concept

Overview

Use this page to pick the right kind of script before you open the Code tab.

Chartnaut has three scripting models — indicators (paint on the chart), definitions (mark setups in history for Collect), and studies (measure what usually happens after those setups) — plus an optional pin layer that shows study numbers on the Terminal while you trade.

Decision table

Goal	DSL	Key APIs	Agent
Lines, histograms, overlays on the chart	Indicator	`meta`, `output.*`, `onBar`, `ctx.plot`	Indicator authoring
Mark setups in history for Collect	Definition `kind: "flow"`	`events.declare`, `ctx.emit`	Definition authoring
Measure outcomes after events	Study	`flows.declare`, `onEvent`, `results.declare`, `ctx.publish`	Study authoring
Show study stats on the Terminal chart	Study + Put on chart	Product UI / Forward insight agent	Forward insight agent (not the study agent)

How they connect

Indicator (paint)
    ↓ may be a dependency of
Definition (emit events)
    ↓ Collect gathers events →
Study (measure + publish)
    ↓ Put on chart →
pin_cell / popover_layout (cast on Terminal)

Studies do not call ctx.emit. They read events from definitions you declare with flows.declare.

Product path vs Code tab

Job	Product UI	Code tab
Build an indicator	Research → Indicators	Indicator API
Build a definition	Research → Definitions	Definition API
Build a study	Definition → Studies	Study API
Put stats on chart	Put on chart / Pin Studio	Show studies on charts

If you are new to the product model, start with Research overview, then come back here for signatures and examples.

Where to look next

Most APIs (drawings, inputs, indicators.declare, MTF, session, budgets) are documented once under Shared runtime. Use the Indicator, Definition, and Study sections for what each type adds on top (series outputs, emit/events, collect/publish).

Shared runtime
Script anatomy — declare phase vs runtime hooks
First indicator guide — minimal runnable script
Agents overview — who writes which tier

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