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Adds three new read-only tools the chat LLM can call to answer "who/what did the most X" questions that previously fell through the cracks: - rank_top_customers — ranks customers by invoiced_total, paid_total, invoice_count, or outstanding_balance over a named time period - rank_top_items — ranks catalog items by quantity_sold or revenue - rank_expense_categories — ranks expense categories by total spend All three share a new ResolvesPeriod trait that centralizes the period-name → [start, end] logic. GetCompanyStatsTool is refactored onto the same trait (identical public schema — the 'all_time' option is only exposed on the new ranking tools, where an unbounded window makes sense; stats over "all time" collapses every record into one giant bucket and is rarely useful). Each tool follows the existing pattern: snake_case name, one-sentence description tuned for LLM tool selection, JSON-schema parameters with injected company scoping (never trusting LLM-supplied company IDs), and JSON-encodable output. outstanding_balance on the customer tool explicitly ignores the period param since it's a current-state snapshot. Multi-company scoping tests lock down the session-authoritative boundary on every new tool. Per-metric ordering tests verify the aggregate queries actually rank correctly, and an ad-hoc-item exclusion test verifies rank_top_items skips invoice lines where item_id is null (free-typed entries that have no catalog row to rank by id). 15 new tests added (tests/Feature/Ai/Tools/); test suite grows from 398 to 413 passing. LLM tool count goes from 9 to 12 — the model will discover the new tools automatically via the function-calling schema with no prompt changes required.