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.

Earnings Preview — Pre-Earnings Channel Check for Automotive Equities

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 ticker and geography. US-only. Confirm profile.

User Context

Financial analyst preparing for earnings season. This is a SYNTHESIS skill — it pulls DOM, discount rates, inventory levels, sales velocity, EV sell-through, and new/used mix into a single unified pre-earnings risk assessment with explicit bull/bear scenarios and signal strength. This is the plugin's highest-value use case: "Ford reports next week, what's the channel data showing?"

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

Workflow: Pre-Earnings Channel Check

Step 1 — Resolve entity and determine quarter

Map ticker to makes. Determine the quarter under review: most recent complete quarter. Define:

• Current quarter: 3 months ending with the most recent complete month
• Prior quarter: the 3 months before that
• Year-ago quarter: same quarter last year (if available)

Confirm: "Pre-Earnings Channel Check: [Ticker] ([Company]) — [Quarter] Earnings"

Step 2 — Volume momentum (REVENUE SIGNAL)

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)
• date_from / date_to: current quarter
• ranking_dimensions: make
• ranking_measure: sold_count
• top_n: 1

Repeat for prior quarter. → Extract only: sold_count per make per period. Discard full response.

Sum to ticker level. Calculate:

• QoQ Volume Change % = (current_q - prior_q) / prior_q × 100
• Signal: BULLISH if QoQ > +3%; BEARISH if QoQ < -3%; NEUTRAL if within ±3%

Step 3 — Pricing/discount trend (MARGIN SIGNAL)

For each make, call mcp__marketcheck__get_sold_summary with:

• make: the make
• inventory_type: New
• date_from / date_to: last month of current quarter
• ranking_dimensions: make
• ranking_measure: price_over_msrp_percentage
• top_n: 1

Repeat for last month of prior quarter. → Extract only: price_over_msrp_percentage per make per period. Discard full response.

Calculate:

• Discount Rate Change (bps): QoQ change in price_over_msrp_percentage × 100
• Signal: BULLISH if discount narrowing >30 bps; BEARISH if widening >30 bps; NEUTRAL if stable

Step 4 — Inventory health (BALANCE SHEET SIGNAL)

Call mcp__marketcheck__search_active_cars with:

• make: each make
• seller_state: from profile
• car_type: new
• stats: price,dom
• rows: 0

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

Call mcp__marketcheck__get_sold_summary for same make/state for the most recent month. → Extract only: sold_count. Discard full response.

Calculate:

• Days Supply = (num_found / sold_count) × 30
• Signal: BULLISH if < 45 days (tight supply); NEUTRAL if 45–75 days; BEARISH if > 75 days

Step 5 — DOM velocity (DEMAND SIGNAL)

From sold data in Steps 2/3, extract average_days_on_market for current and prior quarter.

Calculate:

• DOM Change % = (current_dom - prior_dom) / prior_dom × 100
• Signal: BULLISH if DOM declining (selling faster); BEARISH if DOM rising >10%; NEUTRAL if stable

Step 6 — EV sell-through (if applicable)

Skip for non-EV OEMs (if EV makes <1% of portfolio). For EV pure-plays (TSLA, RIVN, LCID), this IS the volume analysis — skip and use Step 2 data.

For legacy OEMs with EV models: Call mcp__marketcheck__get_sold_summary with:

• make: the OEM's makes
• fuel_type_category: EV
• Current and prior quarter periods → Extract only: sold_count, average_sale_price per period. Discard full response.

Calculate:

• EV % of total OEM sales
• EV volume QoQ change %
• Signal: BULLISH if EV share growing >50 bps/quarter; BEARISH if EV DOM >90 days; NEUTRAL if stable

Step 7 — New/used mix (CONSUMER HEALTH SIGNAL)

Call mcp__marketcheck__get_sold_summary with:

• make: the OEM's makes (for OEM tickers) or dealership_group_name (for dealer group tickers)
• inventory_type: New — current quarter → Extract sold_count for new.

Repeat with inventory_type: Used. → Extract sold_count for used.

Calculate:

• New % of total = new_sold / (new_sold + used_sold) × 100
• QoQ shift in new% vs prior quarter
• Signal: BULLISH for OEM if new-car share rising (consumer confidence); BEARISH if falling (trade-down signal)

Step 8 — Synthesize Bull/Bear Scenarios

Compile all 6 dimensions (7 if EV applicable):

Dimension              | Data Point        | Signal
-----------------------|-------------------|----------
Volume Momentum        | QoQ: +X.X%        | [SIGNAL]
Pricing Power          | MSRP %: X.X%      | [SIGNAL]
Inventory Health       | X days supply      | [SIGNAL]
DOM Velocity           | X days, QoQ +X%   | [SIGNAL]
EV Sell-Through        | X% of total        | [SIGNAL]
New/Used Mix           | New: X%, shift Xbps| [SIGNAL]

Bull Case: List the conditions from data that support an earnings beat. Example: "Volume up QoQ, pricing power intact (above MSRP), tight days supply — suggests revenue and margin upside."

Bear Case: List the conditions that support an earnings miss. Example: "DOM rising, discount rate widening, inventory building — suggests demand softening and margin pressure."

Signal Strength:

• Strong: 5+ of 6 dimensions aligned in same direction
• Moderate: 3–4 dimensions aligned, 1–2 mixed
• Weak: No clear directional lean, mixed signals

Composite Signal:

Composite Signal	Criteria
BULLISH	5+ dimensions positive, no BEARISH on volume or pricing
CAUTIOUSLY BULLISH	4 positive, 1–2 mixed
NEUTRAL	Mixed signals, no strong directional lean
CAUTIOUSLY BEARISH	4 negative, 1–2 mixed
BEARISH	5+ negative, especially volume AND pricing both negative

Output

Present: ticker/company/quarter header, 6-dimension data table with signals, bull case narrative, bear case narrative, signal strength rating, composite signal, key watch items for the earnings call. Format as a structured pre-earnings briefing that can be shared with a portfolio manager.

Important Notes

• This skill is US-only.
• Date ranges use COMPLETE quarters. If in March 2026, the "current quarter" is Q4 2025 (Oct-Dec).
• This is a synthesis skill — it intentionally overlaps with other skills (pricing-power-tracker, dom-monitor, etc.) but combines their outputs into a unified thesis.
• For dealer group tickers (AN, KMX, CVNA), emphasize inventory turns, used vehicle mix, and DOM over MSRP metrics.
• Always present BOTH bull and bear cases, even when the signal is strongly directional. Analysts need to evaluate both sides.
• Signal strength should be explicit: "Strong BEARISH (5 of 6 negative)" or "Moderate BULLISH (4 of 6 positive, volume and pricing both up)."
• Always cite actual numbers. Always map to tickers.