Sibyl

Run a deep research cycle on any topic.

Searches the web, reads multiple sources, and synthesizes a comprehensive report with findings, analysis, and optionally predictions.

Args: query: The research question (e.g. "What's the outlook for Canadian housing market in 2026?") depth: Research depth. 1=quick (2 queries), 2=standard (4 queries), 3=deep with predictions (6 queries) language: Output language. "auto" (match query language), "en", "zh" (Chinese), or any language name

Quick web search without deep analysis. Returns raw search results.

Args: query: What to search for max_results: Maximum number of results (default 5)

Read and extract clean text content from a URL.

Args: url: The URL to read

Analyze provided text with a specific question using LLM.

Args: text: The text content to analyze question: What to analyze about the text

Generate a structured comparison table for 2-5 items.

Researches each item and produces a side-by-side markdown table with key metrics, strengths, weaknesses, and a bottom-line recommendation.

Args: items: Comma-separated items to compare (e.g. "NVDA,AMD,INTC" or "React,Vue,Angular") query: Context for the comparison (e.g. "for AI/ML workloads" or "for a startup in 2026")

Generate a SWOT analysis (Strengths, Weaknesses, Opportunities, Threats).

Researches the subject and produces a structured SWOT with specific data points.

Args: subject: What to analyze (e.g. "Tesla", "Canadian housing market", "remote work trend")

Get Google Trends data for keywords — real search interest over time.

Shows current interest level, trend direction, peak, and rising related searches.

Args: keywords: Comma-separated keywords (max 5, e.g. "ChatGPT,Claude,Gemini") timeframe: "today 1-m", "today 3-m", "today 12-m", "today 5-y" (default: 12 months)

Generate a chronological timeline of key events for a topic.

Researches the topic and extracts specific dates, events, and milestones into a structured timeline table.

Args: topic: The topic to build a timeline for (e.g. "OpenAI history", "Canada immigration policy changes 2024-2026")

Fetch real financial/stock/ETF data from Yahoo Finance.

Returns current price, trend, moving averages, 52-week range, and % change.

Args: symbols: Comma-separated ticker symbols (e.g. "AAPL,MSFT,SPY" or "XIU.TO,XRE.TO" for Canadian ETFs) period: Time period — "1mo", "3mo", "6mo", "1y", "2y", "5y" (default: 1y)

Common symbols: US: SPY (S&P 500), QQQ (Nasdaq), DIA (Dow), VTI (total market) Canada: XIU.TO (TSX 60), XRE.TO (REIT), XIC.TO (composite) Crypto: BTC-USD, ETH-USD Commodities: GC=F (gold), CL=F (oil)

Generate a price chart for one or more symbols and save as PNG.

Args: symbols: Comma-separated ticker symbols (e.g. "AAPL,MSFT") period: Time period (default: 1y) title: Chart title (auto-generated if empty)

Save the last research report as PDF and/or Markdown file.

Call this after research() to save the report.

Args: format: "pdf", "md", or "both" (default: both) output_dir: Directory to save files (default: current directory)