Nakal

Problem Statement

OverviewThis project builds anASI-sponsored AI copy traderthat lets users copy trades of any public on-chain wallet with agentic intelligence and seamless execution. The systemstarts from the ASI One chat protocol, and all agents are registered and accessible viaAgentverse.How It WorksStart in ASI One Chat: User interacts with the system through the ASI One protocol.Input Wallet: User pastes a public wallet address.Data Fetch: Wallet history & PnL fetched via1inch Portfolio & PnL APIs.Agent Analysis(accessible via Agentverse):Meme-Coin Agent: Suggests high-risk/high-reward plays.Blue-Chip Agent: Focuses on safer, large-cap tokens.Consensus Agent: Ranks suggestions & explains rationale.User Decision: User selects tokens, sets USD amount.Execution:1inch APIs: Provide quotes, optimal swap routes, and execute trades on-chain.Polygon x402: Handlesagentic payments—funds flow securely between users and agents, or between agents, to complete swaps and deposit results into user wallets.Key FeaturesAgentic Analysis: Multiple specialized AI agents debate & rank trade ideas, all accessible through Agentverse.Cross-Chain Ready: Supports swaps on Polygon with seamless fund routing.Non-Custodial Option: Users can sign transactions directly for safety.Full Transparency: Audit logs, risk scores, and transaction receipts.Tech StackFrontend:ASI One LLM(via Agentverse), integrating multiple agents for dynamic reasoning and trade suggestions.Backend: Python & Node.js for orchestration,1inch APIsfor trade data & swap generation,Polygon x402for agentic payment execution.Why We Chose TheseASI: Powers agentic reasoning; all agents are registered on Agentverse and can analyze wallet data, debate strategies, and provide actionable suggestions.1inch APIs: Reliable and efficient on-chain trade execution, quotes, and portfolio/PnL data.Polygon x402: Provides a secure, fast, and low-feeagentic payment layerfor human-to-agent and agent-to-agent fund flows.User FlowStart in ASI One Chat → Paste wallet → Analyze → Get suggestions → Pick trade → Execute via 1inch + Polygon x402 → Funds in wallet.

Solution

How It's MadeThis project combinesmulti-agent reasoning, on-chain data fetching, and automated trade executioninto a seamless workflow.Technical ArchitectureFrontend & Agent InteractionASI One LLMserves as the entry point; all agents are accessible viaAgentverse.Agents communicate through structured JSON messages that encode trade suggestions, risk scores, and reasoning steps.Agents & OrchestrationWallet-Ingest Agent: Uses1inch Portfolio & PnL APIsto fetch historical trades, normalizes timestamps, token decimals, and computes derived metrics (ROI, average holding, slippage).Meme-Coin & Blue-Chip Agents: Implement custom scoring heuristics for volatility, liquidity, and market cap; outputs ranked suggestions with rationale.Consensus Agent: Aggregates suggestions using weighted scoring based on risk and historical accuracy.Execution Agent: Converts suggestions into1inch calldata, verifies balances and allowances, and prepares transactions forPolygon x402routing.BackendPythonhandles agent orchestration, data normalization, risk scoring, and LLM input/output preprocessing.Node.jsmanages real-time websocket communication, 1inch API calls, and Polygon x402 integration for automated settlement.Automated Execution & Payments1inch: On-chain swap execution, optimal route selection, and price checks.Polygon x402: Handlesagentic payments; ensures funds flow between users and agents or between agents, managing approvals and settlements automatically.Notable Technical Aspects / HacksDynamic Agent Chaining: Agents can call each other’s outputs in real-time to refine suggestions—enables “debate-style” reasoning.Calldata Auto-Generation: Execution agent generates swap calldata programmatically based on LLM output without manual intervention.Risk-aware Execution: Pre-execution sanity checks include liquidity thresholds, slippage limits, and multi-agent confidence scores.Hybrid Tech Stack: Python for AI/data-heavy tasks, Node.js for real-time orchestration, all integrated seamlessly via APIs and WebSockets.Embedded Audit Trail: Every agent suggestion and executed swap is logged with timestamp, wallet, calldata, and transaction hash for full traceability.This design enables areal-time, agent-driven trading assistantthat bridges AI reasoning and on-chain execution while maintaining flexibility, safety, and transparency.