KryptoGO Meme Trader Agent Skill

Overview

This skill enables an AI agent to analyze and trade meme coins through the KryptoGO platform, combining deep on-chain cluster analysis with trade execution.

Analysis (multi-chain: Solana, BSC, Base, Monad): wallet clustering, accumulation/distribution detection, address behavior labels, network-wide accumulation signals (Pro/Alpha tier).

Trading (Solana only): portfolio monitoring with PnL tracking, swap execution via DEX aggregator, local transaction signing (private key never leaves the machine).

Default mode is supervised — all trades require user confirmation. Autonomous trading is available as opt-in. See

references/autonomous-trading.md

When to Use

• User asks to analyze a meme coin or token on Solana/BSC/Base/Monad
• User asks to trade, buy, or sell tokens
• User asks to scan for trending tokens or market opportunities
• User asks to monitor portfolio positions or check PnL
• Cron-triggered periodic portfolio monitoring and signal scanning

When NOT to Use

• BTC/ETH/major L1 macro analysis, NFTs, cross-chain bridging, non-DEX transactions, non-Solana trading

Setup Flow

1. Get API Key

1. Go to kryptogo.xyz/account and create an API key
2. Add to

   ~/.openclaw/workspace/.env

   :

   echo 'KRYPTOGO_API_KEY=sk_live_YOUR_KEY' >> ~/.openclaw/workspace/.env && chmod 600 ~/.openclaw/workspace/.env
   

Do NOT paste your API key directly in chat. Always set secrets via

.env

file.

2. Generate Agent Wallet

python3 scripts/setup.py

Creates a Solana keypair, saves to

.env

3. Fund the Wallet

Send SOL to the agent's public address (minimum 0.1 SOL).

Security Rules

• NEVER print, log, or include private keys in any message or CLI argument
• NEVER accept secrets pasted directly in chat — instruct users to set them in

  .env

• NEVER use the Read tool on

  .env

  — load credentials via

  source

  command only
• Runtime scripts do NOT read

  .env

  directly — all credentials are accessed via environment variables only, which must be pre-loaded by the caller (

  source ~/.openclaw/workspace/.env

  )
• Exception:

  scripts/setup.py

  reads and writes

  .env

  for initial keypair generation and address repair — this is the only script that touches credential files
• Private key stays in memory only during local signing — never sent to any server

Authentication

All endpoints require:

Authorization: Bearer sk_live_<48 hex chars>

Agent Behavior

Session Initialization

On every session start (including heartbeat/cron), the agent MUST load credentials BEFORE running any scripts:

source ~/.openclaw/workspace/.env

This is REQUIRED — scripts do not read

.env

Default Mode: Supervised

By default, the agent operates in supervised mode: it analyzes tokens, presents recommendations, and waits for user approval before executing any trade. Stop-loss/take-profit conditions are reported to the user but not auto-executed.

To enable autonomous trading, set

require_trade_confirmation: false

references/autonomous-trading.md

Persistence (CRITICAL)

IMMEDIATELY after submitting a transaction, the agent MUST:

1. Write trade details to

   memory/trading-journal.json

   with

   status: "OPEN"

2. Include:

   token_symbol

   ,

   token_address

   ,

   entry_price

   ,

   position_size_sol

   ,

   tx_hash

   ,

   timestamp

User Preferences

Store in

memory/trading-preferences.json

max_position_size

max_open_positions

max_daily_trades

stop_loss_pct

take_profit_pct

min_market_cap

scan_count

risk_tolerance

require_trade_confirmation

chains

Safety Guardrails

Trading Limits (Hard Caps)

max_position_size

max_open_positions

max_daily_trades

If any limit is hit, the agent must stop and notify the user.

Credential Isolation

Runtime scripts in this skill do NOT read

.env

source ~/.openclaw/workspace/.env

Exception:

scripts/setup.py

.env

.env

--force

Automated Monitoring (Cron)

Quick Setup

# Supervised mode (default): analysis + notifications, no auto-execution
source ~/.openclaw/workspace/.env && bash scripts/cron-examples.sh setup-default

# Autonomous mode (opt-in): auto-buys and auto-sells
source ~/.openclaw/workspace/.env && bash scripts/cron-examples.sh setup-autonomous

# Remove all cron jobs
bash scripts/cron-examples.sh teardown

stop-loss-tp

discovery-scan

For full cron configuration, manual setup, heartbeat alternative, and monitoring workflow details, see

references/autonomous-trading.md

On-Chain Analysis Framework (7-Step Pipeline)

Step 1: Token Overview & Market Cap Filter

/token-overview?address=<mint>&chain_id=<id>

min_market_cap

Step 2: Cluster Analysis

/analyze/<mint>?chain_id=<id>

• ≥30-35% = "controlled" — major entity present
• ≥50% = high concentration risk
• Single cluster >50% → skip (rug pull risk)

Free tier limitation: Cluster analysis only returns the top 2 clusters. To see full cluster data, upgrade at kryptogo.xyz/pricing.

Step 3: Cluster Trend (Multi-Timeframe)

/analyze-cluster-change/<mint>

cluster_ratio

changes

Core insight: Price and cluster holdings DIVERGING is the key signal.

• Rising price + falling cluster % = distribution (bearish)
• Falling price + rising cluster % = accumulation (bullish)

Step 4: Address Labels + Sell Pressure Verification

1. /token-wallet-labels

   → identify dev/sniper/bundle wallets

2. /balance-history

   for each risky address → check if still holding
3. Compute

   risky_ratio

   = active risky holdings / total cluster holdings

4. 30% = high risk, 10-30% = medium, <10% = low

Labels represent behavioral history, not current holdings. Always verify via

/balance-history

.

Step 5: Deep Dive (Optional)

/balance-history

/balance-increase/<mint>

/top-holders-snapshot/<mint>

/analyze-dca-limit-orders/<mint>

/cluster-wallet-connections

Step 6: Decision

Apply Bullish Checklist from

references/decision-framework.md

Step 7: Execute Trade

Use

scripts/swap.py

source ~/.openclaw/workspace/.env && python3 scripts/swap.py <token_mint> 0.1
source ~/.openclaw/workspace/.env && python3 scripts/swap.py <token_mint> <amount> --sell

API Quick Reference

/agent/account

/agent/trending-tokens

/agent/portfolio

/agent/swap

/agent/submit

/token-overview

/analyze/:token_mint

/analyze-cluster-change/:token_mint

/balance-history

/wallet-labels

/token-wallet-labels

/signal-dashboard

Full request/response details: see

references/api-reference.md

Multi-Chain Support

501

56

8453

143

Error Handling

Operational Scripts

All scripts require credentials to be pre-loaded:

source ~/.openclaw/workspace/.env

source ~/.openclaw/workspace/.env && bash scripts/portfolio.sh              # Portfolio check
source ~/.openclaw/workspace/.env && bash scripts/trending.sh               # Trending tokens
source ~/.openclaw/workspace/.env && bash scripts/analysis.sh               # Full analysis dashboard
source ~/.openclaw/workspace/.env && python3 scripts/swap.py <mint> 0.1     # Buy
source ~/.openclaw/workspace/.env && python3 scripts/swap.py <mint> <amt> --sell  # Sell
source ~/.openclaw/workspace/.env && bash scripts/test-api.sh               # API connectivity test

Learning & Adaptation

The agent improves over time by recording trades, analyzing outcomes, and adjusting strategy. Every trade is logged to

memory/trading-journal.json

For full details on the learning system, trade journal format, post-mortem process, and strategy reviews, see

references/autonomous-trading.md

Core Concepts

Full concepts guide: see

references/concepts.md

Best Practices

1. Always check

   /agent/account

   first to confirm tier and quota
2. Always check

   /agent/portfolio

   on startup to detect existing positions
3. Never expose private keys in logs, messages, or CLI arguments
4. Validate price impact before submitting — abort >10%, warn >5%
5. Sign and submit promptly — blockhash expires after ~60 seconds
6. Persist state to

   memory/trading-state.json

   after every action
7. Log every trade to journal — no exceptions
8. Read

   memory/trading-lessons.md

   before scanning — avoid repeating known bad patterns

File Structure

kryptogo-meme-trader/
├── SKILL.md                       ← You are here
├── package.json
├── .env.example
├── references/
│   ├── api-reference.md           ← Full API docs
│   ├── concepts.md                ← Core concepts
│   ├── decision-framework.md      ← Entry/exit strategies
│   └── autonomous-trading.md      ← Autonomous mode, cron, learning system
├── scripts/
│   ├── setup.py                   ← First-time setup
│   ├── cron-examples.sh           ← Cron configurations
│   ├── portfolio.sh / trending.sh / analysis.sh / test-api.sh
│   ├── swap.py                    ← Swap executor
│   └── trading-preferences.example.json
└── examples/
    ├── trading-workflow.py
    └── deep-analysis-workflow.py