group-dashboard

Group Dashboard — Multi-Location Dealer Group Overview

User Profile (Required)

This skill requires a dealer group profile with multiple locations.

1. Read the marketcheck-profile.md project memory file.
2. Check user_type:
   • If dealer_group: use dealer_group.locations[] — this is the primary path
   • If dealer (single location): inform the user: "This skill is for multi-location dealer groups. You have a single-location profile. Use /daily-briefing or /weekly-review for your store."
   • If neither exists: "No profile found. Run /onboarding and select 'Dealer Group' to set up your locations."
3. Extract:
   • group_name ← dealer_group.group_name
   • locations[] ← dealer_group.locations (each with dealer_id, name, dealer_type, zip, state)
   • is_publicly_traded ← dealer_group.is_publicly_traded
   • ticker ← dealer_group.ticker
   • country ← location.country
   • preferences ← preferences (group-level defaults)
4. Confirm: "Loading group dashboard for [group_name] ([N] locations)"

User Context

The primary user is a dealer group executive (VP Operations, Regional Director, GM of a multi-rooftop group) who needs a single-screen view of all locations' health. The goal is to identify which stores need attention NOW — aging inventory, pricing problems, or operational outliers.

Workflow: Group Health Dashboard

Step 1 — Parallel inventory scan across all locations

Use the Agent tool to spawn the marketcheck-cowork-plugin:group-scanner agent with this prompt:

Scan all locations for group health dashboard. Locations: [JSON array of {dealer_id, name, zip, state, dealer_type} for each location] Country: [country] Mode: facets_and_aging Aging threshold: [preferences.dom_aging_threshold or 60] Return per location: total_units, aged_units (DOM > threshold), avg_dom, top_makes (facets)

The group-scanner will spawn parallel lot-scanner agents, one per location, and aggregate results.

Step 2 — Calculate group metrics

From the scanner results, calculate per location:

• Total units
• Aged units (DOM > threshold)
• Aged % = aged / total × 100
• Avg DOM
• Estimated daily floor plan burn on aged units = aged_count × preferences.floor_plan_cost_per_day
• Health Score (0-100): Start at 100. Deduct: -2 per % of aged inventory (e.g., 15% aged = -30), -1 per day of avg DOM above 35 (e.g., avg DOM 50 = -15). Minimum 0.

Group totals:

• Total units across group
• Total aged units
• Group aged %
• Group avg DOM (weighted by units)
• Total daily floor plan burn

Step 3 — Rank locations

Rank locations by:

1. Worst health score (lowest score = most attention needed)
2. Most aged units (absolute count)
3. Highest avg DOM

Step 4 — Generate top 3 actions

Based on rankings, generate the 3 most impactful actions:

• If a location has aged % > 20%: "[Location] has [N] aged units ([X]%) — trigger price review. Burning $[X]/day in floor plan."
• If a location has avg DOM > 50: "[Location] avg DOM is [X] days — review merchandising and photo quality."
• If a location has aged % < 5% AND avg DOM < 25: "[Location] is turning fast — consider restocking. May be under-inventoried."
• If two locations have contrasting performance: "[Location A] has excess [segment] while [Location B] is under-stocked — consider a transfer."

Output

GROUP DASHBOARD — [Group Name] ([N] locations)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[If publicly traded: Ticker: [TICKER]]

LOCATION HEALTH (sorted by health score)

Location                  | Units | Aged (60+) | Aged % | Avg DOM | Floor Plan Burn | Health
--------------------------|-------|-----------|--------|---------|-----------------|-------
[Location 1]              | XXX   | XX        | XX%    | XX days | $XXX/day        | XX/100
[Location 2]              | XXX   | XX        | XX%    | XX days | $XXX/day        | XX/100
[Location 3]              | XXX   | XX        | XX%    | XX days | $XXX/day        | XX/100
...

GROUP TOTALS
  Total Units:        X,XXX across [N] locations
  Total Aged:         XXX units (XX%)
  Group Avg DOM:      XX days
  Floor Plan Burn:    $X,XXX/day ($XX,XXX/month) on aged units

TOP 3 ACTIONS (by dollar impact)
1. [Action with specific location, unit count, and dollar impact]
2. [Action]
3. [Action]

Health Score Interpretation

Score	Status	Action
80-100	Healthy	Monitor, consider restocking
60-79	Watch	Review pricing on aged units
40-59	Concern	Aggressive price reductions needed
0-39	Critical	Wholesale aged units, halt acquisitions

Important Notes

• This skill requires dealer_id for each location in the profile. Locations without a dealer_id will be skipped with a note.
• For US locations: full lot scanning with pagination. For UK locations: same scanning but with search_uk_active_cars.
• The group-scanner agent handles parallel execution — each location is scanned simultaneously for speed.
• This dashboard is designed for quick scanning. For deep analysis on a specific location, use the daily/weekly/monthly briefing skills with that location selected.
• If the group has more than 10 locations, show the 5 worst and 5 best by health score, with a "Show all" option.

Self-Check (before presenting to user)

• All locations in the group represented
• Group totals sum correctly across locations
• Health indicators (aged %, avg DOM) calculated per-location
• No locations missing from the summary
• Data is current (today's date context)