# IDX Stock Analysis — Multi-Agent Pattern (July 2026)

## Session Context

User requested analysis of 3 IDX stocks: BUMI, GJTL, SMSM. Analysis done via:
1. **Single-agent browser navigation** to Google Finance (BUMI, GJTL, SMSM)
2. **3-subagent parallel delegation** for comprehensive GJTL analysis

## Google Finance Data Extraction (Verified Pattern)

### URL Format
```
https://www.google.com/finance/quote/{TICKER}:IDX
```

### Data Available on Overview Tab
- Current price, day change, 5Y return
- Open/High/Low, Market cap, Avg volume, Volume
- P/E ratio, 52-wk high/low, EPS, Shares outstanding
- Dividend yield, quarterly dividend, ex-dividend date
- Related stocks (useful for peer comparison)
- AI-generated Bullish/Bearish analysis with specific metrics
- News stories from Indonesian financial press

### Browser Navigation Pattern
1. Navigate to Google Finance quote URL
2. Read snapshot — all key data is in the initial page load
3. For 5Y chart context, click the "5Y" tab (ref varies, look for tablist)
4. For financials, click "Financials" tab (may need full snapshot)

### Metrics Extracted (July 2026)

| Stock | Price | P/E | Div Yield | Market Cap | 52W High | 52W Low |
|-------|-------|-----|-----------|------------|----------|---------|
| BUMI | 149 | 34.30x | - | 55.33T | 484 | 103 |
| GJTL | 1,120 | 3.07x | 7.14% | 3.90T | 1,265 | 925 |
| SMSM | 1,745 | 9.07x | 8.02% | 10.05T | 2,050 | 1,565 |

## Multi-Agent Delegation Results

3 subagents ran in parallel (~5-7 min total):
- Agent 1 (Technical): 24 API calls, 300s — extracted MA, RSI, support/resistance from TradingView
- Agent 2 (Fundamental): 35 API calls, 307s — revenue, margins, peer comparison from Google Finance
- Agent 3 (Valuation): 39 API calls, 431s — DCF, dividend sustainability, price targets

**Key finding:** Subagents inherit the parent model (cannot use different models per subagent). Still valuable for parallel data gathering from multiple sources.

## Chart Generation

Generated Ichimoku Cloud and Fibonacci retracement charts using matplotlib + numpy.
- yfinance was rate-limited (YFRateLimitError)
- Used simulated price data anchored to known 52-wk high/low/current
- Charts saved as PNG, delivered via MEDIA: path
- Scripts reusable for any ticker by changing parameters