Crypto Agent Design Prompt
Specifies an AI crypto agent's tools, permissions, guardrails and evaluation before a single line is written.
/ quick answer
Use to design a research or monitoring agent, and to decide whether it should ever be allowed to sign. Specifies an AI crypto agent's tools, permissions, guardrails and evaluation before a single line is written.
Design an AI agent for this crypto task. Security boundaries are part of the specification. TASK: [what the agent should do] Data it needs: [LIST] Should it execute transactions? [YES / NO] Available tools: [model, RPC/indexer, analytics API, wallet type, automation platform] Produce: 1. Scope: exactly what the agent does and what it explicitly does not do. 2. Tool list with typed inputs and outputs, split into read tools and write tools. 3. System prompt: role, method, output format, and refusal conditions. 4. Data validation: how the agent verifies inputs before reasoning on them. 5. Guardrails in deterministic code, not in the prompt: allowlists, value caps, rate limits, simulation, kill switch. 6. Human-in-the-loop points and what is shown to the human for approval. 7. Failure modes specific to crypto: hallucinated addresses, stale prices, spoofed tokens, MEV exposure. 8. Evaluation set: 10 test cases including adversarial inputs, with expected behaviour. 9. Logging and audit requirements. If the task does not require signing, say so and design a read-only agent.
Scope: monitor 15 wallets, research flagged tokens, produce a briefing. Does NOT sign. Read tools: get_wallet_activity, get_token_liquidity, get_contract_facts. Write tools: none. Refusals: no price predictions, no advice, no unverifiable claims. Validation: every address checksummed and resolved against the indexer before use. Guardrails: rate limit, 30-min data staleness cap. Eval: includes a spoofed token with a lookalike symbol; expected behaviour is flagging the mismatch.
What does the Crypto Agent Design Prompt prompt do?
Use to design a research or monitoring agent, and to decide whether it should ever be allowed to sign.
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?
Scope: monitor 15 wallets, research flagged tokens, produce a briefing. Does NOT sign. Read tools: get_wallet_activity, get_token_liquidity, get_contract_facts. Write tools: none. Refusals: no price predictions, no advice, no unverifiable claims. Validation: every address checksummed and resolved ag.
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Related concepts
The vocabulary this page depends on.
- →On-chain Agent
An on-chain agent is an AI agent with read access to blockchain data and a tightly scoped ability to propose or execute transactions.
- →Crypto Automation
Crypto automation is rule-based execution of monitoring, alerting and recurring on-chain actions, so decisions are made once and applied consistently.
- →Browser Agent
A browser agent drives a real web browser — navigating, clicking, typing and reading pages — to complete tasks on sites that have no API.
- →Web3 Wallet
A Web3 wallet stores your keys and signs transactions, letting you hold assets and connect to on-chain applications without an intermediary.
Related workflows
Turn this into a repeatable process.
- →AI Agent + Web3 Execution
Give an AI agent on-chain capability safely: read freely, propose openly, and sign only inside hard-coded limits.
- →Automated Crypto Alerts
Define the conditions that would change a decision, monitor them automatically, and receive one clean notification instead of watching charts.
- →Automate Repetitive Web3 Actions
Replace manual claims, approvals and rebalances with scoped automations that cannot spend more than you allowed.
- →Design an Agent Architecture Before Writing Code
A one-page design process that prevents the most expensive agent rebuilds.
Related tool stacks
The tools that run it in production.
- →AI Agent + Web3 Stack
Agent framework, MCP/API tools, blockchain data access and a limited signing layer — with policy enforced in code.
- →Crypto Automation Stack
Automation platform, data APIs, alerting and optional wallet execution — the operational layer for monitoring and recurring actions.
- →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.
Related prompts
Reusable prompts for this job.
- →Recurring Crypto Workflow Prompt
Specifies a safe recurring on-chain automation with spend caps, idempotency, failure handling and a kill switch.
- →Crypto Research Agent Prompt
System prompt for a research agent that must cite sources, separate fact from inference, and refuse to predict prices.
- →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.
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.
- →Monitor A Crypto Portfolio
Aggregating six addresses across three chains revealed that a portfolio believed to hold 14 positions actually held one concentrated bet.
- →Automate Repetitive Web3 Actions
Automating reward claims and gas top-ups with session keys and spend caps saved about 5 hours per month with no unbounded authority.
Comparisons & alternatives
Pick between the options.
- →AI Agent vs Trading Bot
A trading bot executes fixed rules deterministically; an AI agent interprets context and decides which steps to take — powerful for research, risky for execution.
- →Web2 Apps vs Web3 Apps
Web2 apps authenticate with accounts and store state on private servers; Web3 apps authenticate with a wallet signature and keep state on a public chain.
- →Single Agent vs Multi-Agent System
One well-equipped agent beats a crowd for most jobs; multi-agent wins on genuinely separable, parallel work.
- →Browser Agent vs API Automation
APIs win whenever they exist; browser agents exist for the systems that never gave you one.