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.

Market Trends Reporter — Market Intelligence for Sector Analysis

Generate investment-grade market trend analyses using real sold transaction data and live inventory signals. Every insight is mapped to stock tickers and framed with BULLISH / BEARISH / NEUTRAL / CAUTION investment 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 geographic scope and focus. US-only. Confirm profile.

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

User Context

Financial analyst or sector strategist needing market trend intelligence for investment decisions. Every insight tied to stock tickers with explicit BULLISH/BEARISH/NEUTRAL/CAUTION investment signals.

Workflow: Fastest and Slowest Depreciating Models (Residual Signal)

Identify which models are losing value fastest (or holding value best) and map to OEM tickers.

1. Current period sold summary — Call mcp__marketcheck__get_sold_summary with date_from/date_to (current month), inventory_type=Used, ranking_dimensions=make,model, ranking_measure=average_sale_price, ranking_order=desc, top_n=50, state if scoped. → Extract only: make, model, average_sale_price, sold_count per entry. Discard full response.

2. Prior period sold summary — Repeat step 1 for same month one year ago (or per benchmark_period_months). → Extract only: make, model, average_sale_price, sold_count per entry. Discard full response.

3. For each make/model, calculate:

   • Depreciation Rate (%) — only include models with 100+ units for statistical reliability
   • Map each model to its OEM ticker

4. Present two tables with tickers:

   • Fastest Depreciating Models (Top 15) — with ticker and investment signal
   • Best Value-Holding Models (Bottom 15) — with ticker

5. Investment narrative: "STLA models dominate the fast-depreciation list with 4 of the top 10 — BEARISH for STLA residual exposure. TM and TSLA models lead value retention — BULLISH for residual books."

6. For the top 3 fastest depreciating, pull current active listings as data points.

Workflow: EV vs ICE Price Parity Tracker (Adoption Thesis Signal)

Track the price gap as a signal for EV adoption acceleration.

1. EV + ICE sold summary by segment — Call mcp__marketcheck__get_sold_summary for each fuel_type_category (EV, ICE) x body_type (SUV, Sedan, Pickup) x period (current, prior). Use ranking_dimensions=make,model, ranking_measure=average_sale_price, ranking_order=desc, top_n=10. → Extract only: average_sale_price, sold_count per fuel_type/body_type/period combo. Discard full response.

2. Calculate per body type:

   • EV-to-ICE Price Gap ($) and (%) with trend
   • Year-over-Year Gap Change
   • Parity Signal: APPROACHING PARITY (<15% gap, narrowing) = BULLISH for EV OEM tickers; STALLED = NEUTRAL; DIVERGING = BEARISH for mass-market EV thesis

3. Present with ticker implications:

   • Narrowing gap → BULLISH for TSLA, RIVN, LCID (addressable market expanding)
   • Widening gap → BEARISH for EV pure-plays (affordability barrier persists)
   • Segment-specific: "SUV parity approaching — BULLISH for GM (Equinox EV price point); Pickup gap still wide — CAUTION for F (Lightning pricing still premium)"

Workflow: Regional Price Variance (Geographic Signal)

Reveal where specific vehicles are cheapest/most expensive for portfolio valuation context.

1. Sold summary by state — Call mcp__marketcheck__get_sold_summary with date_from/date_to (recent month), make, model, inventory_type=Used, summary_by=state, limit=51. → Extract only: per state — average_sale_price, sold_count. Discard full response.

2. Calculate:

   • Price spread between most and least expensive states
   • State price index = state avg / national avg × 100

3. Present with investment context:

   • Regional pricing variance affects dealer group earnings by geography
   • Large spreads indicate market inefficiency — relevant for CVNA and KMX (national pricing models) vs traditional dealers (local pricing)
   • State-level trends can signal regional economic health relevant to auto lending portfolios

Workflow: New Car Markup and Discount Tracker (OEM Pricing Power Signal)

Identify which models sell above/below MSRP — the purest signal of supply/demand balance by OEM.

1. Top markups + deepest discounts — Call mcp__marketcheck__get_sold_summary with date_from/date_to (recent month), inventory_type=New, ranking_dimensions=make,model, ranking_measure=price_over_msrp_percentage, top_n=20. Run twice: ranking_order=desc (premiums), then ranking_order=asc (discounts). → Extract only: make, model, price_over_msrp_percentage, sold_count per entry. Discard full response.

2. Brand-level pricing power — Call with ranking_dimensions=make, ranking_measure=price_over_msrp_percentage, ranking_order=desc, top_n=20. → Extract only: make, price_over_msrp_percentage per brand. Discard full response.

3. Present with ticker-level aggregation:

   • OEM Pricing Power Ranking (by ticker):
     • Ticker | Makes | Avg % Over/Under MSRP | # Models Above MSRP | # Models Below | Signal
   • Signal: BULLISH if OEM's average is above MSRP (pricing power intact); BEARISH if below (incentive-dependent); trend direction matters most

4. Investment narrative: "TM and BMWYY are the only tickers with positive MSRP parity across their lineup — BULLISH for margins. STLA has the deepest average discount at -5.2% — BEARISH for per-unit gross profit. F crossed from above-MSRP to below on 3 models this month — margin compression signal."

5. For prior-period comparison, show trend and flag models that flipped from premium to discount territory — these are inflection points.

Output

Present: investment signal headline with tickers, ranked data tables with sample sizes and ticker-level aggregation, BULLISH/BEARISH/NEUTRAL/CAUTION signals per finding, and portfolio implications (overweight/underweight recommendations). Cite data source and period.

Important Notes

• US-only: Requires get_sold_summary for sold data.
• Always map brands to tickers. An analyst evaluating market trends is making stock-level decisions.
• Depreciation trends are LEADING indicators — they precede incentive changes, production adjustments, and earnings impacts by 1-2 quarters.
• The MSRP parity tracker is the purest signal of OEM pricing power — a shift from above-MSRP to below is a significant inflection point for the ticker.
• For comprehensive market intelligence, this skill combines well with the market-momentum-report for the broadest sector view.