Boolsai Signals

Each tool has a clearly distinct purpose: domain_timeline for historical stack changes on a domain, event_dossier for deep dive on a single event, farm_domain for ingesting new domains, find_signals for automated pattern discovery, recent_events for live feed, scan_at_date for historical URL scans, signal_diff for comparing two signal patterns, signal_landscape for a multi-dimensional sweep, test_filter for arbitrary hypothesis testing, ticker_history for ticker-level events, universe_summary for orientation, and wayback_backtest for backtesting on historical data. No two tools have overlapping roles.

All tool names follow a consistent snake_case pattern with a verb_noun structure: domain_timeline, event_dossier, farm_domain, find_signals, recent_events, scan_at_date, signal_diff, signal_landscape, test_filter, ticker_history, universe_summary, wayback_backtest. The naming is predictable and intuitive.

With 12 tools, the set is well-scoped for a financial signals analysis platform. Each tool serves a specific analytical need without redundancy or overload, making it easy for an agent to navigate.

The tool set covers the full workflow: orientation (universe_summary), discovery (find_signals, signal_landscape), hypothesis testing (test_filter, signal_diff), investigation (event_dossier, ticker_history, domain_timeline), data ingestion (farm_domain), and multiple historical analysis methods (scan_at_date, wayback_backtest, recent_events). Minor gap: no explicit export tool, but core analysis is well-covered.