/whale-tracking
Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens
$ npx -y skills add agiprolabs/claude-trading-skills --skill whale-tracking --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/whale-tracking
Context preview
The summary Claude sees to decide when to auto-load this skill.
Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens
SKILL.md
whale-tracking.SKILL.mdname: whale-tracking
description: Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens
Whale Tracking for Solana Tokens
Whale tracking monitors the on-chain behavior of large wallets to detect accumulation, distribution, and smart money movements before they become visible in price action. On Solana, where token ownership is highly concentrated and whale transactions can move markets instantly, tracking large holders is one of the highest-signal alpha sources available.
Why Whale Tracking Matters
A single large wallet selling 5% of a token's supply can crash the price 30-50% on thin Solana DEX liquidity. Conversely, a known profitable wallet accumulating a new token often precedes major price runs. Whale tracking converts on-chain transparency into actionable intelligence.
Key use cases:
- **Early warning**: Detect large holder sells before the price impact fully propagates
- **Smart money following**: Identify wallets with strong track records and monitor their new positions
- **Accumulation detection**: Spot gradual buying by whales who split orders to avoid detection
- **Distribution detection**: Catch insiders or early investors offloading positions
- **Risk assessment**: Evaluate token concentration risk before entering a position
What Constitutes a Whale
Whale classification depends on context. A wallet holding $50K of a $1M market cap token is a whale; the same $50K in SOL is not. Use relative and absolute thresholds:
Absolute Thresholds
| Category | Trade Size | Portfolio Size | Typical Behavior | |----------|-----------|---------------|-----------------| | Retail | < 10 SOL | < 100 SOL | Reactive, follows trends | | Mid-size | 10-100 SOL | 100-1,000 SOL | Mixed strategies | | Whale | 100-1,000 SOL | 1,000-10,000 SOL | Informed, moves markets | | Mega-whale | > 1,000 SOL | > 10,000 SOL | Market makers, funds, insiders |
Relative Thresholds (Per Token)
| Metric | Threshold | Significance | |--------|-----------|-------------| | % of supply held | > 2% | Significant holder | | % of daily volume | > 5% single trade | Market-moving transaction | | Top N holders | Top 20 | Core holder group | | Concentration ratio | Top 10 hold > 50% | High concentration risk |
Use both absolute and relative metrics. A 50 SOL trade in a $200K market cap token is whale-level; the same trade in a $50M token is retail.
Accumulation vs Distribution Patterns
Accumulation Signals
Accumulation is when a whale builds a position over time, often trying to minimize price impact.
**DCA pattern** (Dollar-Cost Averaging):
- Multiple buys of similar size over hours or days
- Buys at regular intervals (e.g., every 30 minutes)
- Position grows steadily without large single transactions
**Dip buying**:
- Buys concentrated during price dips
- Larger-than-usual purchases when price drops > 10%
- Position increases during periods of general selling
**Multi-wallet accumulation**:
- New wallets funded from the same source
- Each wallet buys small amounts of the same token
- Positions later consolidated into a primary wallet
**Detection heuristics**:
accumulation_score = 0
if buy_count > sell_count * 2: accumulation_score += 2
if avg_buy_size > avg_sell_size: accumulation_score += 1
if position_change_7d > 0: accumulation_score += 1
if buys_during_dips > buys_on_pump: accumulation_score += 2
if dca_pattern_detected: accumulation_score += 2
# Score >= 4 = likely accumulating
Distribution Signals
Distribution is when a whale reduces or exits a position, often gradually to avoid crashing the price.
**Gradual selling**:
- Multiple sells over days, each < 5% of position
- Sells increase in frequency over time
- Position shrinks steadily
**Transfer to exchange**:
- Tokens transferred to known exchange deposit addresses
- Large transfers to Binance, OKX, Bybit hot wallets
- Often precedes selling by hours or days
**Rapid exit**:
- Single large market sell (> 20% of position)
- Often triggers cascading liquidations
- Visible as large red candles with high volume
**Detection heuristics**:
distribution_score = 0
if sell_count > buy_count * 2: distribution_score += 2
if position_change_7d < 0: distribution_score += 1
if transfers_to_exchanges > 0: distribution_score += 3
if sell_frequency_increasing: distribution_score += 2
if position_pct_remaining < 50: distribution_score += 1
# Score >= 4 = likely distributing
Whale Watchlist Management
Maintain a watchlist of wallets worth tracking. Sources for discovering whale wallets:
Discovery Methods
1. **Top holders per token**: Query `getTokenLargestAccounts` for any token of interest 2. **Large transaction monitoring**: Watch for trades > 100 SOL on key tokens 3. **Profitable trader rankings**: Use SolanaTracker or Birdeye top trader endpoints 4. **Known fund wallets**: Public wallet addresses of crypto funds and DAOs 5. **Cross-referencing**: Wallets that appear in top holders of multiple successful tokens
Watchlist Structure
Each watchlist entry should track:
whale_entry = {
"address": "WhaLe...",
"label": "Smart money #47", # Human-readable label
"discovered": "2026-01-15", # When added to watchlist
"discovery_reason": "top_trader", # How they were found
"win_rate": 0.72, # Historical trade win rate
"avg_pnl": 3.4, # Average PnL multiplier
"tokens_tracked": 12, # Number of tokens held
"last_active": "2026-03-09", # Last on-chain activity
"tags": ["dex_trader", "sniper"], # Classification tags
}Wallet Classification Tags
| Tag | Description | |-----|-------------| | `sniper` | Buys tokens within minutes of launch | | `dex_trader` | Primarily trades on DEXes | | `accumulator` | Builds positions gradually | | `flipper` | Short hold ti
Read more
name: whale-tracking description: Large wallet monitoring, accumulation and distribution detection, and smart money signal generation for Solana tokens
Whale Tracking for Solana Tokens
Whale tracking monitors the on-chain behavior of large wallets to detect accumulation, distribution, and smart money movements before they become visible in price action. On Solana, where token ownership is highly concentrated and whale transactions can move markets instantly, tracking large holders is one of the highest-signal alpha sources available.
Why Whale Tracking Matters
A single large wallet selling 5% of a token's supply can crash the price 30-50% on thin Solana DEX liquidity. Conversely, a known profitable wallet accumulating a new token often precedes major price runs. Whale tracking converts on-chain transparency into actionable intelligence.
Key use cases:
- **Early warning**: Detect large holder sells before the price impact fully propagates
- **Smart money following**: Identify wallets with strong track records and monitor their new positions
- **Accumulation detection**: Spot gradual buying by whales who split orders to avoid detection
- **Distribution detection**: Catch insiders or early investors offloading positions
- **Risk assessment**: Evaluate token concentration risk before entering a position
What Constitutes a Whale
Whale classification depends on context. A wallet holding $50K of a $1M market cap token is a whale; the same $50K in SOL is not. Use relative and absolute thresholds:
Absolute Thresholds
| Category | Trade Size | Portfolio Size | Typical Behavior | |----------|-----------|---------------|-----------------| | Retail | < 10 SOL | < 100 SOL | Reactive, follows trends | | Mid-size | 10-100 SOL | 100-1,000 SOL | Mixed strategies | | Whale | 100-1,000 SOL | 1,000-10,000 SOL | Informed, moves markets | | Mega-whale | > 1,000 SOL | > 10,000 SOL | Market makers, funds, insiders |
Relative Thresholds (Per Token)
| Metric | Threshold | Significance | |--------|-----------|-------------| | % of supply held | > 2% | Significant holder | | % of daily volume | > 5% single trade | Market-moving transaction | | Top N holders | Top 20 | Core holder group | | Concentration ratio | Top 10 hold > 50% | High concentration risk |
Use both absolute and relative metrics. A 50 SOL trade in a $200K market cap token is whale-level; the same trade in a $50M token is retail.
Accumulation vs Distribution Patterns
Accumulation Signals
Accumulation is when a whale builds a position over time, often trying to minimize price impact.
**DCA pattern** (Dollar-Cost Averaging):
- Multiple buys of similar size over hours or days
- Buys at regular intervals (e.g., every 30 minutes)
- Position grows steadily without large single transactions
**Dip buying**:
- Buys concentrated during price dips
- Larger-than-usual purchases when price drops > 10%
- Position increases during periods of general selling
**Multi-wallet accumulation**:
- New wallets funded from the same source
- Each wallet buys small amounts of the same token
- Positions later consolidated into a primary wallet
**Detection heuristics**:
accumulation_score = 0 if buy_count > sell_count * 2: accumulation_score += 2 if avg_buy_size > avg_sell_size: accumulation_score += 1 if position_change_7d > 0: accumulation_score += 1 if buys_during_dips > buys_on_pump: accumulation_score += 2 if dca_pattern_detected: accumulation_score += 2 # Score >= 4 = likely accumulating
Distribution Signals
Distribution is when a whale reduces or exits a position, often gradually to avoid crashing the price.
**Gradual selling**:
- Multiple sells over days, each < 5% of position
- Sells increase in frequency over time
- Position shrinks steadily
**Transfer to exchange**:
- Tokens transferred to known exchange deposit addresses
- Large transfers to Binance, OKX, Bybit hot wallets
- Often precedes selling by hours or days
**Rapid exit**:
- Single large market sell (> 20% of position)
- Often triggers cascading liquidations
- Visible as large red candles with high volume
**Detection heuristics**:
distribution_score = 0 if sell_count > buy_count * 2: distribution_score += 2 if position_change_7d < 0: distribution_score += 1 if transfers_to_exchanges > 0: distribution_score += 3 if sell_frequency_increasing: distribution_score += 2 if position_pct_remaining < 50: distribution_score += 1 # Score >= 4 = likely distributing
Whale Watchlist Management
Maintain a watchlist of wallets worth tracking. Sources for discovering whale wallets:
Discovery Methods
1. **Top holders per token**: Query `getTokenLargestAccounts` for any token of interest 2. **Large transaction monitoring**: Watch for trades > 100 SOL on key tokens 3. **Profitable trader rankings**: Use SolanaTracker or Birdeye top trader endpoints 4. **Known fund wallets**: Public wallet addresses of crypto funds and DAOs 5. **Cross-referencing**: Wallets that appear in top holders of multiple successful tokens
Watchlist Structure
Each watchlist entry should track:
whale_entry = {
"address": "WhaLe...",
"label": "Smart money #47", # Human-readable label
"discovered": "2026-01-15", # When added to watchlist
"discovery_reason": "top_trader", # How they were found
"win_rate": 0.72, # Historical trade win rate
"avg_pnl": 3.4, # Average PnL multiplier
"tokens_tracked": 12, # Number of tokens held
"last_active": "2026-03-09", # Last on-chain activity
"tags": ["dex_trader", "sniper"], # Classification tags
}Wallet Classification Tags
| Tag | Description | |-----|-------------| | `sniper` | Buys tokens within minutes of launch | | `dex_trader` | Primarily trades on DEXes | | `accumulator` | Builds positions gradually | | `flipper` | Short hold ti
A comprehensive collection of 67 ready-to-use trading, DeFi, and quantitative finance Agent Skills. Works with Claude Code, Cursor, Codex, Gemini CLI, and 30+ other tools.
Repo: agiprolabs/claude-trading-skills
Other skills on trading-skills.
- /backtrader
Event-driven backtesting with bar-by-bar execution, complex order types, multiple analyzers, and custom indicators
Open skill - /birdeye-api
Solana token market data via Birdeye — prices, OHLCV, trades, token metadata, security checks, and trader activity
Open skill - /coingecko-api
Broad crypto market data from CoinGecko covering 13,000+ tokens. Global market stats, historical price data going back years, exchange volumes, trending tokens, and category filters. Best for macro analysis and long-term historical data.
Open skill - /cointegration-analysis
Cointegration testing for pairs trading using Engle-Granger, Johansen, and rolling stability analysis
Open skill - /copy-trading
Wallet evaluation, monitoring, and copy-trade strategy design for Solana DEX trading
Open skill - /correlation-analysis
Cross-asset correlation analysis including rolling correlation, hierarchical clustering, tail dependence, and regime-dependent correlation
Open skill

