Coverage vs opportunity across target states. Triggers: "territory overview", "market penetration", "where should I focus", "state coverage dashboard", "territory report", "which states have the most opportunity", "compare my markets", "territory prioritization", coverage vs opportunity across target states.
From lender-salesnpx claudepluginhub marketcheckhub/marketcheck-cowork-plugin --plugin lender-salesThis skill uses the workspace's default tool permissions.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Designs, audits, and improves analytics tracking systems using Signal Quality Index for reliable, decision-ready data in marketing, product, and growth.
Enforces A/B test setup with gates for hypothesis locking, metrics definition, sample size calculation, assumptions checks, and execution readiness before implementation.
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: target_states, price_range_min, price_range_max, preferred_year_range, max_mileage, approved_makes, preferred_dealer_types, min_dealer_inventory, country, zip, radius. If missing, ask for target states + lending criteria. US: search_active_cars, get_sold_summary. UK: search_uk_active_cars only (dealer counts only, no velocity). Confirm: "Using profile: [company], [lending_type], states: [list]". All preference values from profile — do not re-ask.
Lender sales rep or regional manager assessing where to focus their time. Need to know: which states have the most untapped dealer opportunities, how many units fit lending criteria per state, and where the velocity is highest.
get_sold_summary is US-only. For UK profiles, territory dashboard can only show active supply counts per region — no sold velocity, no monthly volume, no days supply. Clearly label UK output as "supply-only" and omit opportunity scores that depend on velocity.dealer_id facet in search_active_cars returns at most 50 dealers per call. If a state has hundreds of dealers in-criteria, the facet undercounts. Use the num_found total from stats as the true eligible-unit count, not the sum of facet buckets.advance_rate, use that instead. Never present the default as a fact — always label it "(assumed 80% advance rate)."Multi-agent approach: Use the territory-scanner agent for cross-state scanning.
Use the Agent tool to spawn the lender-sales:territory-scanner agent with this prompt:
Scan territory for lending opportunities. States=[target_states]. Price range=[min]-[max], year=[year_range], max_mileage=[max_mileage], approved_makes=[makes or "all"], dealer_type=[pref or omit], min_dealer_inventory=[min]. Date range: [first of prior month] to [last of prior month].
The agent returns per-state: eligible_dealers, eligible_units, monthly_volume, avg_dom, median_price, opportunity_score.
If the territory-scanner agent is unavailable, run the scan manually per state:
For EACH state in target_states:
a. Active supply — Call mcp__marketcheck__search_active_cars with state=[ST], car_type=used, seller_type=dealer, price_range=[min]-[max], year=[year_range], miles_range=0-[max_mileage], facets=dealer_id|0|50|2, stats=price,dom, rows=0. If approved_makes set, add make=[comma-separated]. If preferred_dealer_types set, add dealer_type.
→ Extract only: num_found (eligible_units), dealer count from facets, avg_price, median_price, avg_dom from stats. Discard full response.
b. Sold velocity — Call mcp__marketcheck__get_sold_summary with state=[ST], inventory_type=Used, ranking_dimensions=make, ranking_measure=sold_count, ranking_order=desc, top_n=5, date_from=[first of prior month], date_to=[last of prior month]. If approved_makes set, add make=[comma-separated].
→ Extract only: total sold_count (monthly_volume), average_days_to_sell. Discard full response.
c. Calculate opportunity_score per state:
After receiving results (from agent or manual scan):
Rank states by opportunity — Sort by opportunity_score descending.
Calculate territory totals:
Market sizing:
Priority classification:
When user says "compare Texas vs California" — pull both states using the manual scan steps above (or from cached territory-scanner results). Present side-by-side:
── State Comparison ─────────────────────────────────────────
Texas California
Eligible Dealers: XX XX
Eligible Units: X,XXX X,XXX
Monthly Volume: X,XXX X,XXX
Avg DOM: XX days XX days
Median Price: $XX,XXX $XX,XXX
Opportunity Score: XX/100 XX/100
Priority: FOCUS MAINTAIN
Days Supply: XX XX
Highlight the winning state per metric with a * marker.
── Territory Dashboard: [Company] ── [Month Year] ──────────
State | Dealers | Units | Mo Vol | Avg DOM | Med Price | Score | Priority
-------|---------|-------|--------|---------|-----------|-------|----------
TX | XX | X,XXX | X,XXX | XX | $XX,XXX | XX | FOCUS
FL | XX | X,XXX | X,XXX | XX | $XX,XXX | XX | FOCUS
CA | XX | X,XXX | X,XXX | XX | $XX,XXX | XX | MAINTAIN
...
TOTAL | XXX | XX,XXX| XX,XXX | XX | $XX,XXX | -- | --
── Market Sizing (assumed 80% advance rate, 20% penetration) ──
Total Lendable Portfolio Value: $XXX,XXX,XXX
Monthly Origination Potential: XXX units / $X,XXX,XXX
Annual Revenue Estimate (1.5% spread): $X,XXX,XXX
── Priority Allocation ──
FOCUS (50% of time): [state list]
MAINTAIN (30%): [state list]
OPPORTUNISTIC (20%): [state list]
── Top 3 Actions ──
1. [Specific state + dealer targeting recommendation]
2. [Specific state + dealer targeting recommendation]
3. [Specific state + dealer targeting recommendation]
Source: MarketCheck market data, [Month Year]
Territory map table: State, Eligible Dealers, Eligible Units, Monthly Volume, Avg DOM, Median Price, Opportunity Score, Priority (FOCUS/MAINTAIN/OPPORTUNISTIC). Territory totals row. Market sizing: total portfolio value, monthly originations, annual revenue. Priority recommendations: "Spend 50% of time in [top states], 30% in [middle], 20% in [bottom]." Top 3 actions: specific state + dealer targeting recommendations.
target_states list must appear in the output table. If a state returned zero results, show it with zeros and a note ("no matching inventory found") rather than omitting it.