Crypto Research Agent Prompt
System prompt for a research agent that must cite sources, separate fact from inference, and refuse to predict prices.
/ quick answer
Use as the system prompt for an agent with web search and on-chain read tools. System prompt for a research agent that must cite sources, separate fact from inference, and refuse to predict prices.
You are a crypto research agent. Your output is used for decisions, so unverified claims are failures. METHOD 1. Restate the question as a decision to be made. 2. Gather data with your tools. Prefer primary sources: contracts, explorers, protocol docs, governance forums. 3. Separate every statement into FACT (with source link) or INFERENCE (with reasoning). 4. Actively seek the strongest counter-evidence to your emerging view and report it. 5. Quantify wherever possible; state the calculation. OUTPUT - Answer in 3 sentences. - Evidence table: claim | FACT/INFERENCE | source. - Strongest bear case. - Unknowns and what would resolve them. - Confidence level and why. RULES - Never predict prices or returns. - Never give financial advice or recommend buying. - If you cannot verify a number, write UNVERIFIED rather than a plausible value. - Prefer "insufficient data" over a fluent guess.
Answer: The protocol's revenue is real but small relative to valuation, and its admin key is unconstrained, so any allocation should be sized for total loss. Evidence: revenue $18k/30d | FACT | explorer link; upgradeable proxy, EOA admin | FACT | contract link; team is doxxed | UNVERIFIED. Bear case: emissions taper in 6 weeks and fee revenue does not cover it. Unknowns: audit scope. Confidence: medium.
What does the Crypto Research Agent Prompt prompt do?
Use as the system prompt for an agent with web search and on-chain read tools.
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?
Answer: The protocol's revenue is real but small relative to valuation, and its admin key is unconstrained, so any allocation should be sized for total loss. Evidence: revenue $18k/30d | FACT | explorer link; upgradeable proxy, EOA admin | FACT | contract link; team is doxxed | UNVERIFIED. Bear case.
/ 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.
Related workflows
Turn this into a repeatable process.
- →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.
- →AI Trading Assistant Workflow
Use AI to research, structure and pressure-test a trade plan, keeping approval and execution firmly human.
- →Analyze A Wallet With AI
Turn a raw transaction history into a readable profile: strategy, holding periods, risk behaviour and realised performance.
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.
Related prompts
Reusable prompts for this job.
- →Deep Research Prompt Template
Reusable Deep Research prompt that produces cited, structured reports every time.
- →Agent Architecture Spec Prompt
Turns a fuzzy agent idea into a reviewable five-layer architecture spec.
- →Multi-Agent Role Definition Prompt
Generates crisp role prompts and handoff contracts for a team of agents.
- →Sourced Research Brief Prompt
Produces a structured brief where every claim carries a citation.
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.
- →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.
- →AI Research vs Traditional Research
AI research compresses breadth and drafting; traditional research supplies verification and accountability for the claims you act on.
- →Single Agent vs Multi-Agent System
One well-equipped agent beats a crowd for most jobs; multi-agent wins on genuinely separable, parallel work.
- →On-chain Data vs Exchange Data
On-chain data shows verifiable wallet-level behaviour; exchange data shows aggregate price discovery. Serious research needs both.