Smart Money Analysis Prompt
Tests whether a group of 'smart money' wallets is genuinely informative or a survivorship-biased label.
/ quick answer
Use before building a watchlist or copying any wallet cohort. Tests whether a group of 'smart money' wallets is genuinely informative or a survivorship-biased label.
Evaluate whether this set of wallets is genuinely informative. Assume the "smart money" label is unproven. WALLETS (address, claimed PnL, period, position count, notable trades): [LIST] Assess: 1. For each wallet: is performance broad-based or concentrated in one or two positions? Show the concentration. 2. Survivorship and selection bias in how these wallets were identified. 3. Signs of non-replicable edge: insider timing, wash activity, MEV, launch access. 4. Whether their entries were realistically copyable at the time (liquidity, timing, gas). 5. Which wallets, if any, deserve monitoring — and the filters to apply. 6. What would falsify the "informative" conclusion within 60 days. Be sceptical by default. Do not recommend copying without filters.
Wallet A: 84% of PnL from one position — not evidence of skill. Wallet C: profitable across 27 positions and two market phases; broad-based. Selection bias: all wallets were chosen from a post-hoc profit leaderboard, so failures are invisible. Non-replicable edge: Wallet B bought within 40 seconds of pool creation twice — likely launch access. Monitor: C only, filtered to buys over $20k in pools over $2M. Falsified if C's next 10 tracked entries underperform a majors benchmark.
What does the Smart Money Analysis Prompt prompt do?
Use before building a watchlist or copying any wallet cohort.
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?
Wallet A: 84% of PnL from one position — not evidence of skill. Wallet C: profitable across 27 positions and two market phases; broad-based. Selection bias: all wallets were chosen from a post-hoc profit leaderboard, so failures are invisible. Non-replicable edge: Wallet B bought within 40 seconds o.
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Related concepts
The vocabulary this page depends on.
- →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.
- →On-chain Data
On-chain data is the public record of every transaction, balance and contract call — the raw material for wallet tracking and market research.
Related workflows
Turn this into a repeatable process.
- →Smart Money Tracking Workflow
Build a curated wallet watchlist, monitor it for meaningful trades, and use alerts as research triggers rather than buy signals.
- →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.
- →AI Token Research Workflow
Screen a token in under 30 minutes: contract facts, liquidity structure, holder concentration and a written risk verdict.
- →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.
- →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.
- →Wallet Analysis Prompt
Turns a transaction export into a behavioural profile: strategy type, timeframes, risk pattern and whether the wallet is worth watching.
- →Deep Research Prompt Template
Reusable Deep Research prompt that produces cited, structured reports every time.
- →Sourced Research Brief Prompt
Produces a structured brief where every claim carries a citation.
- →Token Research Prompt
Structures a full token due-diligence pass: mechanics, liquidity, concentration, bear case and unverifiable claims flagged explicitly.
Related use cases
How people apply it, and what came out.
- →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.
- →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.
Comparisons & alternatives
Pick between the options.
- →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.
- →On-chain Data vs Exchange Data
On-chain data shows verifiable wallet-level behaviour; exchange data shows aggregate price discovery. Serious research needs both.
- →AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.