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.

DOM Monitor — Days on Market as a Leading Investment Signal

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 needing DOM as a primary analytical dimension — not a secondary metric buried inside other analyses. Days on market is the single most predictive metric for earnings direction in recent cycles: Ford's DOM rose 54% Q3→Q4 2025 preceding a 32% earnings miss; Stellantis's DOM fell 14% Q2→Q4 signaling a turnaround. This skill provides dedicated DOM tracking with rate-of-change calculations, inflection point detection, and distress flagging.

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 1: DOM Ranking by OEM

Use when user asks "which brands are sitting longest" or "DOM ranking across OEMs."

Step 1 — Pull current DOM data

Call mcp__marketcheck__get_sold_summary with:

• state: from profile or user input (or omit for national)
• date_from / date_to: most recent complete month
• ranking_dimensions: make
• ranking_measure: average_days_on_market
• ranking_order: desc (longest first)
• top_n: 25

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

Step 2 — Aggregate to ticker level

Map makes to tickers. For multi-make tickers, calculate weighted average DOM (weighted by sold_count). Rank tickers by DOM.

Step 3 — Signal assignment per ticker

Signal	Threshold
BULLISH	Avg DOM < 30 days (hot seller, pricing power intact)
NEUTRAL	Avg DOM 30–60 days (healthy range)
CAUTION	Avg DOM 60–90 days (aging, incentives likely)
BEARISH	Avg DOM > 90 days (distress, production cuts likely)

Workflow 2: DOM Trend (Multi-Period with Rate-of-Change)

Use when user asks "DOM trend for Ford" or "is demand softening for Toyota."

Step 1 — Pull 5-period DOM data

For EACH period (current, 1mo, 2mo, 3mo, 6mo), call mcp__marketcheck__get_sold_summary with:

• make: each make in the target ticker's mapping
• state: from profile
• date_from / date_to: the period's date range
• ranking_dimensions: make
• ranking_measure: average_days_on_market
• top_n: 1

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

Step 2 — Calculate rate-of-change

• DOM at each period: Weighted average across ticker's makes
• MoM DOM Change: current_dom - prior_dom (days)
• MoM DOM Change %: (current - prior) / prior × 100
• 3-Month Acceleration: Compare MoM change at period 1 vs period 3 — is the rate of change itself increasing?
• 6-Month Trajectory: Direction from Period 5 → Period 1

Step 3 — Inflection detection

Flag if DOM trajectory changes direction (declining → rising, or rising → declining) within the 5-period window. An inflection from declining to rising is a CAUTION signal — it means demand was improving but is now softening.

Step 4 — Signal assignment

Signal	Threshold
BULLISH	DOM declining >5 days/month (accelerating sell-through)
NEUTRAL	DOM stable within ±2 days/month
CAUTION	DOM rising 2–5 days/month OR inflection from declining to rising
BEARISH	DOM rising >5 days/month (sustained demand deterioration)

Workflow 3: Segment Velocity Comparison

Use when user asks "which vehicle segments have slowing velocity" or "SUV vs truck DOM."

Step 1 — Pull segment-level DOM

For each major body type (SUV, Pickup, Sedan, Hatchback), call mcp__marketcheck__get_sold_summary with:

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

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

Repeat for prior month.

Step 2 — Cross-segment comparison

Map makes to tickers. For each segment, calculate:

• Segment average DOM (all makes)
• Ticker's DOM within segment vs segment average
• MoM change per ticker per segment

Step 3 — Identify most-exposed tickers

Flag tickers with above-average DOM in high-volume segments (SUV, Pickup). These tickers face the most margin pressure from aging inventory.

Workflow 4: DOM Inflection Point Flagging

Use when user asks "DOM distress signals" or "which OEMs are crossing danger thresholds."

Step 1 — Pull active inventory DOM

Call mcp__marketcheck__search_active_cars with:

• make: each make in target ticker(s)
• seller_state: from profile
• stats: dom
• rows: 0

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

Step 2 — Threshold check

Flag makes crossing these thresholds:

• >60 days active DOM: CAUTION — aging inventory, expect discounts
• >90 days active DOM: BEARISH — demand distress, incentive costs rising
• >120 days active DOM: BEARISH SEVERE — production cut signal, channel stuffing risk

Step 3 — Compare active vs sold DOM

Active DOM (from Step 1) vs Sold DOM (from Workflow 2) reveals the demand velocity gap:

• If active DOM >> sold DOM: inventory is building faster than it's selling = BEARISH
• If active DOM ≈ sold DOM: healthy flow-through = NEUTRAL
• If active DOM << sold DOM: tight supply, undersupply premium = BULLISH

Output

Present: DOM ranking table by ticker with signal, 5-period trend table with rate-of-change and trajectory, segment velocity comparison, inflection alerts, active vs sold DOM gap. Every metric includes signal with rationale. Connect DOM trends to earnings implications: rising DOM → incentive spend → margin compression → earnings headwind.

Important Notes

• This skill is US-only.
• Date ranges use the most recent COMPLETE month.
• DOM is the PRIMARY metric in this skill — do not dilute with pricing or volume analysis. Those are covered by other skills.
• For EV pure-plays (TSLA, RIVN, LCID), DOM is especially important as it reveals whether demand is keeping pace with production ramp.
• Low volume makes (<100 units/month) should be flagged with reduced confidence.
• Always cite actual numbers. Always map to tickers.
• Differentiation from existing skills: DOM appears as a secondary metric in oem-stock-tracker (Step 6) and dealer-group-health-monitor. This skill makes DOM the sole analytical dimension with dedicated rate-of-change tracking, inflection detection, and distress threshold flagging.