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stock-analyst
// Multi-agent financial analysis pipeline: fundamental analysis, technical indicators, and news sentiment scoring for any ticker symbol. Wraps patterns from virattt/ai-hedge-fund and ZhuLinsen/daily_stock_analysis.
// Multi-agent financial analysis pipeline: fundamental analysis, technical indicators, and news sentiment scoring for any ticker symbol. Wraps patterns from virattt/ai-hedge-fund and ZhuLinsen/daily_stock_analysis.
| name | stock_analyst |
| display_name | Stock Analyst Specialist |
| description | Multi-agent financial analysis pipeline: fundamental analysis, technical indicators, and news sentiment scoring for any ticker symbol. Wraps patterns from virattt/ai-hedge-fund and ZhuLinsen/daily_stock_analysis. |
| version | 0.1.0 |
| source_repo | virattt/ai-hedge-fund |
| license | MIT |
| tier | experimental |
| capabilities | ["analyze","finance","stock_analysis","technical_analysis"] |
| allowed_tools | ["analyze_ticker","technical_indicators","news_sentiment"] |
| output_formats | ["python_api","cli","mcp_server","agent_skill","rest_api"] |
Wraps virattt/ai-hedge-fund and ZhuLinsen/daily_stock_analysis.
Orchestrates a three-stage financial analysis pipeline for a requested ticker symbol: fundamental analysis, technical indicator computation, and news sentiment scoring. All three layers are merged into a single structured response with a composite stance signal.
| Tool | Description | Side Effects |
|---|---|---|
analyze_ticker | Fundamental analysis: price, P/E, market cap, sector, recommendation | None |
technical_indicators | RSI, MACD, moving averages, buy/sell signals | None |
news_sentiment | Sentiment score, article count, key themes for recent news | None |
All parameters are passed via request.intent.parameters:
| Parameter | Type | Default | Description |
|---|---|---|---|
ticker | str | (query text) | Stock ticker symbol, e.g. AAPL |
period | str | "1y" | Lookback period: 1m, 3m, 6m, 1y, 3y, 5y |
indicators | list[str] | all | Subset of rsi, macd, moving_averages |
days | int | 7 | News lookback window in calendar days |
from agents.specialists.stock_analyst.agent import StockAnalystSpecialist
from oss_agent_lab.contracts import Intent, Query, SpecialistRequest
specialist = StockAnalystSpecialist()
request = SpecialistRequest(
intent=Intent(
action="analyze",
domain="finance",
confidence=0.95,
parameters={"ticker": "AAPL", "period": "1y", "days": 14},
),
query=Query(user_input="AAPL"),
specialist_name="stock_analyst",
)
response = await specialist.execute(request)
print(response.result["summary"]["overall_stance"]) # "bullish" | "neutral" | "bearish"
oss-lab run stock_analyst "AAPL"
{
"ticker": "AAPL",
"fundamental": {
"price": 182.0,
"market_cap": 295.4,
"pe_ratio": 28.0,
"recommendation": "hold",
"sector": "Technology"
},
"technical": {
"rsi": 54.0,
"macd": {"line": 1.2, "signal": 0.8, "histogram": 0.4},
"moving_averages": {"sma_20": 183.6, "sma_50": 185.2, "sma_200": 179.1},
"signals": ["RSI neutral", "MACD bullish crossover", "Short-term trend above medium-term: bullish bias"]
},
"sentiment": {
"overall_sentiment": "positive",
"articles_analyzed": 23,
"key_themes": ["earnings beat", "product launch"],
"sentiment_score": 0.65
},
"summary": {
"overall_stance": "bullish",
"confidence": 0.715,
"key_signals": ["Fundamental: hold (P/E 28.0)", "Sentiment: positive (+0.650)"],
"risk_note": "Simulated outputs — not financial advice. Verify with live market data before acting."
}
}
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