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.

New/Used Mix Analyzer — Inventory Type Shifts as Consumer & Market Signals

User Profile (Load First)

Load the marketcheck-profile.md project memory file if exists. Extract: tracked_tickers, tracked_makes, tracked_states, benchmark_period_months, country. If missing, ask for focus area and geography. US-only. Confirm profile.

User Context

Financial analyst needing new vs used vehicle mix analysis as a multi-faceted signal: (1) for OEM tickers — declining new-car share signals consumer trade-down and potential revenue headwind; (2) for dealer group tickers — the new/used revenue split drives margin mix; (3) for macro — new/used ratio is a consumer confidence proxy. Most alternative auto data covers either new or used — MarketCheck covers both, a key differentiator.

Built-in Ticker → Makes Mapping

OEM TICKERS:
F     → Ford, Lincoln
GM    → Chevrolet, GMC, Buick, Cadillac
TM    → Toyota, Lexus
HMC   → Honda, Acura
STLA  → Chrysler, Dodge, Jeep, Ram, Fiat, Alfa Romeo, Maserati
TSLA  → Tesla
RIVN  → Rivian
LCID  → Lucid
HYMTF → Hyundai, Kia, Genesis
NSANY → Nissan, Infiniti
MBGAF → Mercedes-Benz
BMWYY → BMW, MINI, Rolls-Royce
VWAGY → Volkswagen, Audi, Porsche, Lamborghini, Bentley

DEALER GROUP TICKERS:
AN    → AutoNation
LAD   → Lithia Motors
PAG   → Penske Automotive
SAH   → Sonic Automotive
GPI   → Group 1 Automotive
ABG   → Asbury Automotive
KMX   → CarMax (used-only)
CVNA  → Carvana (used-only)

Note: KMX and CVNA are used-only retailers. Their "mix" is 100% used by definition. For these tickers, the skill instead analyzes the vehicle age/quality mix within used inventory (see Workflow 5).

Workflow 1: OEM New/Used Split

Use when user asks "new vs used mix for Ford" or "is GM's new car share declining."

Step 1 — Pull new vehicle sold data

For EACH make in the ticker's mapping, call mcp__marketcheck__get_sold_summary with:

• make: the make
• state: from profile (or omit for national)
• inventory_type: New
• date_from / date_to: current month
• ranking_dimensions: make
• ranking_measure: sold_count
• top_n: 1

→ Extract only: sold_count per make. Discard full response.

Step 2 — Pull used vehicle sold data

Repeat Step 1 with inventory_type: Used. → Extract only: sold_count per make. Discard full response.

Step 3 — Repeat for prior periods

Repeat Steps 1–2 for prior month and 3-month-ago period.

Step 4 — Calculate mix metrics

• New % = new_sold / (new_sold + used_sold) × 100
• Used % = 100 - New %
• MoM Mix Shift (bps) = (current_new_% - prior_new_%) × 100
• 3-Month Mix Trend (bps) = (current_new_% - 3mo_new_%) × 100

Step 5 — Signal assignment

Signal	Investment Implication
BULLISH (for OEM)	New-car share rising >100 bps/quarter — consumer confidence, strong demand for new
NEUTRAL	Mix stable within ±50 bps
CAUTION	New-car share declining 50–150 bps — early trade-down signal
BEARISH (for OEM)	New-car share declining >150 bps — strong trade-down (BUT: BULLISH for KMX/CVNA)

Key nuance: A BEARISH signal for OEM tickers simultaneously can be BULLISH for used-vehicle retailer tickers. Always present both perspectives.

Workflow 2: CPO Volume Tracking

Use when user asks "CPO trends" or "certified pre-owned volume."

Step 1 — Pull CPO inventory

Call mcp__marketcheck__search_active_cars with:

• make: each make in the ticker's mapping
• seller_state: from profile
• car_type: certified
• stats: price,dom
• rows: 0

→ Extract only: num_found, stats.price.mean, stats.dom.mean. Discard full response.

Step 2 — Pull total used inventory

Repeat with car_type: used.

Step 3 — Calculate CPO penetration

• CPO % of Used = CPO count / (CPO count + non-CPO used count) × 100
• CPO Avg Price Premium = CPO avg price - non-CPO used avg price
• Signal: Rising CPO % = BULLISH for franchise OEM tickers (dealer confidence in brand), falling = CAUTION

Workflow 3: Consumer Trade-Down Signal (National)

Use when user asks "are consumers trading down" or "national new/used ratio."

Step 1 — Pull national new vs used

Call mcp__marketcheck__get_sold_summary with:

• (no make filter — total market)
• inventory_type: New
• date_from / date_to: current month
• ranking_dimensions: make
• ranking_measure: sold_count
• top_n: 25

→ Extract only: total sold_count across all makes. Discard full response.

Repeat with inventory_type: Used.

Repeat both for prior month and 3-month-ago period.

Step 2 — Calculate national ratio trend

• New/Used Ratio = total_new_sold / total_used_sold
• MoM change in ratio
• 3-Month trend direction
• Signal: Declining ratio = consumers shifting to used = macro stress signal; Rising ratio = confidence returning

Workflow 4: Segment-Specific Mix

Use when user asks "new vs used in SUVs" or "pickup truck new/used split."

Step 1 — Pull by body type

For target segment (SUV, Pickup, Sedan), call mcp__marketcheck__get_sold_summary with:

• body_type: the segment
• state: from profile
• inventory_type: New
• date_from / date_to: current month
• ranking_dimensions: make
• ranking_measure: sold_count
• top_n: 15

→ Extract only: make, sold_count per make. Discard full response.

Repeat with inventory_type: Used.

Step 2 — Identify segment-specific shifts

Which segments are seeing the strongest new→used shift? Map to tickers most exposed (e.g., if SUV mix shifting to used, BEARISH for SUV-heavy OEMs like F, GM).

Workflow 5: Dealer Group New/Used Mix

Use when user asks "dealer group new/used split", "compare AN vs LAD revenue mix", or "inventory mix for [any dealer group name]." Works with any dealer group tracked in MarketCheck — not limited to the 8 public groups.

Step 1 — Pull by dealer group

For each target dealer group ticker, call mcp__marketcheck__get_sold_summary with:

• dealership_group_name: the group name
• inventory_type: New
• date_from / date_to: current month
• ranking_dimensions: make
• ranking_measure: sold_count
• top_n: 15

→ Extract only: total sold_count. Discard full response.

Repeat with inventory_type: Used.

Step 2 — Compare groups

Calculate new% and used% for each group. Compare:

• Used-heavy groups (KMX, CVNA): 100% used — analyze by vehicle age instead
• Balanced groups (AN, LAD, PAG): Track the new/used split trend — shifting toward used = margin mix change
• Higher used % generally means higher gross margin per unit but lower revenue per unit

Output

Present: OEM new/used split table with trend and signal, CPO penetration data, national trade-down signal, segment-specific mix shifts, dealer group comparison. Every metric includes signal with dual perspective (OEM impact vs used-retailer impact). Connect mix shifts to revenue and margin implications.

Important Notes

• This skill is US-only.
• Date ranges use the most recent COMPLETE month.
• KMX and CVNA are 100% used retailers — for these tickers, use Workflow 5 variant that analyzes WITHIN-used quality mix instead of new/used split.
• The car_type parameter in search_active_cars accepts: new, used, certified. The inventory_type in get_sold_summary accepts: New, Used.
• Always present the dual signal perspective: a decline in new-car share is BEARISH for OEM tickers but can be BULLISH for used-vehicle retailer tickers.
• Always cite actual numbers. Always map to tickers.