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Run an honest post-mortem on your last 20 journal entries
Your journal is a diary, not a dataset. Turn your own entries into the patterns you've been avoiding.
The prompt — copy and run it
Act as a rigorous but kind performance-review coach (educational analysis of MY OWN past decisions — not investment advice; never suggest a future trade, security, or market view). I will paste my recent trade-journal entries with any account-identifying details removed. Analyze ONLY what I pasted: A) PROCESS vs OUTCOME — classify each entry: followed-plan/good-outcome, followed-plan/bad-outcome, broke-plan/good-outcome, broke-plan/bad-outcome. The dangerous quadrant is broke-plan/good-outcome — flag every instance and say why it's dangerous. B) PATTERN HUNT — recurring behaviors across entries: exit behavior vs plan, sizing consistency, entry reasons that repeat in losers, emotional language that precedes plan-breaks. C) THE ONE QUESTION — the single most uncomfortable question my own entries raise, stated plainly. D) JOURNAL UPGRADE — 3 fields my entries are missing that would make next month's review sharper (e.g. planned exit at entry, regime note, emotional state). My entries: [PASTE — remove account numbers, balances, and personal details first] Rules: Judge only what I pasted; if the sample is too small to support a pattern, say 'insufficient entries' rather than inventing one. Never extrapolate to what I should trade next. If I ask for picks, refuse and return to the review.
How to use this prompt
- Copy the full prompt above with the Copy button.
- Add your context. This prompt runs as-is — paste it, then add the specific details, data, or files it should reason over.
- Paste into ChatGPT, Claude, or Gemini and run. Read the reality guardrail below before you act on the output.
Why this prompt works
The trader's own journal is the one dataset an LLM can analyze with zero advice risk — it's all in the past. The four-quadrant sort (process vs outcome) is the classic decision-quality frame, and 'broke-plan/good-outcome' is where accounts quietly learn to blow up.
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Subscribe free →Frequently asked
When should I use this prompt?
Your journal is a diary, not a dataset. Turn your own entries into the patterns you've been avoiding.
Why does this prompt work?
The trader's own journal is the one dataset an LLM can analyze with zero advice risk — it's all in the past. The four-quadrant sort (process vs outcome) is the classic decision-quality frame, and 'broke-plan/good-outcome' is where accounts quietly learn to blow up.
What mistake does this prompt help you avoid?
Pasting sensitive account data into a consumer LLM — the prompt instructs stripping account numbers, balances, and personal details before pasting.
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