalls += 1; // Small wallets: balance ≤ 100
            }
        }

        println!(
            "Token Distribution:\n  Whales: {}\n  Mid-tier: {}\n  Small wallets: {}",
            whales, mids, smalls
        );
    }
}

fn main() {
    let mut tracker = TokenDistributionTracker::new();

    // Simulate holder balances
    tracker.update_balance("Wallet1".to_string(), 1500.0);
    tracker.update_balance("Wallet2".to_string(), 750.0);
    tracker.update_balance("Wallet3".to_string(), 50.0);
    tracker.update_balance("Wallet4".to_string(), 1200.0);
    tracker.update_balance("Wallet5".to_string(), 300.0);

    // Analyze and display the distribution
    tracker.analyze_distribution();
}

• Developer On-Chain History Assess a project’s legitimacy by analyzing the on-chain history of its developers. Look for consistent contributions, activity across multiple projects, and engagement with the blockchain community.

use std::collections::HashMap;

// Represents a developer's activity
#[derive(Debug)]
struct DeveloperActivity {
    address: String,
    projects_contributed: Vec<String>,
    transactions_count: u32,
    community_engagement: u32, // Community interactions (e.g., discussions, proposals)
}

// Tracker for developer activities
struct DeveloperTracker {
    developers: HashMap<String, DeveloperActivity>, // Address to DeveloperActivity
}

impl DeveloperTracker {
    // Initialize the tracker
    fn new() -> Self {
        DeveloperTracker {
            developers: HashMap::new(),
        }
    }

    // Record a developer's activity
    fn record_activity(&mut self, address: String, project: String, community_interactions: u32) {
        let developer = self.developers.entry(address.clone()).or_insert(DeveloperActivity {
            address,
            projects_contributed: Vec::new(),
            transactions_count: 0,
            community_engagement: 0,
        });

        developer.projects_contributed.push(project);
        developer.transactions_count += 1;
        developer.community_engagement += community_interactions;
    }

    // Assess developer's legitimacy based on activity
    fn assess_legitimacy(&self) {
        for (address, activity) in &self.developers {
            let contribution_score = (activity.projects_contributed.len() * 10) as u32
                + activity.transactions_count
                + activity.community_engagement;
            println!(
                "Developer: {}\n  Projects: {:?}\n  Transactions: {}\n  Community Engagement: {}\n  Legitimacy Score: {}",
                address,
                activity.projects_contributed,
                activity.transactions_count,
                activity.community_engagement,
                contribution_score
            );
        }
    }
}

fn main() {
    let mut tracker = DeveloperTracker::new();

    // Simulate developer activities
    tracker.record_activity("dev1".to_string(), "ProjectA".to_string(), 5);
    tracker.record_activity("dev1".to_string(), "ProjectB".to_string(), 3);
    tracker.record_activity("dev2".to_string(), "ProjectA".to_string(), 2);
    tracker.record_activity("dev3".to_string(), "ProjectC".to_string(), 8);
    tracker.record_activity("dev3".to_string(), "ProjectD".to_string(), 6);

    // Assess and display developer legitimacy
    tracker.assess_legitimacy();
}

• Top Holders On-Chain Activity Keep tabs on the actions of significant holders. Spot trends like accumulation, sell-offs, or transfers to exchanges, which could signal major market moves.

use std::collections::HashMap;

// Represents a wallet's transaction activity
#[derive(Debug)]
struct WalletActivity {
    address: String,
    balance: f64,
    transactions: u32,
    transfers_to_exchange: u32,
}

// Tracker for wallet activities
struct WalletTracker {
    wallets: HashMap<String, WalletActivity>, // Address to WalletActivity
}

impl WalletTracker {
    // Initialize the tracker
    fn new() -> Self {
        WalletTracker {
            wallets: HashMap::new(),
        }
    }

    // Update a wallet's balance and track activity
    fn update_wallet_activity(&mut self, address: String, amount: f64, to_exchange: bool) {
        let wallet = self.wallets.entry(address.clone()).or_insert(WalletActivity {
            address,
            balance: 0.0,
            transactions: 0,
            transfers_to_exchange: 0,
        });

        wallet.balance += amount;
        wallet.transactions += 1;
        if to_exchange {
            wallet.transfers_to_exchange += 1;
        }
    }

    // Detect trends (accumulation, sell-offs, transfers)
    fn detect_trends(&self) {
        for (_, wallet) in &self.wallets {
            if wallet.balance > 5000.0 {
                println!(
                    "Significant Wallet: {}\n  Balance: {:.2}\n  Transactions: {}\n  Transfers to Exchange: {}\n",
                    wallet.address, wallet.balance, wallet.transactions, wallet.transfers_to_exchange
                );
                
                if wallet.transfers_to_exchange > 3 {
                    println!("  Trend: Likely sell-off (multiple transfers to exchange)");
                } else if wallet.balance > 10000.0 {
                    println!("  Trend: Accumulation (balance over 10,000 tokens)");
                }
            }
        }
    }
}

fn main() {
    let mut tracker = WalletTracker::new();

    // Simulate wallet activities
    tracker.update_wallet_activity("wallet1".to_string(), 12000.0, false); // Accumulation
    tracker.update_wallet_activity("wallet2".to_string(), 3000.0, false);
    tracker.update_wallet_activity("wallet1".to_string(), 1000.0, true);  // Transfer to exchange
    tracker.update_wallet_activity("wallet1".to_string(), -500.0, true);  // Sell-off
    tracker.update_wallet_activity("wallet3".to_string(), 20000.0, false); // Accumulation
    tracker.update_wallet_activity("wallet3".to_string(), 2000.0, true);  // Transfer to exchange

    // Detect trends in wallet activities
    tracker.detect_trends();
}

• KOL’s Buys Track purchases by Key Opinion Leaders (KOLs) and influencers who can sway market sentiment. Understand their strategies and replicate them for potential gains.

use std::collections::HashMap;

// Represents a KOL (Key Opinion Leader) or influencer's purchase activity
#[derive(Debug)]
struct KOLActivity {
    address: String,
    purchases: Vec<f64>, // List of purchase amounts
}

// Tracker for KOL activities
struct KOLTracker {
    kol_purchases: HashMap<String, KOLActivity>, // Address to KOLActivity
}

impl KOLTracker {
    // Initialize the tracker
    fn new() -> Self {
        KOLTracker {
            kol_purchases: HashMap::new(),
        }
    }

    // Record a KOL's purchase
    fn record_purchase(&mut self, address: String, amount: f64) {
        let kol_activity = self.kol_purchases.entry(address.clone()).or_insert(KOLActivity {
            address,
            purchases: Vec::new(),
        });

        kol_activity.purchases.push(amount);
    }

    // Analyze KOL's strategy based on purchase patterns
    fn analyze_strategy(&self) {
        for (_, kol_activity) in &self.kol_purchases {
            let total_purchases: f64 = kol_activity.purchases.iter().sum();
            let average_purchase = total_purchases / kol_activity.purchases.len() as f64;

            println!(
                "KOL: {}\n  Total Purchases: {:.2}\n  Average Purchase: {:.2}",
                kol_activity.address,
                total_purchases,
                average_purchase
            );

            if average_purchase > 5000.0 {
                println!("  Strategy: Likely accumulation (high average purchase)");
            } else if total_purchases > 10000.0 {
                println!("  Strategy: Significant market influence (high total purchases)");
            } else {
                println!("  Strategy: Small-scale purchases, cautious approach");
            }
        }
    }
}

fn main() {
    let mut tracker = KOLTracker::new();

    // Simulate KOL purchases
    tracker.record_purchase("KOL1".to_string(), 10000.0);
    tracker.record_purchase("KOL1".to_string(), 1500.0);
    tracker.record_purchase("KOL2".to_string(), 6000.0);
    tracker.record_purchase("KOL2".to_string(), 2000.0);
    tracker.record_purchase("KOL3".to_string(), 3000.0);
    tracker.record_purchase("KOL3".to_string(), 500.0);

    // Analyze KOL strategies
    tracker.analyze_strategy();
}

• Web and GitHub Scans Dive into a project’s online presence and development activity. Analyze GitHub repositories for updates, contributions, and code quality while scanning the web for news, discussions, and community sentiment.

use std::collections::HashMap;

// Represents GitHub repository activity
#[derive(Debug)]
struct RepoActivity {
    repo_name: String,
    stars: u32,
    forks: u32,
    recent_commits: u32,
}

// Represents a project's online presence
#[derive(Debug)]
struct WebPresence {
    mentions: u32,
    sentiment_score: f64, // Positive: >0, Negative: <0
}

// Tracker for project activity
struct ProjectTracker {
    github_repos: HashMap<String, RepoActivity>, // Repo name to activity mapping
    web_mentions: WebPresence,
}

impl ProjectTracker {
    // Initialize the tracker
    fn new() -> Self {
        ProjectTracker {
            github_repos: HashMap::new(),
            web_mentions: WebPresence {
                mentions: 0,
                sentiment_score: 0.0,
            },
        }
    }

    // Analyze GitHub repositories (placeholder for real API calls)
    fn analyze_github_repo(&mut self, repo_name: String, stars: u32, forks: u32, recent_commits: u32) {
        self.github_repos.insert(
            repo_name.clone(),
            RepoActivity {
                repo_name,
                stars,
                forks,
                recent_commits,
            },
        );
    }

    // Scan the web for mentions (placeholder for real web scraping)
    fn scan_web(&mut self, mentions: u32, sentiment_score: f64) {
        self.web_mentions.mentions += mentions;
        self.web_mentions.sentiment_score = sentiment_score;
    }

    // Display project insights
    fn display_insights(&self) {
        println!("GitHub Repository Analysis:");
        for (_, repo) in &self.github_repos {
            println!(
                "  Repo: {}\n    Stars: {}\n    Forks: {}\n    Recent Commits: {}",
                repo.repo_name, repo.stars, repo.forks, repo.recent_commits
            );
        }

        println!(
            "Web Mentions:\n  Total Mentions: {}\n  Sentiment Score: {:.2}",
            self.web_mentions.mentions, self.web_mentions.sentiment_score
        );

        if self.web_mentions.sentiment_score > 0.0 {
            println!("  Community Sentiment: Positive");
        } else if self.web_mentions.sentiment_score < 0.0 {
            println!("  Community Sentiment: Negative");
        } else {
            println!("  Community Sentiment: Neutral");
        }
    }
}

fn main() {
    let mut tracker = ProjectTracker::new();

    // Simulate GitHub activity analysis
    tracker.analyze_github_repo("NovaBot".to_string(), 1200, 350, 25);
    tracker.analyze_github_repo("NovaAgents".to_string(), 800, 120, 15);

    // Simulate web sentiment analysis
    tracker.scan_web(150, 0.85); // 150 mentions, positive sentiment

    // Display insights
    tracker.display_insights();
}

Users can configure their agents to concentrate on areas like e.g. low cap tokens, ensuring their strategies align with their goals.