How do I install the Kryptogo Meme Trader skill?

Run npx skillmds@latest add yejiming/kryptogo-meme-trader in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

What does the Kryptogo Meme Trader skill do?

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. It is listed under AI & ML on SkillMD.

Is Kryptogo Meme Trader safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Kryptogo Meme Trader?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Kryptogo Meme Trader free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under MIT.

Who published Kryptogo Meme Trader?

yejiming (@yejiming) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Kryptogo Meme Trader by yejiming — Agent Skill

Name: Kryptogo Meme Trader
Author: yejiming

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

# 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

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              # 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, 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

Kryptogo Meme Trader

File contents

KryptoGO Meme Trader Agent Skill

Overview

When to Use

When NOT to Use

Setup Flow

1. Get API Key

2. Generate Agent Wallet

3. Fund the Wallet

Security Rules

Authentication

Agent Behavior

Session Initialization

Default Mode: Supervised

Persistence (CRITICAL)

User Preferences

Safety Guardrails

Trading Limits (Hard Caps)

Credential Isolation

Automated Monitoring (Cron)

Quick Setup

On-Chain Analysis Framework (7-Step Pipeline)

Step 1: Token Overview & Market Cap Filter

Step 2: Cluster Analysis

Step 3: Cluster Trend (Multi-Timeframe)

Step 4: Address Labels + Sell Pressure Verification

Step 5: Deep Dive (Optional)

Step 6: Decision

Step 7: Execute Trade

API Quick Reference

Multi-Chain Support

Error Handling

Operational Scripts

Learning & Adaptation

Core Concepts

Best Practices

File Structure

Frequently asked questions

Kryptogo Meme Trader

File contents

KryptoGO Meme Trader Agent Skill

Overview

When to Use

When NOT to Use

Setup Flow

1. Get API Key

2. Generate Agent Wallet

3. Fund the Wallet

Security Rules

Authentication

Agent Behavior

Session Initialization

Default Mode: Supervised

Persistence (CRITICAL)

User Preferences

Safety Guardrails

Trading Limits (Hard Caps)

Credential Isolation

Automated Monitoring (Cron)

Quick Setup

On-Chain Analysis Framework (7-Step Pipeline)

Step 1: Token Overview & Market Cap Filter

Step 2: Cluster Analysis

Step 3: Cluster Trend (Multi-Timeframe)

Step 4: Address Labels + Sell Pressure Verification

Step 5: Deep Dive (Optional)

Step 6: Decision

Step 7: Execute Trade

API Quick Reference

Multi-Chain Support

Error Handling

Operational Scripts

Learning & Adaptation

Core Concepts

Best Practices

File Structure

Related skills

Frequently asked questions

How do I install the Kryptogo Meme Trader skill?

What does the Kryptogo Meme Trader skill do?

Is Kryptogo Meme Trader safe to use?

Which AI agents work with Kryptogo Meme Trader?

Is Kryptogo Meme Trader free to use?

Who published Kryptogo Meme Trader?