Alfa Tool Examples

Description: Search the web for information on any topic.

When to use it: When you need general information from the web that isn’t necessarily stock-specific.

Example use case: “Find information about recent inflation trends.”

Key parameters:

• queries: List of search terms you want to look up
• urls: Optional specific web addresses to include in your search
• date_range: Optional timeframe to limit your search results

Tips:

• Use specific, targeted queries for better results
• Results will be automatically summarized for readability
• Can be used with or without specific URLs

Description: Extract text content from specific web pages.

When to use it: When you want to analyze information from particular web pages you already know about.

Example use case: “Read the content of Apple’s latest press release at [specific URL].”

Key parameters:

• urls: Full web addresses of the pages you want to extract
• queries: Optional additional search terms to find related content on the same site

Tips:

• Always include the complete URL including domain and routing
• Use this when you want content from specific pages you already know
• Results will be automatically processed and summarized

Description: Retrieve news events and developments about specific companies.

When to use it: When you want to understand significant news events affecting particular stocks.

Example use case: “What major news has affected Microsoft in the past month?”

Key parameters:

• stock_ids: The companies you want news about
• date_range: Timeframe for the news (defaults to the last week)

Tips:

• Provides organized news events rather than just articles
• Use for a high-level view of important company developments
• Cannot be used for future dates - only past and present news

Description: Retrieve financial and statistical data for companies.

When to use it: When you need specific metrics or financial data for stocks.

Example use case: “What’s the P/E ratio for Tesla compared to other automakers?”

Key parameters:

• statistic_reference: The metric to retrieve (e.g., “P/E Ratio”, “Revenue”)
• stock_ids: Stocks to analyze
• date_range: Optional timeframe for analysis
• is_time_series: Whether to return a series of values over time
• target_currency: Optional currency conversion

Tips:

• Can handle simple and complex financial metrics
• Supports time series for trend analysis
• Can calculate derived statistics (ratios, growth rates, etc.)
• Very flexible with natural language descriptions of statistics

Description: Retrieve economic and market-wide statistical data.

When to use it: When you need data on broad economic indicators.

Example use case: “Show me how interest rates have changed over the past year.”

Key parameters:

• statistic_reference: The metric to retrieve (e.g., “Interest Rates”, “Inflation”)
• date_range: Optional timeframe for analysis

Tips:

• Works with macroeconomic indicators not tied to specific stocks
• Can show time series for trend analysis
• Useful for economic context in investment decisions
• Examples include interest rates, inflation, unemployment, GDP

Description: Get current market prices for stocks.

When to use it: When you need the most up-to-date price information.

Example use case: “What’s the current price of Amazon stock?”

Key parameters:

• stock_ids: Stocks to get prices for

Tips:

• Returns the most recent available price
• Shows intraday/real-time prices during market hours
• Only shows current prices - use statistics tool for historical prices
• Cannot be used for calculations - use statistics tool for that

Description: Retrieve full transcripts of company earnings calls.

When to use it: When you need complete, verbatim records of earnings calls.

Example use case: “Get me the full transcript of Tesla’s latest earnings call.”

Key parameters:

• stock_ids: Companies to get earnings call transcripts for
• date_range: Timeframe for the earnings calls

Tips:

• Returns complete, unabridged transcripts
• Use only when complete transcripts are explicitly requested
• Great for searching specific phrases or detailed analysis
• Cannot find documents from the future
• Defaults to last quarter if no date range specified

Description: Retrieve condensed summaries of company earnings calls.

When to use it: When you need the key points from earnings calls without all the details.

Example use case: “Summarize Apple’s last earnings call.”

Key parameters:

• stock_ids: Companies to get earnings call summaries for
• date_range: Timeframe for the earnings calls

Tips:

• Returns concise summaries instead of full transcripts
• Default tool for earnings call information
• More efficient than full transcripts for general understanding
• Cannot find documents from the future
• Defaults to last quarter if no date range specified

Description: Access professional research reports about companies.

When to use it: When you need in-depth professional analysis from financial analysts.

Example use case: “Find research reports about Nvidia’s AI strategy.”

Key parameters:

• stock_ids: Companies to get research for
• date_range: Timeframe for the research

Tips:

• Provides access to professional broker (sell-side) research
• Contains detailed analysis beyond news or company statements
• Cannot find documents from the future
• Only use when specifically asked for research documents

Description: Retrieve official regulatory filings like SEC documents.

When to use it: When you need specific types of regulatory filings.

Example use case: “Find all 8-K filings for Tesla from last year.”

Key parameters:

• stock_ids: Companies to get filings for
• form_types: Types of filings to retrieve
• date_range: Timeframe for the filings
• use_full_text: Whether to get complete documents

Tips:

• Must be used after Filings Type Lookup tool
• Retrieves specific filing types (10-K, 10-Q, 8-K, etc.)
• Set use_full_text=True for complete filing text
• Cannot find documents from the future
• Results should be summarized, not shown directly

Description: Calculate the year-over-year percentage change for a specific statistic.

When to use it: When you need to see how a metric has changed compared to the same period last year.

Example use case: “What’s the year-over-year revenue growth for Apple?”

Key parameters:

• statistic_reference: The metric to analyze (e.g., “Revenue”)
• stock_ids: Stocks to analyze
• date_range: Optional timeframe for analysis
• is_time_series: Whether to return a series of values over time
• target_currency: Optional currency conversion

Tips:

• Shows percentage change from previous year’s value
• Also known as YoY or year-on-year change
• Use for trend analysis and growth evaluation

Description: Analyze future revenue growth expectations for stocks.

When to use it: When you want to understand analysts’ expectations for future growth.

Example use case: “Which technology companies have the highest expected revenue growth?”

Key parameters:

• stocks: Stocks to analyze
• num_quarters: How many future quarters to look ahead
• mode: Whether to check “earnings” or “revenue” expectations

Tips:

• Shows expected percentage growth based on analyst forecasts
• Can analyze either revenue or earnings expectations
• Compares actual past figures with future estimates
• Useful for forward-looking investment decisions

Description: Generate insights, themes, or patterns from text data.

When to use it: When you want to identify patterns or trends in information.

Example use case: “What are the key themes in recent quarterly reports for tech companies?”

Key parameters:

• idea_definition: Description of the type of insights you’re looking for
• texts: Information to analyze
• max_ideas: Maximum number of ideas to generate
• format_instructions: Optional guidance on output format

Tips:

• Can identify patterns, themes, trends, events, policies, etc.
• Provides descriptions and supporting evidence for each idea
• Useful for thematic analysis and trend identification
• Great for brainstorming investment themes or macroeconomic patterns

Description: Extract specific answers from text information.

When to use it: When you have a specific question that can be answered from text data.

Example use case: “What countries does Coca-Cola operate in according to their latest annual report?”

Key parameters:

• question: The specific question to answer
• texts: Information to search for the answer

Tips:

• Focuses on finding precise answers rather than summarizing
• Good for factual questions with definitive answers
• More targeted than general summarization
• Uses relevance filtering to find pertinent information

Description: Perform custom operations on tables of data.

When to use it: When you need to sort, filter, rank, or aggregate table data.

Example use case: “Rank these stocks by market cap and show only those above $10 billion.”

Key parameters:

• input_table: The table to transform
• transformation_description: Detailed description of the transformation to perform

Tips:

• Can perform sorting, filtering, ranking, and aggregation
• Uses natural language descriptions for transformations
• Great for complex data manipulations
• Not for time-based calculations (use statistical tools instead)

Description: Filter stocks based on whether they beat or missed earnings expectations.

When to use it: When you want to find stocks that exceeded or fell short of analyst estimates.

Example use case: “Show me S&P 500 companies that beat earnings expectations last quarter.”

Key parameters:

• stocks: List of stocks to filter
• miss: Whether to find misses (True) or beats (False)
• quarters: Number of quarters or specific quarters to check
• mode: Whether to check “earnings” or “revenue” expectations
• filter: Whether to filter the list or just provide beat/miss information

Tips:

• Can check either earnings or revenue expectations
• Can look at specific quarters or a number of recent quarters
• Provides actual figures, expected figures, and surprise percentages
• Set filter=False for analysis of specific stocks without filtering

Description: Filter and rank stocks based on their relevance to a theme or profile.

When to use it: When you want to find stocks related to a specific concept or theme.

Example use case: “Find companies that are leaders in sustainable manufacturing.”

Key parameters:

• stocks: Stocks to filter
• stock_texts: Information about the stocks
• profile: Description of what you’re looking for
• complete_ranking: Whether to fully rank the stocks
• score_threshold: Minimum score for inclusion
• top_n: Optional limit to just the top N results
• bottom_m: Optional inclusion of the bottom M results
• no_filter: Whether to include all stocks with any relevance

Tips:

• Provides detailed scoring and explanations for matches
• Can be used with simple string profiles or complex profiles from Generate Profiles
• Set complete_ranking=True for “best” or “worst” matching
• Set score_threshold to control quality cutoff (0-5 scale)
• Results include reasoning for each stock’s inclusion

Description: Create separate summaries for each idea in a list.

When to use it: When you need individual text summaries for multiple ideas or themes.

Example use case: “For each macroeconomic trend identified, summarize how it affects tech stocks.”

Key parameters:

• ideas: List of ideas to create summaries for
• texts: Information related to the ideas
• topic_template: Template for what to summarize about each idea
• column_header: Header for the summary column

Tips:

• Creates focused summaries for each idea from a brainstorming session
• Must use “IDEA” as a placeholder in the topic template
• Builds on the output of the Idea Brainstorm tool
• Results appear as a column in the ideas table

Description: Collect and prepare information needed for writing market commentary.

When to use it: When you want to gather data for a comprehensive market analysis.

Example use case: “Prepare to write a commentary on recent tech sector performance.”

Key parameters:

• stock_ids: Specific companies to include
• topics: Subjects to focus on
• universe_name: Market index or ETF to analyze
• date_range: Timeframe to analyze
• portfolio_id: Optional portfolio to analyze
• macroeconomic: Whether to include macroeconomic trends
• theme_num: Number of top themes to identify
• top_n_stocks: Number of top contributors to highlight

Tips:

• Essential preparation step before Write Commentary
• Gathers relevant data for comprehensive analysis
• Can focus on specific companies, sectors, markets, or portfolios
• Can include macroeconomic context when relevant

Description: Extract structured table data from text information.

When to use it: When you need to convert unstructured text into organized table format.

Example use case: “Extract a table of product launches and dates from these press releases.”

Key parameters:

• texts: Information to convert to a table
• table_description: Description of the table to create
• table_schema: Column definitions for the table
• from_description_only: Whether to create the table purely from description

Tips:

• Converts unstructured information into structured tables
• Requires defining columns and their data types
• Great for extracting comparable data points from text
• Must not be used on already summarized text - use original sources

Description: Create a line chart from tabular data.

When to use it: When you want to visualize trends over time or continuous relationships.

Example use case: “Show me a graph of Apple’s stock price over the past year.”

Key parameters:

• input_table: Table data to visualize

Tips:

• Best for time series data or continuous relationships
• Good for price trends, performance metrics over time, etc.
• Requires at least 7-14 data points for a meaningful visualization
• Input must be a properly structured table

Description: Create a pie chart from tabular data.

When to use it: When you want to show proportions of a whole.

Example use case: “Show the sector breakdown of my portfolio as a pie chart.”

Key parameters:

• input_table: Table data to visualize

Tips:

• Best for showing parts of a whole
• Good for portfolio allocations, market share, etc.
• Works best with a single dimension of categorical data
• Not suitable for time series or multiple periods

Description: Create a bar chart from tabular data.

When to use it: When you want to compare discrete categories.

Example use case: “Create a bar chart showing revenue by product category.”

Key parameters:

• input_table: Table data to visualize

Tips:

• Best for comparing discrete categories
• Good for performance across categories, rankings, etc.
• Works well with multi-dimensional data in discrete buckets
• Not ideal for continuous time series data

Description: Get buy/sell recommendations and analysis for stocks.

When to use it: When you want investment recommendations with supporting rationales.

Example use case: “Which tech stocks look most promising right now?”

Key parameters:

• stock_ids: Stocks to analyze
• filter: Whether to filter the list to recommended stocks
• buy: For buy (True) or sell (False) recommendations, or None for neutral analysis
• horizon, delta_horizon, news_horizon: Time frames for analysis
• news_only: Whether to focus solely on news sentiment
• num_stocks_to_return: Optional limit on results
• star_rating_threshold: Minimum rating for inclusion
• investment_style: Optional investment approach to consider
• date: Optional date for historical analysis
• bullets: Whether to format reasoning as bullet points

Tips:

• Provides scores, ratings, and detailed rationales
• Can filter to just buy or sell recommendations
• Can focus on news sentiment or include quantitative metrics
• Set filter=False for analysis without filtering
• Star ratings are on a 5-point scale

Description: Evaluate and compare companies competing in a specific market.

When to use it: When you need detailed competitive positioning of companies.

Example use case: “Is Amazon the leader in cloud computing compared to Microsoft and Google?”

Key parameters:

• prompt: The competitive question to analyze
• criteria: Evaluation criteria (from Get Criteria for Competitive Analysis)
• stocks: Companies to compare
• all_text_data: Information about the companies
• target_stock: Optional focal company for the analysis

Tips:

• Provides detailed scoring and analysis across multiple criteria
• Evaluates relative market positioning
• Requires criteria, stocks, and comprehensive text data
• Best for qualitative market leadership questions
• Not for simple quantitative comparisons