Help us improve
Share bugs, ideas, or general feedback.
From analyst
Days-on-market as a leading investment signal. Triggers: "days on market", "DOM trends", "inventory aging", "sell-through velocity", "demand distress", "which brands are sitting longest", "DOM signal", "DOM inflection", "what's sitting on lots", "demand softening signal", dedicated days-on-market analysis as a primary leading indicator for investment decisions rather than as a secondary metric.
npx claudepluginhub marketcheckhub/marketcheck-cowork-plugin --plugin analystHow this skill is triggered — by the user, by Claude, or both
Slash command
/analyst:dom-monitorThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
> **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.
Provides UI/UX resources: 50+ styles, color palettes, font pairings, guidelines, charts for web/mobile across React, Next.js, Vue, Svelte, Tailwind, React Native, Flutter. Aids planning, building, reviewing interfaces.
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Explores codebases via GitNexus: discover repos, query execution flows, trace processes, inspect symbol callers/callees, and review architecture.
Share bugs, ideas, or general feedback.
Date anchor: Today's date comes from the
# currentDatesystem 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.
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.
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.
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
Use when user asks "which brands are sitting longest" or "DOM ranking across OEMs."
Call mcp__marketcheck__get_sold_summary with:
state: from profile or user input (or omit for national)date_from / date_to: most recent complete monthranking_dimensions: makeranking_measure: average_days_on_marketranking_order: desc (longest first)top_n: 25→ Extract only: make, average_days_on_market, sold_count per make. Discard full response.
Map makes to tickers. For multi-make tickers, calculate weighted average DOM (weighted by sold_count). Rank tickers by DOM.
| 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) |
Use when user asks "DOM trend for Ford" or "is demand softening for Toyota."
For EACH period (current, 1mo, 2mo, 3mo, 6mo), call mcp__marketcheck__get_sold_summary with:
make: each make in the target ticker's mappingstate: from profiledate_from / date_to: the period's date rangeranking_dimensions: makeranking_measure: average_days_on_markettop_n: 1→ Extract only: average_days_on_market, sold_count per make per period. Discard full response.
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.
| 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) |
Use when user asks "which vehicle segments have slowing velocity" or "SUV vs truck DOM."
For each major body type (SUV, Pickup, Sedan, Hatchback), call mcp__marketcheck__get_sold_summary with:
state: from profilebody_type: the segmentdate_from / date_to: current monthranking_dimensions: makeranking_measure: average_days_on_marketranking_order: desctop_n: 15→ Extract only: make, average_days_on_market, sold_count per make per segment. Discard full response.
Repeat for prior month.
Map makes to tickers. For each segment, calculate:
Flag tickers with above-average DOM in high-volume segments (SUV, Pickup). These tickers face the most margin pressure from aging inventory.
Use when user asks "DOM distress signals" or "which OEMs are crossing danger thresholds."
Call mcp__marketcheck__search_active_cars with:
make: each make in target ticker(s)seller_state: from profilestats: domrows: 0→ Extract only: num_found, stats.dom.mean, stats.dom.min, stats.dom.max. Discard full response.
Flag makes crossing these thresholds:
Active DOM (from Step 1) vs Sold DOM (from Workflow 2) reveals the demand velocity gap:
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.
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.