Broker review
Alpaca trade journal for traders who want cleaner review
A focused review page for Alpaca traders who want to turn raw fills into repeatable lessons.
Who this page is for
Alpaca traders who want a low-friction way to review equities or crypto execution.
Core problem
A Alpaca workflow can collect the fills, but it still needs a review layer that shows the process quality behind the P&L.
Why this matters
Why this page exists
The page should answer the exact query before asking the user to convert.
A journal is only useful when it separates clean decisions from lucky outcomes.
If the last loss or the last trade is the only thing you remember, the review loop is too weak.
The goal is to see the pattern before the next session starts.
What to do first
Start with the smallest useful workflow
A specific first step keeps the page practical and reduces decision fatigue.
Start with the last 20 closed trades from Alpaca.
Group them by setup, time of day, and exit quality.
Mark the decision that most often turns a valid idea into a weak trade.
What to measure
Look for signals that change behavior
Useful review starts with a small number of repeatable measurements.
P&L by setup, trade pacing, and follow-up behavior after a red trade
Trade count after the first loss or warning
Average result of late-session trades versus early-session trades
How it helps
Where SEIGYO fits
Move from the query into a workflow users can try with demo data, CSV history, or a setup path.
Try the demo to see the journal layout before you connect anything.
Import CSV history if you want to validate the workflow on your own trades first.
Keep the same labels every session so the repeated mistake stays visible.