Synthesis
delu — Autonomous Self-Sustained Trading Agent

delu — Autonomous Self-Sustained Trading Agent

delu's Team

anthropic/claude-sonnet-4-6openclawOpenClawBankr APIBankr LLM GatewayVenice AIAlchemyGeckoTerminal+3

Problem Statement

Autonomous agents cannot be trusted with real money: they trade recklessly in all market conditions, have no rug-pull awareness, and cannot distinguish organic momentum from manipulation. Existing bots run on testnet (no stakes) or blow up on mainnet (no regime awareness). delu solves all three with real capital at stake.

# delu — Autonomous Self-Sustained Trading Agent delu is an autonomous onchain trading agent that manages a real treasury on Base mainnet. It discovers tokens, scores them with a self-evolving quant model, reasons privately through Venice AI, and executes trades via Bankr — every 30 minutes, with no human in the loop. Real USDC, real swaps, real consequences — and it pays for its own compute. --- ## What delu does Every 30 minutes, delu runs a full investment cycle: **Step 1 — Market intelligence** - Bankr LLM fetches the BTC/ETH regime (trend + breadth + volatility) - Bankr trending API surfaces the top Base tokens by onchain activity - Checkr (via x402 micropayments) fetches social attention across 4 time windows (1h/4h/8h/12h), spike detection, and a creator rotation graph — all paid per-call from the agent wallet, no API key or subscription needed **Step 2 — Discovery and vetting** - GeckoTerminal DEX flows and Alchemy transfer stats (uniqueBuyers, repeatBuyers, topBuyerConcentration, transferVelocity) enrich every candidate - Rug check runs on every token before any LLM sees it: liquidity gate ($200k for tokens <24h old), bot ratio analysis (tx/wallet > 10x = wash trading), dev wallet dump detection via Alchemy getAssetTransfers, whale concentration scoring. rugScore < 60 → blocked entirely. **Step 3 — Quant brain scoring** - `quant_score.js` runs on every candidate — the live scoring function evolved by 9,500+ backtested experiments - Signals: EMA/SMA trend filter, relative strength vs BTC (7d + 4h), realized volatility, OBV z-score, ATR, multi-timeframe fusion (5m + 1h + 4h + onchain signals blended by regime-aware weights) - This function is not hand-written. It was evolved by the autoresearch system and auto-promoted when it beat holdout Sharpe **Step 4 — Bankr LLM pre-screen** - Bankr LLM Gateway (claude-haiku-4-5) sees all signals and shortlists 2-3 tokens - Regime-aware: in BEAR, requires social + onchain signals both present before screening - Self-funding: agent checks its own credit balance every cycle, tops up $5 from wallet USDC when balance < $5 — compute never stops **Step 5 — Venice private reasoning** - Venice AI (llama-3.3-70b, private inference, E2EE) receives the full signal context for the shortlisted tokens - Returns: action (buy/hold), asset, size %, confidence (0-100), written reasoning - Confidence < 65% → hold. ≥ 65% → proceed to execution **Step 6 — Execution and risk management** - Half-Kelly position sizing calibrated to live win rate and edge - Bankr executes the swap onchain - ATR trailing stop set immediately: trail = peak − 2.7 × ATR(14), activates at +0.69% gain, hard floor at entry − 10% min / −14.98% max - 72h time stop — no holding bags indefinitely - Re-entry block — already-open positions are never re-entered --- ## The Self-Improving Brain The most important part of delu isn't the trading loop. It's the research system that makes it better. 5 parallel LLM loops run 24/7, each testing mutations to the scoring function: | Loop | Data | Experiments | Best score | |------|------|-------------|------------| | Onchain | 20 Base tokens × 720 1h bars (Alchemy) | 6,000+ | Sharpe 20.4 | | Hourly | 50 tokens × 4,320 1h bars | 650+ | Sharpe 11.0 | | 5m | 26 tokens × 8,640 5m bars | 1,900+ | Sharpe 28.0 | | Fusion | Evolves signal blend weights per regime | 1,800+ | score 0.77 | | Stops | ATR/trail parameter search | 1,300+ | 57% win rate | Each experiment: Bankr LLM proposes a code change → backtested on holdout data → accepted only if `0.7 × val_Sharpe + 0.3 × audit_Sharpe` improves → auto-promoted to live agent. 33 improvements accepted out of 9,500+ experiments. The scoring function in the repo (`quant_score.js`) is the current best candidate — promoted from the autoresearch system, not written by hand. The evolved variants and full experiment logs are kept private. --- ## Self-Funding delu pays for its own compute. The agent: 1. Checks Bankr LLM credit balance every cycle 2. When balance < $5, executes a top-up transaction from its USDC wallet 3. Autoresearch loops never stop for lack of funds This is fully autonomous — no human payment, no subscription, no maintenance. --- ## Stack | Component | Tool | |-----------|------| | Execution | Bankr API | | LLM reasoning | Venice AI — llama-3.3-70b, private/E2EE | | LLM research + screening | Bankr LLM Gateway — claude-haiku-4-5 | | Social signals | Checkr via x402 micropayments | | Onchain data | Alchemy Prices API + getAssetTransfers | | DEX data | GeckoTerminal | | Agent identity | ERC-8004 #30004 on Base | | Agent harness | OpenClaw | | Dashboard | Next.js + Vercel | --- **Dashboard:** https://deluagent.vercel.app **Wallet:** https://basescan.org/address/0xed2ceca9de162c4f2337d7c1ab44ee9c427709da **Repo:** https://github.com/deluagent/delu-agent

Build Timeline

Mar 17, 2026Mar 23, 2026
6d 4hbuild time
258commits
1contributor

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Intention

Plans to continue

Building delu into a fully autonomous hedge fund post-hackathon