Nadfunagent

**CRITICAL COMMUNICATION RULES:**
1. **Language**: Always respond in the SAME language as the user's question.  If in English, respond in English.
2. **Data Loading**: BEFORE executing any operations, FIRST request and load ALL required data from user or configuration files. Use OpenClaw's memory/session storage to save loaded data so you don't need to ask again.
3. **Telegram Integration**: 
   - Send detailed reports to Telegram after each trading cycle
   - If Telegram bot connection is not established, request user to start conversation with bot first
   - Include position status, P&L, new opportunities found, trades executed
4. **Initial Setup**: When first invoked, ask user for:
   - MMIND_TOKEN_ADDRESS (or load from .env)
   - MONAD_PRIVATE_KEY (or load from .env)
   - MONAD_RPC_URL (or load from .env)
   - MONAD_NETWORK (or load from .env)
   - Telegram user ID for notifications
   Save all this data in OpenClaw memory for future use.
5. **Missing variables**: If `.env` is missing or any required variable (MONAD_PRIVATE_KEY, MONAD_RPC_URL, MMIND_TOKEN_ADDRESS, MONAD_NETWORK) is not set, **ask the user to provide it** before running trading or scripts. Do not proceed with buy/sell or execute-bonding-v2 until config is complete.

# Nad.fun Autonomous Trading Agent

Autonomous trading agent that scans Nad.fun markets, analyzes tokens using momentum strategies, executes trades, and distributes profits to MMIND token holders.

## Prerequisites

- `monad-development` skill installed (for wallet and RPC setup)
- `nadfun-trading` skill installed (for buy/sell operations), or use the `trading/` folder from this repo
- `nadfun-indexer` skill installed (for querying events)
- `nadfun-agent-api` skill installed (for market data)
- Network configured (mainnet only for this skill)
- MMIND token address configured

**Paths (clean install):** Config is read from `NADFUN_ENV_PATH` if set, else `$HOME/nadfunagent/.env`. Positions report: `POSITIONS_REPORT_PATH` or `$HOME/nadf...

# Nad.fun Autonomous Trading Agent

Autonomous trading agent for Nad.fun that scans markets, analyzes tokens, executes trades, and distributes profits to MMIND token holders.

## 🎯 Project Overview

This agent autonomously:
- Scans Nad.fun markets using 3 methods (New Events API, Market Cap API, Creation Time API)
- Analyzes tokens using comprehensive scoring (liquidity, momentum, volume, holders, progress, authority)
- Manages positions with stop-loss (-10%) and take-profit (+5% / -10% via `check-pnl.js --auto-sell`)
- Executes trades on **both bonding curve AND DEX** (supports all market types)
- **Trading scripts** in `trading/`: buy, sell, P&L from entry price (recorded by buy), full cycle (`execute-bonding-v2.js`). Mainnet only.
- Distributes profits to MMIND token holders

## 🚀 Quick Start

### Prerequisites

- OpenClaw CLI installed
- Node.js 18+ installed
- Access to Monad blockchain (mainnet or testnet)

### Installation

#### Option 1: Install from GitHub (Recommended)

```bash
# Install OpenClaw CLI first
npm install -g openclaw

# Install this agent from GitHub
clawhub install nadfunagent
```

#### Option 2: Manual Installation

```bash
# Clone repository
git clone https://github.com/encipher88/nadfunagent.git
cd nadfunagent

# Copy SKILL.md to OpenClaw workspace
mkdir -p ~/.openclaw/workspace/skills/nadfunagent
cp SKILL.md ~/.openclaw/workspace/skills/nadfunagent/
```

### Required Skills

Install these OpenClaw skills first:

```bash
clawhub install monad-development
clawhub install nadfun-trading
clawhub install nadfun-indexer
clawhub install nadfun-agent-api
```

### Scripts and trading (all Node.js)

This repo uses **Node.js only** (no Python). Two folders:
- **scripts/** — helper scripts for the agent (check positions, save found tokens, write positions report). See `scripts/README.md`.
- **trading/** — full trading suite (buy/sell/P&L/cycle) you can run standalone or from OpenClaw:

- **Buy/sell**: `buy-token.js`, `sell-token.js`, `sell-all.js`...