monthly-dealer-strategy

name	monthly-dealer-strategy
description	Comprehensive monthly market intelligence. Triggers: "monthly review", "monthly strategy", "monthly dealer report", "strategic review", "monthly market analysis", "end of month analysis", "what's my market doing this month", "monthly performance", "strategic briefing", market share, depreciation trends, market conditions, full inventory intelligence.

Date anchor: Today's date comes from the # currentDate system context. Compute ALL relative dates from it. Example: if today = 2026-03-14, then "prior month" = 2026-02-01 to 2026-02-28, "current month" (most recent complete) = February 2026, "three months ago" = December 2025. Never use training-data dates.

get_sold_summary parameter safety:

• Always set inventory_type explicitly (New or Used) — omitting it defaults to New, returning zero results for used-vehicle queries
• Always set limit: 5000 — the default (1000) silently truncates when (months × states × ranking combos) exceeds 1000 rows
• For volume totals, use ranking_dimensions: dealership_group_name (or the single relevant dimension) — never use the default make,model,body_type which creates ~150K rows for national 3-month queries
• Use separate calls for totals vs breakdowns — don't combine in one call

Monthly Dealer Strategy — Comprehensive Market Intelligence Report

A strategic monthly analysis that gives a dealer the complete picture: how their brand is performing in the market, which models are depreciating fastest, what the broader market trends look like, and a full inventory intelligence report. Run this on the first Monday of each month.

Architecture: This skill uses up to 3 parallel sub-agents to generate the 5-section report. Brand analytics, market demand, and lot composition run simultaneously.

Note: This skill is primarily US-focused. Most sections require get_sold_summary which is US-only. UK dealers will receive a supply-side market overview only.

Profile

Load the marketcheck-profile.md project memory file — required (if missing, tell user to run /onboarding and stop). Extract: dealer_id, dealer_name, dealer_type, franchise_brands, zip/postcode, state/region, country, radius, target_margin, recon_cost, floor_plan_per_day, max_dom, aging_threshold. Also extract: default_inventory_type from preferences ("used" | "new" | "both"; default "used" if not set). Apply as car_type in all lot-scanner and search calls, and as inventory_type in all sold summary calls. Override if user explicitly states otherwise. Never mix new and used data in the same report section. US: all agents. UK: lot-scanner only — Section 5 (supply-side) available; Sections 1-4 require US sold data. Calculate: current_month, prior_month, three_months_ago date ranges. Confirm: "Running monthly strategy report for [dealer_name]..."

Execution: Multi-Agent Orchestration

Wave 1 — Launch Simultaneously (US)

Launch these three agents in parallel using the Agent tool. All are independent.

Agent A: lot-scanner (facets-only mode)

Use the Agent tool to spawn the dealer:lot-scanner agent with this prompt:

Pull lot composition for dealer_id=[dealer_id], country=US, mode=facets_only. Use rows=0 with facets=make|0|10|1,model|0|20|1 and stats=price,dom. Return the top 5 make/model combinations by count and overall lot statistics.

Agent B: market-demand-agent

Use the Agent tool to spawn the dealer:market-demand-agent agent with this prompt:

Generate full inventory intelligence for state=[state], dealer_type=[dealer_type], zip=[zip], radius=[radius], target_margin_pct=[target_margin], recon_cost=[recon_cost]. Date range: [current_month date_from] to [current_month date_to]. Run sections: ds_ratios, turn_rates. Also include body type breakdown.

Agent C: brand-market-analyst

Use the Agent tool to spawn the dealer:brand-market-analyst agent with this prompt:

Analyze brand performance and market trends for state=[state], dealer_type=[dealer_type], franchise_brands=[brands list]. Current month: [current_month dates]. Prior month: [prior_month dates]. Three months ago: [three_months_ago dates]. Run sections: brand_share, market_trends. Skip depreciation (will provide lot models in Wave 2).

Wave 2 — After Lot Scanner Completes

Once lot-scanner returns the top 5 make/model combos from the dealer's lot:

Run depreciation watch directly (or spawn brand-market-analyst again):

For each of the top 5 models, call mcp__marketcheck__get_sold_summary with:

• make, model: the model
• state: from profile
• inventory_type: Used
• ranking_dimensions: make,model
• ranking_measure: average_sale_price
• top_n: 1
• limit: 5000
• Two calls per model: current_month dates AND three_months_ago dates → Extract only: average_sale_price per model per period. Discard full response.

Calculate:

• Price Change $ = current avg_sale_price - baseline avg_sale_price
• Monthly Depreciation Rate % = (Price Change / baseline) / 3 × 100
• Flag models with monthly depreciation > 1.5% as ACCELERATING DEPRECIATION

Wave 3 — Supply-Side Overview (US + UK)

This simple single call can run after Wave 1 completes or in parallel with Wave 2.

US: Call mcp__marketcheck__search_active_cars UK: Call mcp__marketcheck__search_uk_active_cars

With:

• zip/postcode: from profile
• radius: from profile
• car_type: used
• facets: make|0|20|1,body_type|0|10|1
• stats: price,dom
• rows: 0 → Extract only: facet counts per make and body_type, price/dom stats (mean, median, count). Discard full response.

UK Execution Path

For UK dealers, only run:

1. Wave 3 (Supply-Side Overview) using search_uk_active_cars
2. Note: "Sections 1-4 require US sold data and are not available for UK dealers."

Assembly — Combine All Results

1. Section 1 (Brand Performance) — from brand-market-analyst agent output
2. Section 2 (Depreciation Watch) — from Wave 2 depreciation calculations + lot-scanner facets
3. Section 3 (Market Trends) — from brand-market-analyst agent output
4. Section 4 (Inventory Intelligence) — from market-demand-agent agent output
5. Section 5 (Supply-Side Overview) — from Wave 3

Output

Present: 5-section report — (1) brand performance share table with MoM change in bps, (2) depreciation watch for lot models flagging >1.5%/month, (3) market trends with fastest depreciating models and MSRP parity, (4) inventory intelligence with D/S ratios and aging summary, (5) supply-side overview by body type and make. End with 30-DAY ACTION PLAN (5 items) and key metrics to watch. Cite report period and data source.