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.
/ quick answer
An investor screened new tokens by reading threads and skimming charts, with no consistent checklist, and had twice bought tokens that could not be exited at size. A structured AI research pass cut token screening from three hours to 35 minutes and produced documented passes instead of impulse entries.
What is the Research A Token With AI use case?
An investor screened new tokens by reading threads and skimming charts, with no consistent checklist, and had twice bought tokens that could not be exited at size.
What was the outcome?
Screening time fell from around 3 hours to 35 minutes per token. Of 14 tokens screened in two months, 11 were documented passes — 4 for exit-liquidity limits and 3 for non-timelocked admin keys — decisions that previously would have been made on narrative alone.
Which tools were used?
Claude with the token research prompt — structured analysis and bear case, Block explorer — contract facts, mint authority, deployer history, DEX Screener — pool depth and impact estimates, Notion — thesis log with dates.
/ continue exploring
Related concepts
The vocabulary this page depends on.
- →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.
- →Crypto Automation
Crypto automation is rule-based execution of monitoring, alerting and recurring on-chain actions, so decisions are made once and applied consistently.
- →Gas Fee
A gas fee is the network payment for computation and storage in a transaction, priced by demand rather than by trade size.
- →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.
Related workflows
Turn this into a repeatable process.
- →AI Token Research Workflow
Screen a token in under 30 minutes: contract facts, liquidity structure, holder concentration and a written risk verdict.
- →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.
- →Analyze A Wallet With AI
Turn a raw transaction history into a readable profile: strategy, holding periods, risk behaviour and realised performance.
- →Track A Whale Wallet
Monitor a single large address correctly: separate real position changes from custody moves before drawing any conclusion.
Related tool stacks
The tools that run it in production.
- →AI Crypto Research Stack
A read-only research stack combining an AI assistant, web search, market data and on-chain analytics to screen assets quickly.
- →On-chain Research Stack
Explorer, indexer and analytics layers combined so wallet and token questions get answered with verifiable data.
- →Crypto Automation Stack
Automation platform, data APIs, alerting and optional wallet execution — the operational layer for monitoring and recurring actions.
- →AI Research & Knowledge Stack
Default toolset for analysts, founders and creators doing deep research with AI.
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.
- →Crypto Research Agent Prompt
System prompt for a research agent that must cite sources, separate fact from inference, and refuse to predict prices.
- →Crypto Market Analysis Prompt
Produces a structured market brief: regime, liquidity conditions, sector rotation, catalysts and what would change the view.
- →Crypto Portfolio Analysis Prompt
Audits a portfolio for hidden concentration, correlated exposure, custody risk and missing exit plans.
Related use cases
How people apply it, and what came out.
- →Build An AI Crypto Research Agent
A read-only research agent produced daily briefings on a 30-token watchlist, cutting a 90-minute manual routine to a 10-minute review.
- →Analyze Wallets With AI
AI profiling of 60 candidate wallets cut a week of manual review to an afternoon and identified 4 worth monitoring.
- →Tech Creator Replaces a Research Assistant With a Workflow
A YouTuber cut their research time per video from 8 hours to 90 minutes.
- →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.
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.
- →AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.