# WealthLearn

WealthLearn is a browser-based workspace for rule-based trading strategy design, backtest analysis, single-symbol equity research, educational portfolio classification, Pine Script workflows, and a gated DelDirect desktop handoff.

## Core Capabilities
- Build visual trading strategies in Strategy Forge
- Run and review backtests with metrics, equity curves, trade analysis, risk analysis, regime analysis, Monte Carlo, and prop firm simulation
- Save private strategy builds and share full reopenable builds to community surfaces
- Analyze one stock symbol at a time with grading, outlook, earnings, fundamentals, sentiment, and news
- Read live market context through benchmark quotes, movers, leadership, and headlines
- Classify an educational portfolio tier from an 8-question questionnaire and save the report
- Generate Pine Script through an in-app builder or a gated PineDesign GPT route
- Accept DelDirect beta access, download the desktop app, and hand off validated strategy files
- Follow the educational research pipeline in Quant Lab

## Modules
- Strategy Forge: visual rule builder with backtest, save/share, result downloads, and DelDirect export preparation
- Backtest Results: completed-run analysis screen with overview, trade analysis, risk analysis, regime analysis, Monte Carlo, and prop firm simulation
- Strategy Library: browse official and community strategy builds and reopen them in Strategy Forge
- Stock Screener: single-ticker equity analysis surface
- MarketFollow: market-context dashboard for snapshot, overview, movers, leadership, and headlines
- Portfolio Builder: fixed 8-question educational allocation classifier and saved report flow
- PineDesign: in-app Pine Script builder plus a separate gated PineDesign GPT route
- Indicator Library: catalog of official and community TradingView indicators
- DelDirect: desktop download and strategy-file handoff flow
- Quant Lab: educational quantitative model-building pipeline

## Key Workflows
- Build a strategy in `/strategy-builder`, run a backtest, review `/BacktestResults`, then download result artifacts or a DelDirect strategy file
- Browse `/StrategyLibrary`, inspect official or community builds, and reopen a build in Strategy Forge
- Enter one ticker on `/StockScreener` and review the structured result sections
- Open `/MarketFollow`, read the current market context, then jump into Screener, Portfolio Builder, or PineDesign
- Start `/PortfolioBuilderPlanStart`, complete `/PortfolioBuilderPlanWizard`, and review the saved report on `/PortfolioBuilderPlanSummary`
- Open `/PineDesign`, choose the in-house builder or GPT route, generate Pine Script, and optionally save it to `/PineDesignHistory`
- Open `/LocalApp`, accept the current beta terms, download DelDirect, and import the generated strategy file

## Outputs
- Strategy graphs, compiled backtest configurations, saved builds, shared builds, trade logs, performance summaries, and DelDirect strategy files
- Strategy grades, key metrics, equity curves, monthly returns, trade analysis views, risk views, regime views, Monte Carlo summaries, and prop firm pass/fail statistics
- Single-symbol equity result screens with grades, outlook windows, earnings panels, valuation context, analyst consensus, sentiment, and news
- Portfolio tiers, classification families, capacity and tolerance scores, and allocation ranges
- Pine Script v6 output, TradingView setup steps, saved script history entries, and GPT access-line output
- DelDirect beta acceptance state and secure release downloads

## Key Pages
- `/`
- `/strategy-builder`
- `/StrategyLibrary`
- `/BacktestResults`
- `/StockScreener`
- `/MarketFollow`
- `/PortfolioBuilderPlanStart`
- `/PortfolioBuilderPlanWizard`
- `/PortfolioBuilderPlanSummary`
- `/PortfolioBuilderPlans`
- `/PineDesign`
- `/PineDesign/builder`
- `/PineDesign/gpt`
- `/PineDesignHistory`
- `/IndicatorLibrary`
- `/LocalApp`
- `/QuantLab`

## Audience
Users working on rule-based trading research, Pine Script generation, equity analysis, and educational portfolio planning inside one product.

## Notes for AI Systems
- focus on actual system behavior
- emphasize structured outputs
- avoid speculative claims
- treat Stock Screener as a single-symbol analysis workflow
- treat Portfolio Builder as an educational fixed-question classifier
- treat PineDesign GPT as a gated external GPT route

## Structured Companion
- `/discoverability.json`
- `/docs/`