Franlever

Render an inline bar chart comparing one metric (sales, labor %, avg ticket, or orders) across stores over a window, ranked best-first with the brand median marked. Call this when you compare stores on a metric or point out which stores lead or lag. Needs at least two stores with data for the window; for a single store use showMetricTrend instead. Real POS data — do not restate every bar in prose. Location ids come from list_locations. Over MCP this returns the chart's data points rather than drawing it.

showMetricComparison

Use this after search to retrieve one Franlever location or AI COO activity item.

fetch

Read the briefs AI COO has already sent this reader over a recent window: date, daily or weekly, headline, opening sentence, each store's lever with what to do and where it went, and the report lines. Call it when the operator asks what a past brief said, what led on a given day, or how this week's brief compares to last week's. These are the documents as sent; quote them as what the brief said on that date, never as today's figures. Location ids come from list_locations.

getBriefHistory

Read one store's sales by channel or destination as its POS names them (dine in, drive-thru, online ordering, delivery, catering), for a recent window against the equal window before: orders, net sales, average order, share of sales, large orders (five times the store's median ticket), and which half moved — fewer orders or smaller orders. Call it whenever the operator asks why a channel is up or down, what it is costing, or how order values compare across channels. Use the driver the tool computes rather than inferring one: a channel that lost its large orders is a group-order problem, not a channel outage. Defaults to 28 days, up to 56. Location ids come from list_locations.

getChannelBreakdown

Read one business day at one store from its POS: net sales, orders, average ticket, hourly labor % and labor hours, discounts, the day against a typical same weekday (median of recent ones), sales and orders by hour beside the people on the clock, sales by channel, and the largest single order's share of the day. Call it for any question about a specific day — what happened last Saturday, why yesterday was slow, how Tuesday compared — rather than asking the operator for a POS export. Use last-weekday for 'last Saturday' so the store's calendar decides the date. Quote the comparison basis the tool gives, and when one order carried the day, say so. Location ids come from list_locations.

getDayDetail

Read franchise disclosure filings (FDDs) as franchisors filed them with state regulators: Item 19 sales and cost figures, Item 20 outlet counts, unit growth and franchisee turnover, and Items 5-7 franchise fee, initial investment, royalty and ad fund. Use scope 'brand' for this workspace's own filing — royalty, fees, what we disclosed for unit volume — and scope 'industry' to place a brand against its segment. These are annual filings, not live data: name the issue year, say when a filing is stale, carry the sampling caveats, and never build a store-level action on them. Location ids come from list_locations.

getFranchiseDisclosures

Use this when you need sales, labor, orders, and average-ticket history for one authorized store.

get_location_performance

Read one store's orders and sales against the people on the clock, hour by hour in store time, averaged per trading day over the last few weeks and split by weekday group (Mon–Thu, Fri–Sat, Sun) or by single weekday. Each group marks its peak hour and the orders per person it runs there, and flags hours carrying more people than that pace would need. Call it for any question about labor or staffing by hour or day, when the rush is, or whether a shift is over- or under-staffed — never send the operator to pull a labor report. People counts include salaried managers. A staffing gap is people, not dollars: never price it. Defaults to 4 weeks, up to 8. Location ids come from list_locations.

getHourlyCoverage

Read what AI COO has raised at stores over a recent window, and what came back: each lever's title and detail, the version the GM was sent, when it was first raised and last confirmed, how many briefs carried it, and the GM's answer — done, later, or wrong — with any note they left. Call it when the operator asks what was flagged before, whether something has come up already, what a GM said, or how a store has responded. A lever with no answer says nothing about whether the work happened, because Franlever sees only replies: never call one overdue, late, outstanding, unanswered, ignored or slipping, and never count open levers as a failing. 'wrong' is a GM saying the call was mistaken — quote their note and treat it as information about the finding. Location ids come from list_locations.

getLeverHistory

Read the outside-world context for a store: actionable weather for today and tomorrow, county wages, menu-price inflation, ingredient cost pressure, and product recalls. These are the denominators — a store up 3.1% in a market up 3.3% went backwards — so call it before calling a move a win or a loss, and whenever weather, wages, or food costs could explain what the operator is asking about. State the effective date and never present a stale market figure as current. Location ids come from list_locations.

getMarketContext