| name | kryptogo-meme-trader |
| description | Analyze and trade meme coins using KryptoGO's on-chain cluster analysis platform. Covers wallet clustering, address labels, accumulation/distribution detection, and automated swap execution via the Agent Trading API. |
| homepage | https://www.kryptogo.xyz |
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 for autonomous mode, cron setup, and learning system details.
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
- Go to kryptogo.xyz/account and create an API key
- 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 with chmod 600, prints public address to fund.
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>
| Tier | Daily API Calls | Trading Fee | Signal Dashboard | KOL Finder |
|---|
| Free | 100 calls/day | 1% | No | No |
| Pro | 1,000 calls/day | 0.5% | Yes | Yes |
| Alpha | 5,000 calls/day | 0% | Yes | Yes |
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 directly. All credentials are accessed via environment variables only.
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 in preferences. See references/autonomous-trading.md for full details.
Persistence (CRITICAL)
IMMEDIATELY after submitting a transaction, the agent MUST:
- Write trade details to
memory/trading-journal.json with status: "OPEN"
- Include:
token_symbol, token_address, entry_price, position_size_sol, tx_hash, timestamp
User Preferences
Store in memory/trading-preferences.json:
| Preference | Default | Description |
|---|
max_position_size | 0.1 SOL | Max SOL per trade |
max_open_positions | 5 | Max concurrent open positions |
max_daily_trades | 20 | Max trades per day |
stop_loss_pct | 30% | Notify/sell when loss exceeds this |
take_profit_pct | 100% | Notify/sell when gain exceeds this |
min_market_cap | $500K | Skip tokens below this |
scan_count | 10 | Trending tokens per scan |
risk_tolerance | "conservative" | "conservative" (skip medium risk), "moderate" (ask on medium), "aggressive" (auto-trade medium) |
require_trade_confirmation | true | Set to false for autonomous mode |
chains | ["solana"] | Chains to scan |
Safety Guardrails
Trading Limits (Hard Caps)
| Limit | Default | Overridable? |
|---|
| Max single trade | 0.1 SOL | Yes, via max_position_size |
| Max concurrent positions | 5 | Yes, via max_open_positions |
| Max daily trade count | 20 | Yes, via max_daily_trades |
| Price impact abort | >10% | No — always abort |
| Price impact warn | >5% | No — always warn |
If any limit is hit, the agent must stop and notify the user.
Credential Isolation
Runtime scripts in this skill do NOT read .env files directly. All credentials are accessed via environment variables only, which must be pre-loaded by the caller (source ~/.openclaw/workspace/.env). This ensures no runtime script can independently access or exfiltrate credential files.
Exception: scripts/setup.py reads and writes .env — it loads existing keys to avoid regeneration, backs up .env before changes, and writes new keypair entries. This is the only script that touches credential files, and it runs only during initial setup or explicit --force regeneration.
Automated Monitoring (Cron)
Quick Setup
source ~/.openclaw/workspace/.env && bash scripts/cron-examples.sh setup-default
source ~/.openclaw/workspace/.env && bash scripts/cron-examples.sh setup-autonomous
bash scripts/cron-examples.sh teardown
| Job | Interval | Default Behavior |
|---|
stop-loss-tp | 5 min | Report triggered conditions, do NOT auto-sell |
discovery-scan | 1 hour | Analyze and send recommendations, do NOT auto-buy |
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> — get name, price, market cap, holders, risk_level. Skip if market cap < min_market_cap.
Step 2: Cluster Analysis
/analyze/<mint>?chain_id=<id> — wallet clusters, top holders, metadata.
- ≥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 across 15m/1h/4h/1d/7d.
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
/token-wallet-labels → identify dev/sniper/bundle wallets/balance-history for each risky address → check if still holding- Compute
risky_ratio = active risky holdings / total cluster holdings
-
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 for execution — handles wallet_address injection, error checking, and journal logging.
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
| Endpoint | Method | Purpose |
|---|
/agent/account | GET | Check tier & quota |
/agent/trending-tokens | GET | Scan trending tokens |
/agent/portfolio | GET | Wallet portfolio + PnL |
/agent/swap | POST | Build unsigned swap tx (Solana only) |
/agent/submit | POST | Submit signed tx (Solana only) |
/token-overview | GET | Token metadata & market data |
/analyze/:token_mint | GET | Full cluster analysis |
/analyze-cluster-change/:token_mint | GET | Cluster ratio trends |
/balance-history | POST | Time-series balance data |
/wallet-labels | POST | Behavior labels |
/token-wallet-labels | POST | Token-specific labels |
/signal-dashboard | GET | Curated accumulation signals (Pro+) |
Full request/response details: see references/api-reference.md
Multi-Chain Support
| Chain | chain_id | Analysis | Trading |
|---|
| Solana | 501 | Yes | Yes |
| BSC | 56 | Yes | No |
| Base | 8453 | Yes | No |
| Monad | 143 | Yes | No |
Error Handling
| Code | Meaning | Action |
|---|
| 400 | Bad Request | Check parameters |
| 401 | Unauthorized | Check API key |
| 402 | Quota Exceeded | Wait for daily reset or upgrade |
| 403 | Forbidden | Requires higher tier |
| 502/504 | Server error | Retry once after 10s |
Operational Scripts
All scripts require credentials to be pre-loaded: source ~/.openclaw/workspace/.env before running.
source ~/.openclaw/workspace/.env && bash scripts/portfolio.sh
source ~/.openclaw/workspace/.env && bash scripts/trending.sh
source ~/.openclaw/workspace/.env && bash scripts/analysis.sh
source ~/.openclaw/workspace/.env && python3 scripts/swap.py <mint> 0.1
source ~/.openclaw/workspace/.env && python3 scripts/swap.py <mint> <amt> --sell
source ~/.openclaw/workspace/.env && bash scripts/test-api.sh
Learning & Adaptation
The agent improves over time by recording trades, analyzing outcomes, and adjusting strategy. Every trade is logged to memory/trading-journal.json, losses trigger post-mortems, and periodic reviews propose parameter changes.
For full details on the learning system, trade journal format, post-mortem process, and strategy reviews, see references/autonomous-trading.md.
Core Concepts
| Concept | Key Insight |
|---|
| Cluster | Group of wallets controlled by same entity |
| Cluster Ratio | % of supply held by clusters. ≥30% = controlled, ≥50% = high risk |
| Developer | Deployed the token. Highest dump risk |
| Sniper | Bought within 1s of creation. Sell pressure if not cleared |
| Smart Money | Realized profit >$100K. Accumulation often precedes price moves |
| Accumulation | Cluster % rising + price consolidating = bullish |
| Distribution | Price rising + cluster % falling = bearish |
Full concepts guide: see references/concepts.md
Best Practices
- Always check
/agent/account first to confirm tier and quota
- Always check
/agent/portfolio on startup to detect existing positions
- Never expose private keys in logs, messages, or CLI arguments
- Validate price impact before submitting — abort >10%, warn >5%
- Sign and submit promptly — blockhash expires after ~60 seconds
- Persist state to
memory/trading-state.json after every action
- Log every trade to journal — no exceptions
- 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
