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.

Pricing Power Tracker — Discount-to-MSRP Trend Intelligence for Investment Decisions

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 OEM/ticker and geography. US-only. Confirm profile.

User Context

Financial analyst (equity researcher, hedge fund analyst, portfolio manager) needing to track pricing power trends over time. Discount-to-MSRP trajectory is a leading indicator of margin pressure — widening discounts signal incentive spend acceleration and earnings risk. This skill focuses exclusively on TRENDS over multiple periods, not snapshots.

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
CVNA  → Carvana

If the user provides a ticker, map it to makes. If the user provides a make name, reverse-map to the ticker. For dealer group tickers, note that pricing power analysis is most relevant for OEM tickers.

Workflow 1: OEM Discount Rate Trend (Multi-Period)

Use when user asks "discount trend for Ford" or "pricing power over time for GM."

Step 1 — Resolve entity and periods

Map ticker to makes. Determine 5 time periods:

• Period 1 (current): most recent complete month
• Period 2: 1 month prior
• Period 3: 2 months prior
• Period 4: 3 months prior
• Period 5: 6 months prior (from benchmark_period_months or default 6)

Step 2 — Pull discount data per period

For EACH period, call mcp__marketcheck__get_sold_summary with:

• make: each make in the ticker's mapping
• state: from profile or user input (or omit for national)
• inventory_type: New
• date_from / date_to: the period's date range
• ranking_dimensions: make
• ranking_measure: price_over_msrp_percentage
• top_n: 1

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

Step 3 — Calculate trend metrics

• Discount Rate per Period: Average price_over_msrp_percentage across the ticker's makes (weighted by sold_count)
• MoM Discount Change (bps): (current_% - prior_%) × 100
• 3-Month Discount Velocity (bps/month): (current_% - 3mo_%) / 3 × 100
• 6-Month Trajectory: Direction of change from Period 5 → Period 1

Step 4 — Signal assignment

Signal	Threshold
BULLISH	Discount narrowing >30 bps/month OR above-MSRP (positive price_over_msrp_percentage)
NEUTRAL	Discount stable within ±20 bps/month
CAUTION	Discount widening 20–50 bps/month
BEARISH	Discount widening >50 bps/month OR >5% below MSRP

Workflow 2: Nameplate Discount Ranking

Use when user asks "which Ford models are discounted most" or "nameplate pricing power."

Step 1 — Pull nameplate-level data

Call mcp__marketcheck__get_sold_summary with:

• make: each make in the ticker's mapping
• state: from profile
• inventory_type: New
• date_from / date_to: current month
• ranking_dimensions: make,model
• ranking_measure: price_over_msrp_percentage
• ranking_order: asc (deepest discounts first)
• top_n: 15

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

Step 2 — Identify pricing leaders and laggards

• Pricing Leaders: Models selling above MSRP (positive %) — strong demand, no incentive needed
• Pricing Laggards: Models >3% below MSRP — incentive-dependent, margin drag
• Volume Impact: Weight by sold_count to determine which models drive the ticker's aggregate discount

Workflow 3: Within-Segment Comparison

Use when user asks "who has pricing power in SUVs" or "pickup truck discount comparison."

Step 1 — Pull segment-specific data

For a given body_type (SUV, Pickup, Sedan, etc.), call mcp__marketcheck__get_sold_summary with:

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

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

Step 2 — Rank by pricing power within segment

Map makes to tickers. Rank by price_over_msrp_percentage (highest = strongest pricing power). Flag tracked tickers. Identify segment leaders and laggards with investment signal per ticker.

Workflow 4: Discount Velocity Alert

Use when user asks "which OEMs are discounting faster" or "pricing erosion acceleration."

Step 1 — Pull two-period data for all OEMs

Call mcp__marketcheck__get_sold_summary for current month and 3 months ago with:

• state: from profile
• inventory_type: New
• ranking_dimensions: make
• ranking_measure: price_over_msrp_percentage
• ranking_order: asc
• top_n: 25

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

Step 2 — Calculate velocity and rank

• Discount Velocity = (current_% - 3mo_%) / 3 (bps per month)
• Rank all makes by velocity (most negative = fastest discounting)
• Map to tickers and aggregate

Step 3 — Signal and alert

Flag tickers where discount velocity exceeds -50 bps/month as BEARISH. Present ranked table with velocity, current discount rate, and signal.

Output

Present: discount trajectory chart data (5-period table with %, bps change, velocity), nameplate-level breakdown for target ticker, within-segment ranking, velocity alert table. Every metric includes BULLISH/BEARISH/NEUTRAL/CAUTION signal with rationale. Always tie to ticker and earnings implications (deeper discounting = lower gross margin per unit = earnings headwind).

Important Notes

• This skill is US-only. All data from get_sold_summary requires US market data.
• price_over_msrp_percentage is only meaningful for new vehicles (inventory_type=New). Do not apply to used vehicles.
• Date ranges should use the most recent COMPLETE month.
• Low volume makes (<100 units/month) should be flagged with reduced confidence.
• Always cite actual numbers, not just signals. Analysts need to verify against their own models.
• Always map insights back to stock tickers.
• Differentiation from existing skills: market-trends-reporter and depreciation-tracker do point-in-time MSRP snapshots. This skill tracks the TRAJECTORY over 5+ periods and calculates velocity (rate of change of discount rate).