Monthly Dealer Strategy — Comprehensive Market Intelligence Report

Monthly Dealer Strategy — Comprehensive Market Intelligence Report

A strategic monthly analysis that gives a dealer group the complete picture: how their brands are 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 locations will receive a supply-side market overview only.

Dealer Group Profile (Load First)

Load the marketcheck-profile.md project memory file. If missing, prompt /onboarding and stop.

Extract ALL locations from dealer_group.locations[]. For each location record: name, dealer_id, dealer_type, franchise_brands, zip (US) or postcode (UK), state (US) or region (UK), web_domain, country. Extract group-level preferences: default_radius_miles (→ radius), target_margin_pct (→ target_margin), recon_cost_estimate (→ recon_cost), floor_plan_cost_per_day, max_acceptable_dom (→ max_dom), dom_aging_threshold (→ aging_threshold).

Location scope: If a specific location name is provided, match to locations[].name and run for that location only. If "all" or no argument, iterate through EVERY location — all execution steps below run for each location using that location's own dealer_id, zip/postcode, state/region, dealer_type, franchise_brands, and country. Never pass one location's zip, state, or brands to a different location's agent or API call.

Inventory type: Read preferences.default_inventory_type from profile ("used" | "new" | "both"; default "used" if not set). Apply as inventory_type / car_type in all agent spawns and direct API calls for every location. If the user specifies a different type, override. Never mix new and used data in the same report section.

Tool routing per location: US: all agents. UK: Wave 3 (Supply-Side Overview) only. Calculate date ranges from # currentDate: current_month, prior_month, three_months_ago. Confirm: "Running monthly strategy for: [location name(s)] | Inventory: [used/new/both]"

Group Monthly Rollup

GROUP MONTHLY STRATEGY — [Group Name]
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━

BRAND PERFORMANCE (group-wide)
  [Aggregate brand share across all locations' states]
  [Highlight franchise brands with ★]

LOCATION SCORECARD
Location         | Units | Avg DOM | Aged % | D/S Ratio | Depreciation Risk | Health
-----------------|-------|---------|--------|-----------|-------------------|-------
[per location]

STRATEGIC PRIORITIES
1. [Group-level strategic recommendation]
2. [Second]
3. [Third]

NEXT MONTH FOCUS
  [What to watch for, acquisitions to pursue, categories to shift]

Execution: Multi-Agent Orchestration

Wave 1 — Launch Simultaneously (US)

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

For each location, spawn agents using THAT location's values (do not reuse values across locations):

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

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

Pull lot composition for dealer_id=[this location's dealer_id], country=[this location's country], 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. Location label: [this location's name].

Agent B: market-demand-agent

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

Generate full inventory intelligence for state=[this location's state], dealer_type=[this location's dealer_type], zip=[this location's 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. Location label: [this location's name].

Agent C: brand-market-analyst

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

Analyze brand performance and market trends for state=[this location's state], dealer_type=[this location's dealer_type], franchise_brands=[this location's franchise_brands]. 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). Location label: [this location's name].

Wave 2 — After Lot Scanner Completes

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

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

For each of the top 5 models from this location's lot-scanner output, call mcp__marketcheck__get_sold_summary with:

• make, model: the model
• state: this location's state
• 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: per model — average_sale_price (current and baseline). Discard full response.

Calculate:

• Price Change $ = current avg_sale_price - baseline avg_sale_price
• Monthly Depreciation Rate % = (Price Change / baseline) / 3 x 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: this location's zip/postcode
• radius: from preferences
• car_type: used
• facets: make|0|20|1,body_type|0|10|1
• stats: price,dom
• rows: 0 → Extract only: total count, avg price (stats), avg DOM (stats), make facets, body_type facets. Discard full response.

UK Execution Path

For UK locations, 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 locations."

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 (Brand Performance share table, Depreciation Watch for lot models, Market Trends with fastest-depreciating models, Inventory Intelligence with D/S ratios and aging, Supply-Side Overview), followed by a 5-item 30-day action plan with dollar impact and key metrics to watch next month.