AI Trading Agent Stop Loss Rules Prompt

Paper-first boundary

Trading Boy does not execute live trades, hold funds, or provide financial advice. This page is for simulated paper-trading review, prompt design, journal structure, and human review. It is not a signal feed, broker instruction, or promise of live trading results.

When to use this page

Use it when stop distance or invalidation is the main reason a paper setup becomes eligible, reduced, or skipped.

The search intent behind how to write an AI trading agent stop loss rules prompt is usually practical: the user wants a reusable asset, an example, and a checklist. This page treats those variants as one owner page rather than splitting guide, example, checklist, and template into thin sibling pages.

Use the asset only after the paper-trading workflow, prompt version, permission boundary, and journal output format are clear. If the user cannot identify the setup, invalidation, risk field, or review question, the next action should be a skip, caveat, or human review rather than a confident simulated entry.

Stop-rule prompt asset

Review field	Pass condition	Paper-mode boundary
Invalidation source	Names whether invalidation comes from structure, time, volatility, or rule failure.	The prompt rejects vague stop placement.
Distance check	Requires stop distance before simulated size is chosen.	Size cannot be selected before risk is measurable.
Move condition	Defines whether a stop can move and what evidence allows it.	The agent cannot move a stop to avoid a paper loss.
Exit label	Labels stop hit, time exit, rule exit, or manual review.	Every paper exit keeps the reason visible.
Review caveat	Marks slippage and fill assumptions as simulated.	The prompt does not imply live execution quality.

Reusable prompt or worksheet text

Role: You are helping organize a simulated paper-trading review. You may summarize context, apply written rules, identify missing fields, and prepare journal evidence. You may not route live trades, request secrets, or provide financial advice.

Required output: Decision type, setup name, rule version, thesis, invalidation, paper risk, data caveat, behavior tag, and one human review question.

Skip rule: If setup, invalidation, paper risk, or data quality is missing, produce a skip or excluded row. Do not invent the missing field to make the record look complete.

Review handoff: Send the output to the paper journal, evaluation checklist, or human review checklist. Choose one next paper-mode action: collect more samples, tighten one field, pause, or revert a prompt change.

Example paper workflow

Scenario: A simulated breakout has a wide invalidation level. The stop loss rules prompt makes the agent calculate paper risk first, then either reduce simulated size or skip because the stop distance breaks the rule.

Good output: The agent explains that the setup is valid but skipped because stop distance would exceed the paper risk limit.

Weak output: The agent says the stop can be tightened later without a written rule.

Decision: The reviewer keeps the evidence in paper mode, checks the output with the AI paper trading agent evaluation checklist, and records any prompt change in AI trading agent prompt versioning.

Use it with these controls

Prompt version: every sample should name the version that produced the output.
Output format: the agent should use consistent fields for entries, exits, skips, and missed setups.
Risk gate: size, exposure, drawdown, stop distance, and pause rules should be checked before judging the idea.
Human review: a person should approve prompt, risk, or workflow changes before the next sample.
Data privacy: private exchange credentials, account identifiers, and secret values should stay out of prompts and screenshots.

How it supports ranking

This owner page consolidates the guide, example, template, checklist, and for-paper-trading variants into one durable page. That gives searchers a complete answer without flooding the sitemap with near duplicates.

It also links into the surrounding Trading Boy system: paper-trading hub, AI paper agent, prompt template, output format, risk controls, permission boundaries, and paper-trading limitations.

Related AI paper-agent pages

Use these links to move between setup, output, risk, journal, and review pages without leaving the paper-first cluster.

AI Trading Agent Stop Loss Rules Prompt FAQ

What is a stop loss rules prompt for?

It makes invalidation and paper risk explicit before a simulated entry is counted.

Can the agent change a stop after entry?

Only if the written rule allows it and the change is recorded before the outcome is known.

Does this prompt prove live stop execution?

No. Paper stops are simulated assumptions and should be reviewed separately from live fills.