pftui
Track positions, markets, macro, sentiment, news, and analytics in one system, with a browser dashboard and a structured CLI your AI agent can work with directly.
curl -fsSL https://raw.githubusercontent.com/skylarsimoncelli/pftui/master/install.sh | bash
Re-run to upgrade. Your data is preserved.
A local-first system for investors and technical operators who want their portfolio, market context, and research state in one place.
Portfolio tracking, watchlists, markets, macro, news, and research state in one place instead of across scattered apps and spreadsheets.
Fast, keyboard-driven, practical enough to live in every day, with both a terminal UI and a web dashboard backed by the same local data.
Every major feature is accessible through the CLI with structured JSON output, so humans and agents can work from the same live state.
A quick look at pftui across the terminal UI, web dashboard, analytics views, and CLI.
Use the install script for the fastest path. Re-running it upgrades pftui while preserving your local data and config.
Fastest path for Linux and macOS.
curl -fsSL https://raw.githubusercontent.com/skylarsimoncelli/pftui/master/install.sh | bash
Ask Claude Code, Codex, or OpenClaw to install pftui and set it up with you. Your agent can read AGENTS.md, configure your watchlist, and walk you through the system.
pftui’s core experience is a fast, keyboard-driven interface built for daily portfolio and market monitoring.
Track positions, transactions, markets, macro, watchlists, news, and journal state in one place, with braille charts, fast navigation, and privacy mode built in.
Use the same local data through a browser with responsive layouts, TradingView charts, click-through asset views, and auto-refreshing pages.
Designed to replace scattered tabs and spreadsheets with one practical system you can actually live in every day.
Every major feature is available through the CLI with structured output, so agents can refresh data, inspect state, update research, and contribute to the same system the human operator uses.
Your agent can refresh market data, inspect portfolio state, manage watchlists, record notes, review macro conditions, and generate briefs through the same local database and CLI.
Run morning briefs, market-close summaries, weekly reviews, scenario tracking, and monitoring loops without building a separate stack around the product.
Agents do not just read data. They can update scenario probabilities, log evidence, set conviction scores, and write notes that remain reviewable and queryable over time.
$ pftui refresh 12 sources updated, 84 symbols, regime classified $ pftui brief --json {"value": 287345, "regime": "risk-off", "movers": [...]} $ pftui conviction set GC=F --score 4 --notes "War + BRICS" Gold conviction: +4 (strong bullish) $ pftui agent-msg send "All 4 layers agree: gold bullish" Message logged to cross-layer feed
Every major feature is available as a composable CLI primitive, with structured output available across the system.
pftui is built as a four-layer intelligence stack. The aggregation engine collects and computes. The database stores and shares. The analytics engine interprets across timeframes. The AI layer acts on the interpretation.
One pftui refresh pulls from 19 data sources, caches everything locally, and runs pre-processing on top of the raw data. By the time anything else reads from the database, the heavy numerical work is already done.
Equity, crypto, commodity, and forex prices across 84 symbols. CFTC Commitments of Traders positioning. COMEX warehouse inventory. BLS economic data across 101 series. World Bank indicators for 8 economies. Polymarket odds. Fear and Greed indices. Economic calendar. Financial news from RSS feeds and Brave Search. BTC on-chain data and ETF flows.
RSI, MACD, SMA, and Bollinger Bands across all symbols. Rolling cross-asset correlation matrices. Market regime classification with confidence scoring. Daily change detection and threshold alerts. FX normalization for multi-currency portfolios. Prediction market probability shifts.
The Analytics Engine does not re-derive technicals from raw price data. It reads pre-computed indicators from the database and asks the higher-order question: what does RSI 89 on oil mean given the current war scenario? The aggregation layer handles compute. The analytics layer handles interpretation.
$ pftui refresh ✓ FX rates (7 currencies) ✓ Prices (84 symbols, RSI/MACD/SMA computed) ✓ Correlations (33 cross-asset pairs) ✓ Regime (risk-off, confidence 0.85) ✓ Predictions (4 markets from Polymarket) ✓ News (116 articles via Brave + RSS) ✓ COT (4 reports from CFTC) ✓ Sentiment (2 indices) ✓ Calendar (3 upcoming events) ✓ Economy (101 BLS series) ✓ World Bank (160 global indicators) ✓ On-chain (ETF flows, BTC metrics)
The shared state layer for everything. The aggregation engine writes price caches and economic data. The analytics engine writes scenarios and convictions. The AI layer writes agent messages and predictions. Every layer's output becomes queryable input for every other layer.
Transactions, price history, COT positioning, COMEX inventory, BLS economic data, World Bank indicators, sentiment indices, prediction markets, scenarios, convictions, trend tracking, agent messages. All normalised, all queryable.
SQLite by default, PostgreSQL for production. No cloud sync. No third-party accounts. Back it up, version it, query it directly. Your data stays yours.
An agent reads regime classification, combines it with scenario probabilities, and writes a conviction score consumed elsewhere in the system. The database is where all layers meet.
Day one is a snapshot. Day thirty is a month of cross-asset history. Day three hundred is a proprietary dataset most retail investors never build. The longer you run it, the more powerful it becomes.
Four intelligence layers operating simultaneously across different time horizons. Each uses different data, updates at different frequencies, and produces different signals. When all layers align on an asset, that is the highest conviction signal in the system.
Prices, volatility, sentiment, regime classification, correlations, calendar events, and triggered alerts. Updated every refresh cycle. Tactical signals: what is happening right now.
Macro scenarios with probabilities, versioned thesis, conviction scores per asset, research questions, economic data, and user predictions with accuracy scoring. Updated daily. Directional signals: which narratives are winning.
Structural trends like AI disruption, nuclear renaissance, and commodity supercycles. Each trend has a direction, evidence log, and per-asset impact mapping. Updated weekly. Thematic signals: what forces are reshaping markets.
Empire lifecycle analysis with power metrics across 8 dimensions, structural cycles with stage tracking, long-term outcome probabilities, and historical parallels. Updated weekly. Structural signals: where are we in the big cycle.
$ pftui analytics summary LOW risk-off regime | VIX 29.5 | 3 alerts triggered | 7 movers MEDIUM war scenario 45% | gold conviction +4 | Fed 75bp pricing HIGH commodity supercycle accelerating | AI displacement evidence MACRO US Stage 5 to 6 transition | 1973 parallel similarity 8/10 ALIGNMENT: gold bullish across all four timeframes
| pftui | Yahoo Finance | Bloomberg Terminal | Spreadsheets | |
|---|---|---|---|---|
| Live Prices | ✓ | ✓ | ✓ | Manual |
| Charts | Braille + TradingView | Basic | Professional | No |
| Technical Analysis | ✓ | Limited | ✓ | Manual |
| Macro Dashboard | ✓ | No | ✓ | No |
| Runs in Terminal | ✓ | No | No | No |
| Privacy | Local SQLite or your Postgres | Cloud | Enterprise | Local |
| Persistent Local DB | 18 tables, compounds daily | No | Proprietary | Manual |
| Agent-ready CLI | 30+ commands, structured output | No | Bloomberg API ($) | No |
| Data Centralisation | 10+ sources, one refresh | 1 source | ✓ | Manual |
| Multi-Timeframe Analytics | LOW / MEDIUM / HIGH / MACRO engine | No | Partial | No |
| AI Agent Integration | ✓ | ✗ | ✗ | ✗ |
| AI Layer Workflows | Briefs, scenarios, conviction loops | No | Custom build | Manual |
| Cost | Free | Free | $24k/year | Free |
Monthly macro intelligence produced by pftui's multi-timeframe analytics engine. Four specialist agents analyze markets across different time horizons, and an Opus-level synthesis layer produces scenario-weighted outlooks with falsifiable predictions.
March 2026 newsletter covering BTC cycle analysis, gold structural thesis, equity valuations, recession probability, AI economic impact, and the Iran conflict. Includes cross-asset correlation mapping and portfolio allocation frameworks for three investor profiles.
Each report ingests the full pftui database state: scenario probabilities, conviction scores, prediction accuracy, structural cycles, power metrics, and agent messages across all four timeframe layers. Live web research verifies every data point. The result is an evidence-weighted outlook where every probability is backed by specific data, every prediction is falsifiable, and every claim is sourced.
Each issue covers the major macro themes driving markets. Scenario analysis with probabilities that sum to 100%. Historical parallels with specific dates and outcomes. Cross-asset correlation maps showing how themes interact. Portfolio allocation frameworks for conservative, balanced, and conviction-driven investors. All data sourced from pftui's PostgreSQL-backed aggregation engine.
MIT licensed. Written in Rust. 1100+ tests. Agent operator guide included. Actively developed.