Analyst PluginCompoundSkillv0.12.3

Public Group Scorecard

Quintile scorecard for publicly traded dealer groups — rank every group from Q1 (best) to Q5 (worst) across all operational dimensions — NEW v0.12.3

public group scorecardquintile ranking dealer groupsscorecard for auto retailersrank dealer stocks quintilebest and worst public dealer groupsQ1 to Q5 dealer ranking
Compound
Complexity
10–18
API Calls
$0.012 – $0.028
MC API Cost
$0.18 – $0.40
Total Cost

Purpose

Quintile scoring normalizes cross-group comparison by converting raw metrics into relative position rankings. Instead of asking 'is 28 days DOM good or bad?', the scorecard answers 'that DOM puts this group in Q1 for DOM efficiency vs all public peers' — immediately actionable for relative value positioning.

Public Group Scorecard runs a full multi-dimensional analysis across all 8 publicly traded dealer groups and assigns Q1–Q5 quintile rankings for Volume, ASP, DOM, Efficiency Score, and Days Supply. Delivers a composite quintile score and an investment heat map.

Audience:Relative value investorsEquity analysts running screensSector strategists building public retailer models

How It Works

Execution flow. MCP tool calls are shown inline on each step.

01
Full Peer Data Pullget_sold_summary

Runs get_sold_summary for all dealer groups (current + prior month) to gather all 8 public groups' volume, ASP, and DOM. Parallel with search_active_cars for days supply.

02
Quintile Calculation

For each metric (Volume, ASP, DOM, Efficiency, Days Supply), ranks all 8 groups and assigns Q1 (top 20%=best 1–2) through Q5 (bottom 20%=worst 7–8).

03
Composite Score

Averages quintile ranks across all dimensions (with DOM and Efficiency weighted 1.5x for investment relevance). Derives composite Q1–Q5 composite score.

04
Scorecard Output

Produces a visual scorecard matrix with quintile heat map, composite ranking, MoM quintile changes (improving/declining), and top/bottom investment picks.

MCP Tool Calls

ToolCallsPurpose
get_sold_summary2All 8 groups current and prior month full metrics
search_active_cars8–16Inventory days supply per group (new + used)

Example Output

PUBLIC GROUP SCORECARD — Q1 2026 | February 2026
═════════════════════════════════════════════════

QUINTILE SCORECARD (Q1=Best, Q5=Worst)
  Group       Ticker  Volume  ASP  DOM  Efficiency  DaysSupply  Composite  MoM
  ──────────  ──────  ──────  ───  ───  ──────────  ──────────  ─────────  ────
  Lithia      LAD     Q1      Q3   Q2   Q1          Q2          Q1         ↑+1
  Group 1     GPI     Q2      Q2   Q1   Q2          Q1          Q1         →
  Penske      PAG     Q2      Q1   Q2   Q2          Q2          Q2         →
  Asbury      ABG     Q3      Q2   Q3   Q3          Q3          Q3         ↓-1
  AutoNation  AN      Q3      Q3   Q4   Q4          Q3          Q3         ↓-2
  Sonic       SAH     Q4      Q4   Q3   Q3          Q4          Q4         →
  CarMax      KMX     Q4      Q4   Q4   Q4          Q4          Q4         →
  Carvana     CVNA    Q5      Q5   Q5   Q5          Q5          Q5         →

TOP PICKS: LAD (Q1 composite, improving), GPI (Q1 composite, stable)
AVOID:     CVNA (Q5 composite), AN (declining rapidly, -2 quintiles MoM)

Cost Estimate

TierCompound
API Calls10–18
MC API — best$0.012
MC API — worst$0.028
Claude — best$0.15
Claude — worst$0.35
Total range$0.18$0.40

8 scorecards/month ≈ $1–3

Limitations

  • US market only.
  • With only 8 publicly traded groups, quintile buckets are narrow — Q1 covers ranks 1–2, Q5 covers ranks 7–8.
  • KMX and CVNA's used-only model makes direct quintile comparison on ASP/segment metrics less valid.
  • Quintile scores are relative — a group can be Q1 in a weak peer cohort; always contextualize with absolute metrics.
Analyst Plugin
View all skills & commands