# Build brief — a focused alternative to TradingWizard

> **Verdict:** Partly, if you narrow it · **Buildability:** 49/100 · **Category:** Personal Finance
> **Source:** https://www.canitbevibecoded.com/tradingwizard
> Independent editorial assessment from Can It Be Vibe Coded? Not affiliated with, endorsed by, or derived from TradingWizard. Verify current pricing and capabilities before acting.

## Context

**TradingWizard** — Market-analysis bots that explain setups and test them with fake money. It currently costs $39/mo.

A personal version is a fair focused build: watch a short list, calculate indicators, explain a setup, and journal simulated trades. Replacing the full service is different. Broad market coverage, current prices, filings and news, continuous bot jobs, stale-data guards, alerts, synced history, and a maintained proof trail are ongoing data and operations work.

This brief describes a focused, single-operator replacement for the part of TradingWizard that is genuinely reproducible. It is deliberately narrower than the product it replaces, and it says so in writing. Build the useful core; do not pretend to have rebuilt the rest.

## What you are building

Monitor a small watchlist, score transparent setups from current candles, explain the levels, and journal paper trades without connecting a broker.

- Import transactions, categorize spending, and forecast cash flow privately.
- A responsive interface with real empty, loading, success, and error states.

## Requirements

### Functional

- Node 22.
- Local SQLite database.
- Scheduled background process.

### Data and integrations

- Twelve Data API key.
- OpenAI-compatible API key.

Each of these needs a real account, credential, or quota. Set them up before writing feature code.

### Non-functional

- Accessibility: semantic markup, labelled controls, visible focus, and reduced-motion support.
- Security: server-side secrets, validated input, and no credentials in the client bundle.
- Reliability: retries with backoff on external calls, and a clear failure state when a provider is down.
- Portability: the operator can export their data and leave without losing it.

## Implementation brief

Build me a local personal market-analysis bot inspired by TradingWizard. Requirements:

- Node 22, TypeScript, Next.js App Router, better-sqlite3, technicalindicators,
  and node-cron. Bind to localhost only.
- watchlist.json holds up to 10 stock or crypto symbols plus a 15m, 1h, or 1d
  timeframe. Fetch candles from Twelve Data with the key in .env.local.
- Cache responses, respect provider limits, and show source plus last-updated time.
  Stale or missing candles must block a new setup.
- Calculate EMA 20/50, RSI 14, ATR 14, recent support and resistance, and volume
  change. Keep every setup rule in one documented rules.ts file.
- For each symbol return WAIT, LONG SETUP, or SHORT SETUP with entry zone, stop,
  target, invalidation, confidence, and the exact rule hits behind the result.
- Use an OpenAI-compatible API only to turn the calculated facts into two plain
  sentences. The model cannot change levels or invent facts. Work without it too.
- Add a paper journal. Confirm each simulated entry manually, size by a fixed risk
  percentage, and update open trades from fresh candles. Never connect a broker.
- Dashboard: watchlist state, latest setup, stale-data warning, open paper trades,
  closed results, and a per-symbol timeline. No profit promises.
- SQLite tables: candles, analyses, paper_trades, and scan_runs. Keep immutable scan
  facts so every result can be explained later.
- Add npm run scan and a configurable cron. One failed symbol must not stop the rest.
- No accounts, cloud sync, telemetry, payments, live orders, or investment advice.
  Do not scrape consumer websites.
- Include seeded fixtures and tests for stale-data blocking, rule calculations, risk
  sizing, manual confirmation, and duplicate-scan idempotency.
- README with setup, API limits, backup/restore, cron examples, and the exact limits
  of a personal build compared with a maintained multi-market service.

## Delivery standard

- Inspect the repository first, then write a short implementation plan before writing code.
- Deliver the smallest complete end-to-end workflow first; every primary control must work against persisted data.
- Use real validation and storage; never substitute fake dashboards, decorative controls, hard-coded success states, or mock integrations.
- Include responsive layouts plus genuine empty, loading, success, validation, and failure states.
- Keep secrets server-side in environment variables, provide .env.example, and never commit credentials or user data.
- Add structured logs around every external call and return actionable errors without leaking sensitive details.
- Write unit tests for the core logic and one automated test of the main user journey.
- Finish with a README covering setup, architecture, data location, backups, tests, deployment, and known limitations.

## Acceptance criteria

- [ ] A clean install starts the app using only the README and .env.example.
- [ ] The primary journey works from first visit through saved result, reload, edit, export, and deletion where applicable.
- [ ] Invalid input, missing configuration, provider failure, and an empty database each have a usable state.
- [ ] The interface works at 390px and 1440px, is keyboard navigable, and shows visible focus on every control.
- [ ] Tests, type checking, linting, and a production build all pass with no ignored failures.
- [ ] No part of the interface implies a live integration, security guarantee, or scale capability that was not actually built and verified.

## Non-goals

Do not build these, and do not claim to have replaced them:

- Maintained coverage across thousands of markets and data providers.
- Always-on bot scans, stale-data guards, and reliable alert delivery.
- Filings, news, sentiment, research, and broker-context integrations.
- Synced history, mobile access, chat controls, and account security.
- The maintained bot proof trail and production operations.

## What you still own after launch

- Secure credentials, rotate secrets, and handle provider rate limits.
- Run migrations, backups, restores, and dependency updates.
- Test the critical journey after every model, API, or hosting change.
- Monitor failures and fix the edge cases a first prompt will miss.
- Maintain every third-party integration as APIs and OAuth rules change.

## Risk

**High consequence.** Use this as a prototype or personal aid. Keep a qualified human and an established provider in the loop for consequential decisions.

Editorial confidence in this assessment: high. No reviewed project implementation is linked yet.

## Existing alternatives

Before building, compare these checked options:

- [OpenBB](https://openbb.co) — Open-source research terminal with real market-data integrations; analysis without the AI narrator or the paper-trade journal
- [Freqtrade](https://www.freqtrade.io) — Crypto-only bot with backtesting and dry-run paper trading; strategies are Python files, not chat

## Prior art

Working open-source software you can read, fork, or borrow from before starting:

- [OpenBB Platform](https://github.com/OpenBB-finance/OpenBB) — Open-source financial research platform with market-data integrations
- [Freqtrade](https://github.com/freqtrade/freqtrade) — Open-source crypto trading bot with backtesting and dry-run modes

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