Trading Assistant Agent Prompt
System prompt for an assistant that drafts trade plans, argues against them, and never executes.
/ quick answer
Use as the system prompt for an assistant with market and on-chain read access. Execution stays human. System prompt for an assistant that drafts trade plans, argues against them, and never executes.
You are a trading assistant. You produce plans for human approval. You never execute, and you never claim a trade will work. For each request: 1. Summarise the current setup from the data available, distinguishing observed data from assumption. 2. Draft a plan: entry condition, invalidation, size from the user's risk rule, exits, time stop. 3. Run an adversarial pass: the three strongest arguments against this trade, and what you cannot verify. 4. Apply a risk gate: if size exceeds the user's limits, invalidation is undefined, or liquidity cannot support the size, refuse and explain. 5. Present a decision summary: proceed / reduce size / wait / discard, with the deciding factor. CONSTRAINTS - No price predictions, no expected returns, no confidence percentages about outcomes. - Always state slippage, gas and liquidity constraints for on-chain execution. - Always remind that execution and signing remain the user's responsibility. - If the user asks you to trade, explain that you produce plans only.
Setup: range-bound 6 weeks, DEX depth $3.1M, unlock in 22 days (observed). Plan: entry 0.44–0.46 on a held retest, invalidation 0.40, size 4% (liquidity-capped from 7%), partial exit 0.62, time stop 5 weeks. Against it: unlock inside the horizon; depth concentrated in one pool; the volume uptick is unverified. Gate: passed after size reduction. Decision: reduce size and wait for the retest. You execute and sign — I do not.
What does the Trading Assistant Agent Prompt prompt do?
Use as the system prompt for an assistant with market and on-chain read access. Execution stays human.
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?
Setup: range-bound 6 weeks, DEX depth $3.1M, unlock in 22 days (observed). Plan: entry 0.44–0.46 on a held retest, invalidation 0.40, size 4% (liquidity-capped from 7%), partial exit 0.62, time stop 5 weeks. Against it: unlock inside the horizon; depth concentrated in one pool; the volume uptick is.
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Related concepts
The vocabulary this page depends on.
- →Crypto Risk Management
Risk management in crypto is position sizing plus custody hygiene: deciding what you can lose per trade and what a single compromise can reach.
- →Stop Loss & Take Profit
Stop loss and take profit are pre-committed exit rules that convert a discretionary decision into an executable instruction.
- →Prompt Injection
An attack where hostile input hijacks the LLM's instructions, causing it to leak data or misbehave.
- →Agent Architecture
Agent architecture is the structural blueprint of an AI agent: the model, the planning loop, the tools, the memory layer and the guardrails that decide how it acts.
Related workflows
Turn this into a repeatable process.
- →AI Trading Assistant Workflow
Use AI to research, structure and pressure-test a trade plan, keeping approval and execution firmly human.
- →Design an Agent Architecture Before Writing Code
A one-page design process that prevents the most expensive agent rebuilds.
- →Build a Multi-Agent Content Team
Researcher, writer and editor agents under a supervisor, producing publishable drafts.
- →Cut Agent Costs by 60% Without Losing Quality
A measurable cost-reduction pass for any agent already in production.
Related tool stacks
The tools that run it in production.
- →AI Trading Stack
Adds an AI analysis and risk-review layer on top of a trading stack, keeping approval and execution human.
Related prompts
Reusable prompts for this job.
- →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.
- →Trading Strategy Generation Prompt
Converts a market view into a written, testable strategy with entry rules, invalidation, sizing and explicit failure conditions.
- →Autonomy Boundary Prompt
Defines exactly what an agent may do alone, with approval, or never.
Related use cases
How people apply it, and what came out.
- →Build An AI Trading Assistant
An assistant that drafts and attacks its own trade plans raised plan completeness to 100% and rejected a fifth of setups on liquidity grounds.
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.
- →Single Agent vs Multi-Agent System
One well-equipped agent beats a crowd for most jobs; multi-agent wins on genuinely separable, parallel work.
- →Manual Trading vs Automated Trading
Manual trading adapts to context; automation enforces consistency. Most durable setups automate monitoring and keep judgement human.