Key Features
A quick tour of what you get. Each of these has its own guide later on — this page is just the overview. The app is under active development; items marked in development describe where things are headed.
A journal-first review habit
Most tools put a table of numbers first. Trading Journal AI puts the story of your day first: a short recap, the trades beside it for reference, and the week and month as containers you can scroll back through. The goal is to make reviewing fast enough that you actually do it every day.
Tagging in your own language
After a trade, write a sentence and tap the pills that fit — one quality call, plus the process and emotion behind it. Because you reuse the same vocabulary every session, patterns become searchable instead of buried in prose. "Show me every trade I tagged FOMO" becomes a real question you can answer.
Charts, calendar & reports
Every trade opens on a candlestick chart with entry and exit markers — the ticker's full session, so whether you took one trade or ten, you see each one in the context of the others and leave your note right there instead of clicking into a separate page per trade. In the journal, the day's recap leads with a running P&L chart and ticker list beside it, so the numbers that shaped the session stay close without taking over. Calendar and analytics are their own views for when you want the month at a glance or the wider stats.
Your playbook (in development)
Define your setups, patterns, process rules, and review criteria once, and the journal, analytics, and coach can all use them as context. The playbook is the connective tissue of the whole system — it turns scattered reviews into a personal reference for what you trade, how you trade it, and what invalidates it. See the Roadmap.
An AI coach that follows your rules (in development)
The plan: you codify what an A+ trade looks like — the entry, risk, and process criteria you already track (your playbook) — and the coach reads each trade against that standard, flags where you drifted, and drafts feedback in your voice. An early version works today with your own OpenAI API key: reviews run only when you ask, go to the provider you configured under your key, and every draft is yours to edit before it saves. See The AI Coach.
The learning loop (in development)
The direction is a loop that keeps lessons from disappearing into archived notes — dashboard prompts, journal captures, coach synthesizes, dashboard reminds:
- Dashboard opens the loop as the active-day surface: the morning plan, visible rules and risk posture, and in-session check-ins that feed the day's recap.
- Journal captures the day — the durable record everything else builds on (available today).
- Coach turns that record into a focused lesson and a next experiment.
- Dashboard closes the loop by carrying the lesson into your next session as a visible cue.
Local-first by design
Everything is stored in a local SQLite file in your project folder. Your broker exports and notes are gitignored. It runs on your machine, so your review habit stays private unless you deliberately deploy or share it.
Import from your broker
Bring trades in from a broker CSV export rather than retyping them. Fills are grouped into trades automatically, so you review the day's story with each ticker's trades in reach — not a wall of raw fills. See Importing your trades.