If You’re Good at TradingView, Start with 1K Scanner First: Split Discovery from Deep Analysis
Why strong TradingView users should run discovery in 1K Scanner first, then hand off only high-value candidates for deep analysis.
Read entry ->Workflow
12 posts
You wobble less with a candidate pool: how a scanner reduces FOMO
Why building a candidate pool reduces FOMO, explained through Bias → Context → Trigger.
Read entry ->Why screenshots become review evidence: the pros and cons of image-based records
Screenshots preserve real-time context and make reviews more evidence-based, but they also carry framing bias and hide sequence.
Read entry ->Failure Study (20): Why practical mistakes repeat and how to correct them
Correction starts when the event fades and the structure remains.
Read entry ->How to reduce FOMO entries: prebuild your candidates before the move
A practical routine to reduce emotional entries by preparing candidates in advance and managing each one with assumption, constraint, and trigger.
Read entry ->Download/install failed? A user-first troubleshooting checklist to your first scan
A practical checklist for resolving install failures quickly, then validating 1k_scanner with a real user workflow from run to scan to notes.
Read entry ->Review template: stop saying ‘the signal was wrong,’ log assumption/constraint/trigger instead
A user-first post-review routine for replacing ‘the signal was wrong’ with Assumption/Constraint/Trigger notes, so the next session becomes faster and more consistent.
Read entry ->Screenshot + manifest: turning blurry chart captures into structured evidence
A user-first routine for turning chart screenshots into structured decision evidence in 1k_scanner using grid modes, check notes, EMA/NRZ interpretation, and template replay.
Read entry ->New to 1k_scanner? A 5-Minute Start: scan wide, narrow candidates, then focus
A real first-user flow for 1k_scanner: dense grid → consensus hotlist cues → single-chart focus → checknote. No fluff, just what to do in your first 5 minutes.
Read entry ->Why HTF checks still fail in live trading: your review must end as a decision line, not just information
If HTF reviews keep failing under LTF noise, the issue is often not analysis quality but missing decision fixation. This post explains how to convert HTF checks into executable constraints.
Read entry ->HTF is the scene, LTF is the timing: why MTF gets confusing the moment questions mix
Recurring MTF confusion usually starts not from a lack of signals, but from mixing roles. A structural look at HTF/LTF separation and the Bias→Context→Trigger order.
Read entry ->Automate your week in 7 tiny routines (and feel it immediately)
Seven small automations that remove friction without turning your life into a dashboard.
Read entry ->