By name: eod-review description: End-of-day and rolling review of trade outcomes to improve rules and skills. metadata: {"openclaw":{"emoji":"📘","requires":{"bins":["python3"]}}}
End Of Day Review
Run once after market close:
python3 ${OPENCLAW_HOME:-$HOME/.openclaw}/tools/risk/eod_review.py
Outputs:
trading/learning/eod-summary.jsontrading/learning/eod-summary.md
Behavior:
- reviews today, last 5 days, and all-time tagged journal data
- generates rule/skill update suggestions
- one-run-per-day guard via
trading/learning/eod-state.json
Grading doctrine: load knowledge/wiki-highlights/JOURNAL.md and apply
the 4-dimension A/B/C/D scorecard (setup quality, execution, risk
discipline, psychology) to every trade. PnL is not the grade.
Bias post-mortem: for every losing trade AND for every rule violation
(including A-grade winners that broke a rule), load
knowledge/wiki-highlights/MUNGER.md and identify which of the 12
starred tendencies were active. Be specific. Common firings on bad
trades:
- Loser held too long → #11 Pain-Avoiding Denial + #14 Deprival Superreaction (refusing to take the loss that was already real on the books)
- Doubled down on a loser → #14 Deprival Superreaction + #5 Inconsistency-Avoidance (defending the original thesis instead of re-evaluating)
- Chased a breakout late → #15 Social-Proof + #18 Availability (the chart was the most-recent-vivid event in your context)
- Sized up after a winning streak → #12 Excessive Self-Regard + #13 Overoptimism
- Followed a tip / guru / chat-room call → #22 Authority-Misinfluence
- #15 Social-Proof
- Two or more of the above firing simultaneously → #25 Lollapalooza. This is the worst category — the loss was not one mistake, it was several reinforcing each other. Flag these separately in the eod summary because they decay slowest.
The bias category is the root cause layer of the post-mortem. The A/B/C/D grade is the symptom layer. Both belong in the journal.