dma-market-intelligence

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.

DMA Market Intelligence — Comprehensive Market Overview for Auction Planning

Profile

Load the marketcheck-profile.md project memory file if exists. Extract: zip/postcode, state/region, target_dmas, vehicle_segments, country, radius. If missing, ask for target state. US: get_sold_summary, search_active_cars. UK: search_uk_active_cars only (limited — supply snapshot only, no demand data). Confirm: "Using profile: [company], [state], [Country]". All preference values from profile — do not re-ask.

User Context

Auction house sales exec or regional director assessing a DMA for auction potential. Need to understand: Is this market worth running sales in? What segments have demand? Who are the big players?

Gotchas

1. dma-scanner agent availability — If the auction-house:dma-scanner agent is not available or fails, fall back to manual calls: run get_sold_summary for demand and search_active_cars with facets for supply. Do not error out — always have a manual fallback path.
2. "State" is not "DMA" — A DMA (Designated Market Area) is a metro-centric region, but MarketCheck API filters by state. Large states like Texas contain multiple DMAs (Dallas, Houston, San Antonio, Austin). When the user says "Dallas DMA," use zip + radius=100 instead of state=TX to avoid mixing Houston data into Dallas analysis.
3. Dealer group identification is approximate — The facets=dealer_id|0|50|2 call returns individual dealer locations, not parent groups. Multiple dealer_ids may belong to the same group (e.g., AutoNation has dozens of locations per state). Group-level intelligence requires manual recognition of known group names in seller_name fields.
4. Volume trend requires two periods — Never report "MoM trend" from a single month of data. Always pull at least current month and prior month. If the user asks for quarterly trends, pull 3+ months.
5. UK limitation — UK profiles get supply snapshot only via search_uk_active_cars. No demand velocity, no sold data, no market classification. Label the report "Supply Snapshot Only — demand data unavailable for UK market."

Field	Source	Default
Target state	User input or profile	—
Vehicle segments	Profile	all

Workflow: Full DMA Report

Multi-agent approach: Use the dma-scanner agent for comprehensive DMA analysis. If the agent is unavailable, fall back to the manual steps below.

Use the Agent tool to spawn the auction-house:dma-scanner agent with this prompt:

DMA market intelligence for state=[state]. Date range: [first of prior month] to [last of prior month]. Sections: all.

The agent returns: demand snapshot, supply health, top models, top dealer groups.

Manual fallback (if agent is unavailable or for quick single-section runs):

• Demand snapshot: Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, ranking_dimensions=body_type, ranking_measure=sold_count, ranking_order=desc, top_n=15, date_from=[YYYY-MM-01], date_to=[YYYY-MM-DD]. Extract: per body_type sold_count, average_sale_price, average_days_on_market.
• Supply health: Call mcp__marketcheck__search_active_cars with state=[XX], car_type=used, seller_type=dealer, facets=body_type|0|20|1, stats=price,dom, rows=0, price_min=1. Extract: total active supply (num_found), per body_type counts, avg_dom, avg_price.
• Top models: Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, ranking_dimensions=make,model, ranking_measure=sold_count, ranking_order=desc, top_n=20, same date range. Extract: per model sold_count, average_sale_price.
• Top dealer groups: Call mcp__marketcheck__search_active_cars with state=[XX], car_type=used, seller_type=dealer, facets=dealer_id|0|30|2, rows=0. Then for top 10 dealer_ids, call mcp__marketcheck__search_active_cars with dealer_id=[id], car_type=used, rows=1 to get seller_name and city. Extract: dealer name, city, unit count.

After receiving agent results, synthesize:

1. Market scorecard — Headline metrics: total monthly sold volume, avg sale price, avg DOM, days supply, volume trend (MoM).

2. Market classification:

   • EXPANDING: Volume > +5% MoM, days supply < 50, ASP rising
   • STABLE: Volume ±5%, days supply 50-75, ASP flat
   • CONTRACTING: Volume < -5%, days supply > 75, ASP falling
   • MIXED: Conflicting signals

3. Auction strategy implications:

   • EXPANDING: Increase sale frequency, more lanes, aggressive consignment sourcing
   • STABLE: Maintain current pace, focus on lane optimization
   • CONTRACTING: Reduce lanes, focus on high-demand segments only, lower reserves
   • MIXED: Segment-specific strategy

4. Top dealer groups — Frame as both potential consigners (they wholesale trades) AND buyers (they restock from auction). Note which groups are likely auction participants.

5. Segment opportunity map — Which segments to source for (high D/S) vs avoid (low D/S). Connect to lane planning.

Workflow: Multi-DMA Comparison

Use this when the user says "compare Texas vs California" or "which of my markets is strongest."

1. Run dma-scanner agent for each state in parallel.
2. Compare: total volume, ASP, DOM, days supply, growth rate.
3. Rank markets by auction opportunity score = (volume × 40) + (1/days_supply × 30) + (growth_rate × 30).

Output

Market scorecard table: metric, value, trend signal. Demand by segment with D/S ratios. Top 10 models table. Top 10 dealer groups table (flagged as potential consigners or buyers). Market classification with auction strategy. 3 actionable recommendations.

Output Template

-- DMA Market Intelligence: [State] — [Month Year] --------------------------------

-- Market Scorecard ----------------------------------------------------------------
| Metric              | Value        | Trend     | Signal      |
|---------------------|------------- |-----------|-------------|
| Monthly Sold Volume |       12,450 |    +6% MoM | EXPANDING  |
| Avg Sale Price      |      $27,800 |    +2% MoM | RISING     |
| Avg Days on Market  |           38 |    -3 days | IMPROVING  |
| Days Supply         |           42 |           | HEALTHY     |
| Active Listings     |       17,200 |           |             |

Classification: [EXPANDING / STABLE / CONTRACTING / MIXED]

-- Demand by Segment ---------------------------------------------------------------
| Segment  | Sold/Mo | Active Supply | D/S Ratio | Signal |
|----------|---------|---------------|-----------|--------|
| SUV      |   4,200 |         5,100 |      0.82 | WARM   |
| Pickup   |   3,100 |         3,400 |      0.91 | WARM   |
| Sedan    |   2,800 |         4,500 |      0.62 | COOL   |
| ...      |     ... |           ... |       ... | ...    |

-- Top 10 Models by Volume ---------------------------------------------------------
| Rank | Make/Model       | Sold/Mo | Avg Price  | Avg DOM |
|------|------------------|---------|------------|---------|
|    1 | Toyota RAV4      |     820 |    $29,400 |      28 |
| ...  | ...              |     ... |        ... |     ... |

-- Top 10 Dealer Groups ------------------------------------------------------------
| Rank | Dealer Group     | City        | Active Units | Likely Role        |
|------|------------------|-------------|------------- |--------------------|
|    1 | AutoNation       | Dallas      |          420 | BUYER + CONSIGNER  |
| ...  | ...              | ...         |          ... | ...                |

-- Auction Strategy ----------------------------------------------------------------
[Strategy recommendation based on market classification]

-- Recommendations -----------------------------------------------------------------
1. [Actionable recommendation]
2. [Actionable recommendation]
3. [Actionable recommendation]

Self-Check (before presenting to user)

1. Two periods of data for trends — MoM trend requires both current and prior month data. Never calculate a trend from a single data point. If only one month was retrieved, label trend as "N/A — single period."
2. D/S ratios use matching geographies — Demand (sold) and supply (active) must be from the same state/zip+radius. Mixing state-level sold with zip-level supply produces invalid D/S ratios.
3. Market classification matches criteria — EXPANDING requires volume > +5% MoM AND days supply < 50 AND ASP rising. Verify all three conditions are met before labeling. If conditions conflict, classify as MIXED.
4. Days supply formula is correct — Days supply = (active_listings / monthly_sold) x 30. Verify the number is reasonable (typically 30-90 for used vehicles). Values below 15 or above 120 suggest a data issue.
5. Dealer groups are labeled correctly — Dealers with high DOM (> market avg) and large lots are likely CONSIGNERS. Dealers with low DOM and mix gaps are likely BUYERS. Dealers with both signals are BUYER + CONSIGNER.
6. No UK demand data presented — If country is UK, confirm the output clearly states "Supply Snapshot Only" and no sold volume, D/S ratios, or market classification are shown.