Playbooks
Save the setup, invalidation, risk, and market rules every review should use.
A guided process journal for discretionary traders
Free beta · No payment step
Go from your first chart to a better-tested strategy.
Start with one TradingView chart, verify the editable evidence, and save your first useful record. Add a playbook and evidence test when you are ready to turn repeated trades into a testable strategy.
Evidence, not predictionsPrivate account workspaceBrowser OAuth
New trade reviewSanitised demo data
01Guided from the first step
02Editable before save
03Scoped before analysis
04Evidence before conclusions
The complete journal
Every part of the review cycle has a job.
No single total can explain a trader testing several instruments and strategies. The journal preserves the hierarchy from playbook to session to individual trade, then carries that scope into dashboards and reports.
Evidence tests
Keep each hypothesis, instrument, timeframe, and test period in its own historical evidence cohort. No replay or order simulation.
Trade capture
Turn a TradingView link or chart image into an editable evidence preview before save.
Outcome review
Add follow-up evidence, close the trade, and compare the original plan with what happened.
Scoped dashboards
Filter metrics by playbook, evidence test, instrument, and timeframe without blending unrelated trades.
Evidence reports
Review timing, process, and outcome themes with visible sample-size cautions.
Your path from setup to insight
Start here. Follow the same loop every time.
You do not need to know the whole product on day one. Complete each stage in order; the output of one becomes the input to the next.
Start at step one- 1
Create your account
Your private workspace keeps playbooks, chart evidence, outcomes, and reports together.
Output: Workspace ready - 2
Capture your first chart
Paste a TradingView link or choose an image, then verify the editable preview before saving.
Output: First useful record - 3
Add the outcome
Return with the completed chart and confirm the result, timing, and realised R.
Output: Plan compared with result - 4
Add a playbook
When the basic workflow is clear, save the observable strategy rules future reviews should check.
Output: Rules to check - 5
Start an evidence test
Use a bounded session when you have one hypothesis, instrument, and timeframe to test against saved historical evidence.
Output: Test scope fixed - 6
Generate the report
Read strengths, process drags, drawdown, timing patterns, sample limits, and the next experiment.
Output: Decision-ready review - 7
Change one variable and repeat
Keep what is supported, test one improvement, and compare the next sample with the same scope.
Output: A tighter strategy
Clean cohort analysis
See the dashboard for the strategy you are actually reviewing.
Start with the whole journal, then narrow to one playbook, one evidence test, one instrument, or one timeframe. The active scope stays visible beside the sample size so mixed evidence is never mistaken for one system.
- Cumulative performance and process metrics use the same cohort.
- The review queue shows evidence and strategy-fit status.
- Scope coaching turns supported themes into the next test.
Scoped dashboardPlaybook + evidence test
AI with boundaries
A second set of eyes on your process—not a market oracle.
What the review uses
- Your saved playbook rules and required evidence
- The original chart, extracted fields, provenance, and confidence
- Follow-up evidence, timestamps, and the recorded outcome
- The selected report cohort and its sample size
What it is designed to return
- Setup-fit checks and missing evidence
- Plan-versus-outcome feedback
- Repeated process strengths and drags
- Ideas for a bounded next evidence test
What it will not do
- Predict profit or guarantee an outcome
- Issue buy or sell instructions
- Invent unreadable chart facts
- Hide degraded mode when AI is offline
Evidence reportTiming + process
Reports that stay honest
Find when a strategy behaves differently—and whether the sample supports it.
Trade and follow-up timestamps let reports compare weekdays, recorded local time blocks, market sessions, outcome timing, and holding periods. Themes stay tied to the chosen playbook or evidence test.
Timing evidenceEntry, outcome, session, holding periodNext experimentOne testable process change
Browser connection
Your journal account and ChatGPT connection remain separate.
Sign in to the journal normally, then authorize your own ChatGPT account on the official website with a one-time device code. There is nothing to install, and the journal remains usable in deterministic degraded mode when AI is unavailable.
Before you start
Common questions.
The detailed setup guide, field explanations, best practices, and troubleshooting live inside every signed-in workspace.
Does the journal place trades or tell me what to buy?
No. It reviews evidence against the rules you saved. It does not execute orders, predict profit, or issue buy and sell instructions.
Can I use it without the AI connection?
Yes. Manual editing, deterministic extraction, risk/reward, and saved-rule checks remain available. The interface states clearly when AI review is unavailable.
Why separate playbooks and evidence-test sessions?
A playbook is the reusable strategy. An evidence-test session is one bounded historical cohort using that strategy. It does not replay market data or simulate orders. Keeping both prevents unrelated tests from being blended in dashboards and reports.
Can I connect ChatGPT from a phone?
Yes. The responsive website starts a device-code OAuth flow that completes on the official ChatGPT website in your browser; no installed app folder or terminal is required.
What data should I record for useful reports?
Verify the core levels, choose the correct playbook or session, record the chart timezone and trade time, then add follow-up evidence and its timestamp. Consistent evidence creates meaningful cohorts.
Build the evidence
Make every review part of the next decision.
Start with one verified chart. Add rules and a bounded test when you are ready.