After a practice session it is tempting to hand the log to a model and wait to be told the truth. That is not what automated review is for. It is a second pass over text and tags you already produced. It does not see the tape you saw. It does not know whether your stop was structural or hopeful. It does not know if you peeked.
Replay Trader includes AI analysis of practice trades as a review aid after the session. This page states the scope of that kind of aid — on this product or any other — without accuracy claims. If a vendor implies the model can grade your edge, treat that as marketing, not measurement.
The companion piece on using AI to analyse practice trades is a do/don't list so you do not outsource clicks. This one is the honesty document: what the review layer is even allowed to mean.
What automated review can plausibly inspect
Assume the input is a structured log, not a screenshot dump and not a chat that begins "here's how I would have traded Nifty tomorrow."
Completeness. Did every decision row include setup tag, planned invalidation, follow-plan Y/N, and an urge field? A model can list missing cells. That is clerical. It is still useful, because most journals die of empty columns.
Clustering of labels you wrote. If you tagged chase twelve times in the 9:15–10:15 window and twice after lunch, a summary can put that in one paragraph. The clustering is only as honest as the tags. Garbage in, tidy paragraph out.
Contradiction spotting. You wrote "breakout" and also "entered inside the range." A review pass can flag the sentence clash. It cannot tell you which sentence is true.
Question generation. "You took four decisions after a two-loss stop you had written. What was the rule at that moment?" That is a useful prompt. It is not a finding.
Format hygiene. R-multiples instead of fantasy rupees; session IDs; no mixing of live and replay rows. Hygiene is not analysis of markets.
None of the above requires the model to be "good at trading." It requires the model to read a table. That is the ceiling worth paying attention to.
What it cannot tell you
Whether the setup works. Automated review of your practice trades is not a backtest of NSE, not an expectancy study, and not a ranking of breakout versus pullback. Even a clean 300-decision month is a self-observation sample. A paragraph from a model does not turn it into research.
Whether you would have been filled. Historical replay has no live order book. The model cannot invent slippage, partials, or rejected orders from a candle log. If it writes as if fills were certain, it is storytelling.
Whether you were afraid. Fear is not in the CSV. You can tag fear yourself. The model can count the tag. It cannot measure the thing.
Whether the next candle "should" have been obvious. Post-session text has hindsight baked in if you wrote the row after you knew the outcome. Reviewing that text reproduces the hindsight. It does not remove it. Reviewing practice trades without rewriting history is still your job.
Accuracy of the market call. There is no published, verified accuracy rate for Replay Trader's AI review — and this article will not invent one. Do not treat summaries as predictions, signals, or a second opinion on direction.
Your live readiness. A flattering recap of a green sim week is not a licence to size up. Practice remains practice.
A review contract (paste this above the log)
Write the contract before you paste anything into a review tool, including this product's.
You are reviewing a practice log, not advising a live trade.
Do not recommend buying or selling any NSE name.
Do not estimate win rate, expectancy, or "edge."
Do not praise P&L.
List: missing fields; tag contradictions; urge-tag clusters by session window.
Ask three questions I have to answer from memory of the decision, not from the outcome.
If the log is too thin to summarise, say "thin" and stop.
If the tool cannot obey that contract — if it insists on calling setups "high probability" or inventing a coaching personality — do not use it for the month's close-out. Use a ninety-second debrief and a human weekly read instead.
Failure modes specific to "AI reviewed it"
Flattery. Models trained to be helpful will often sound like a mentor. "Your patience in the lunch hour is improving" may be false. Score decision quality with the rubric you wrote. Let the model only audit whether the rubric was filled.
Pattern invention. With fifty rows, a summary can "find" a story that is one noisy cluster. Early-sample noise is the subject of the first fifty decisions piece. Do not let a fluent paragraph outrun the count.
Authority laundering. "The AI said my breakouts are my edge" is how a review aid becomes a superstition. The authorised claim is narrower: repeated historical practice can help you see which setups you appear to handle with cleaner process. A model restating your tags is not additional evidence.
Mid-session chat. If you query a model during replay, you have added a second brain that did not have to take the risk of the click. Review is after. During is outsourcing.
Clean inputs, dirty memory. If you edit the log to look consistent before review, the aid will certify the edit. The honest version is the ugly CSV.
How this sits on Replay Trader
Allowed product claim: AI analysis as a review aid after practice trades. Not allowed: accuracy percentages, "the AI knows if you should have entered," "automated coach that makes you profitable," or any implication that 300 practice decisions plus a summary equals expertise.
Use the aid to catch empty fields and repeated urge tags. Use your own close-out — scorecard, retrospective, written plan — to decide what the month meant. Keep those jobs separate.
If you do not want a model in the loop at all, you can still run the month. The review layer is optional. The log is not.
Indian evenings after office are when this temptation is strongest: you are tired, the session felt messy, and a fluent paragraph would feel like closure. Closure that you did not earn is how a review aid becomes a storyteller. Close the replay. Fill the row. Then, if you still want a second pass, paste the contract first.
Let the model audit the table. You still own the judgement. Join the waitlist.
Related reading
- The 300-Trade Experiment: How Much Can You Learn From 30 Days of Trading Practice?
- Using AI to Analyse Practice Trades (Without Outsourcing Thinking)
- How to Review Practice Trades Without Rewriting History
- Decision Quality in Trading Practice
Educational note
Educational practice content only. Not investment advice. No guaranteed returns. Practice ≠ live profitability.