Whale Tracking Prompt
Interprets a large transfer correctly by classifying counterparties before concluding anything about buying or selling.
/ quick answer
Use whenever a whale alert fires and you need to know whether it means anything. Interprets a large transfer correctly by classifying counterparties before concluding anything about buying or selling.
A large on-chain transfer occurred. Determine what it actually means. Do not assume selling. EVENT Token + chain: [DATA] From / to addresses (with any known labels): [DATA] Size + USD value: [DATA] Sender's holdings and history summary: [DATA] Recent related transfers: [DATA] Answer: 1. Counterparty classification: exchange deposit, exchange withdrawal, bridge, contract interaction, or likely self-transfer — with reasoning. 2. Does this change the sender's actual exposure? Yes / No / Unclear, and why. 3. Three plausible explanations ranked by likelihood. 4. What additional on-chain evidence would distinguish between them. 5. Market relevance: none, minor, or material relative to the token's liquidity. State clearly when the data is insufficient. Do not produce a trading recommendation.
Classification: likely self-transfer — destination is a fresh address funded only by the sender, with no exchange interaction history. Exposure change: No. Ranked explanations: (1) custody reorganisation, (2) preparation for OTC, (3) collateral move. Distinguishing evidence: whether the destination subsequently interacts with an exchange deposit address. Market relevance: none at current liquidity.
What does the Whale Tracking Prompt prompt do?
Use whenever a whale alert fires and you need to know whether it means anything.
Which AI models work with this prompt?
It is model-agnostic: it works with any capable general model. Replace the bracketed variables with your own context before running it.
What output should I expect?
Classification: likely self-transfer — destination is a fresh address funded only by the sender, with no exchange interaction history. Exposure change: No. Ranked explanations: (1) custody reorganisation, (2) preparation for OTC, (3) collateral move. Distinguishing evidence: whether the destination.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →Whale Wallet
A whale wallet holds a position large enough that its trades move price or signal intent — which makes it worth watching and easy to misread.
- →Smart Money
Smart money is a label for wallets with a documented history of profitable, early positioning — a research filter, not a signal to copy blindly.
- →Wallet Tracking
Wallet tracking is the practice of monitoring specific addresses and getting notified when they trade, transfer or interact with contracts.
- →Crypto Automation
Crypto automation is rule-based execution of monitoring, alerting and recurring on-chain actions, so decisions are made once and applied consistently.
Related workflows
Turn this into a repeatable process.
- →Track A Whale Wallet
Monitor a single large address correctly: separate real position changes from custody moves before drawing any conclusion.
- →AI Crypto Research Workflow
A repeatable research loop: turn a question into market data, on-chain evidence and a written risk view before any position is considered.
- →Smart Money Tracking Workflow
Build a curated wallet watchlist, monitor it for meaningful trades, and use alerts as research triggers rather than buy signals.
- →Build An On-chain Alert System
Assemble a monitoring pipeline that watches addresses, tokens and contracts and delivers deduplicated, contextual alerts.
Related tool stacks
The tools that run it in production.
- →Smart Money Stack
Wallet tracker, on-chain analytics, alert delivery and an AI layer that turns raw wallet events into researchable signals.
- →Crypto Automation Stack
Automation platform, data APIs, alerting and optional wallet execution — the operational layer for monitoring and recurring actions.
- →On-chain Research Stack
Explorer, indexer and analytics layers combined so wallet and token questions get answered with verifiable data.
Related prompts
Reusable prompts for this job.
- →Token Research Prompt
Structures a full token due-diligence pass: mechanics, liquidity, concentration, bear case and unverifiable claims flagged explicitly.
- →Wallet Analysis Prompt
Turns a transaction export into a behavioural profile: strategy type, timeframes, risk pattern and whether the wallet is worth watching.
- →Smart Money Analysis Prompt
Tests whether a group of 'smart money' wallets is genuinely informative or a survivorship-biased label.
- →Build An Alert Workflow Prompt
Designs a complete alerting pipeline — events, sources, thresholds, deduplication and delivery — from a plain description.
Related use cases
How people apply it, and what came out.
- →Track A Whale Wallet
A trader replaced noisy whale alerts with a labelled watchlist and counterparty classification, cutting alerts by 94% while keeping the useful ones.
- →Create An On-chain Alert System
A purpose-built alert pipeline with enrichment and deduplication achieved a 30% action rate, versus near-zero for off-the-shelf feeds.
- →Find Smart Money Activity
A research group verified 40 leaderboard wallets and kept only 11, turning a noisy signal source into a usable research queue.
- →Research A Token With AI
A structured AI research pass cut token screening from three hours to 35 minutes and produced documented passes instead of impulse entries.
Comparisons & alternatives
Pick between the options.
- →On-chain Data vs Exchange Data
On-chain data shows verifiable wallet-level behaviour; exchange data shows aggregate price discovery. Serious research needs both.
- →Smart Money vs Technical Analysis
Smart money tracking reads who is positioning; technical analysis reads how price behaves. They answer different questions and fail differently.