AI trading mentor: questions, trade review and limitations

An AI trading mentor can help you question a trade plan and reflect on your decisions, but its answers can be wrong. The tool on this page is a price-entry trade analyzer with Quick and Detailed modes. OneTradeJournal's paid AI Trading Mentor has a separate chart-screenshot workflow inside the journal. Neither is an automated trader or a source of trading signals.

Choose the review you actually need

Use the form above to review a single proposed setup from your own prices. It compares planned risk and reward, then can generate written feedback. It cannot establish how you trade over time from an isolated entry, and it does not contain the full chart-mentor conversation shown elsewhere in the product.

The paid AI Trading Mentor accepts chart screenshots for educational review. Ask Your Journal is a different paid feature for questions about trades you have recorded. Those names describe different workflows. The form above only reviews the information you enter; it cannot see a broker account or a chart you have not supplied.

OneTradeJournal is a manual journal. You record trades and their context yourself, including emotions, mistakes, plan deviation and notes. Those records give a review something concrete to examine; they do not guarantee that an AI explanation identifies the true cause of a result.

Quick mode checks entered levels

The Quick form includes instrument, direction, Entry, Target, Stop Loss, Lots or Qty, Capital and Strategy. Select the instrument deliberately. For shares, use cash-share prices and share quantity. For a derivative, keep prices and quantities consistent with that contract rather than mixing index points with option premiums.

Entry describes your assumed trading price, Stop Loss your planned loss exit and Target your planned favourable exit. Capital is the account amount used for the capital-risk comparison. Lots or Qty is multiplied by the selected instrument's quantity convention. A valid-looking amount does not confirm that the actual contract size is correct.

The calculated loss and reward are price distances multiplied by units. They exclude the effects of actual execution and charges. A planned loss amount should not be read as a guaranteed final loss. A favourable ratio also does not establish the chance of success.

A worked example and a useful review question

Take a fictional cash-share long setup: Entry ₹800, Stop Loss ₹780, Target ₹840, Qty 25 shares and Capital ₹50,000. This is an arithmetic illustration, not a stock pick. The stop distance is ₹800 − ₹780 = ₹20 per share; planned money risk is ₹20 × 25 = ₹500.

The target distance is ₹840 − ₹800 = ₹40 per share, giving ₹1,000 of planned reward. Reward divided by risk is ₹40 ÷ ₹20 = 2, or risk:reward of 1:2. The ₹500 loss is 1% of the assumed ₹50,000 capital. It is also a 2.5% price distance from entry; these percentages divide the loss by different starting amounts.

An example review request could be: 'These are my planned share prices and quantity. Explain the planned loss, then tell me which assumptions are missing. Do not propose a stock or predict the next move.' This is a sample question written for this guide, not an actual AI response or a claim about a successful trade.

Useful follow-up questions concern evidence: What makes the stop meaningful? Is the entry already available or conditional? Does an event fall inside the holding period? What cost or execution assumption could change the result? The risk and reward tool can check the distance arithmetic separately.

Detailed mode adds your reasoning

Detailed mode adds timeframe, market context, strategy, reasoning and a checklist. Use the reasoning field to explain the rule you were following and what would invalidate the idea. Distinguish observations you can show from expectations you have not tested.

• Name the instrument and contract where relevant, and identify the chart period behind your observation.
• Explain the trigger that would make an entry possible. A level marked on a screenshot is not a record of an executed order.
• State the original stop and target assumptions before describing any later changes.
• Describe an emotion as your observation, such as impatience or fear of missing out; do not ask the model to diagnose you.
• Ask which information is missing and whether your stated assumptions contradict each other.

Detailed mode includes summary scores and probability-related cards. These rely on fixed rules and assumed success rates, rather than a measured record of your strategy. Its Confidence percentage is based on how the response is structured. None of these labels demonstrates that an answer is correct or a trade is likely to win.

Review behaviour without inventing a diagnosis

A helpful journal question is specific: 'I changed my planned stop after price moved against me. Compare that action with the plan I wrote.' It gives the reviewer an observable action. A vague prompt such as 'fix my mindset' leaves too much room for invented explanations.

The trading psychology journal guide suggests details to record. If a later review identifies repeated mistakes, check the underlying entries before accepting the pattern. Missing losses, inconsistent tags or a small selection of trades can distort what the record appears to show.

The product's behaviour flags are heuristics, meaning simple pattern checks, rather than diagnoses. A discipline score describes the journal's rule-based assessment. It cannot prove that you will follow a rule tomorrow or prevent an order. Read trading with discipline for a separate process discussion.

Keep the chart, the explanation and the outcome distinct

When using the paid screenshot workflow, include enough visible context to identify the instrument, timeframe and levels being discussed. Explain your annotations in text if they could be ambiguous. A cropped image cannot establish information outside its edges, and a model can misread a visible label.

Before relying on a factual statement, verify it with the relevant original source or your trade records. Check price arithmetic independently. For a market event or exchange rule, confirm the date and scope instead of treating a generated answer as a current notice.

After the trade, record what actually happened before asking for a review. Compare the action with your written rule, then note the outcome separately. A winning trade can involve a rule breach, and a losing trade can follow the plan. Comparing your plan with your actions does not establish that using AI improves returns.

AI trading mentor questions

Sources

• OneTradeJournal: manual records and paid mentor features (checked October 2026).