depreciation-tracker

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Value erosion intelligence for auction timing. Triggers: "depreciation rate", "value retention", "which cars hold value", "which cars are losing value fastest", "depreciation curve for [model]", "residual trends", "fast depreciators", "consignment urgency by depreciation", understanding how quickly vehicles are losing value, which affects consignment timing and expected hammer prices.

MarketcheckHub By MarketcheckHub schedule Updated 4/14/2026

name: depreciation-tracker description: > Value erosion intelligence for auction timing. Triggers: "depreciation rate", "value retention", "which cars hold value", "which cars are losing value fastest", "depreciation curve for [model]", "residual trends", "fast depreciators", "consignment urgency by depreciation", understanding how quickly vehicles are losing value, which affects consignment timing and expected hammer prices. version: 0.1.0

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.

get_sold_summary parameter safety:

  • Always set inventory_type explicitly (New or Used) — omitting it defaults to New, returning zero results for used-vehicle queries
  • Always set limit: 5000 — the default (1000) silently truncates when (months × states × ranking combos) exceeds 1000 rows
  • For volume totals, use ranking_dimensions: dealership_group_name (or the single relevant dimension) — never use the default make,model,body_type which creates ~150K rows for national 3-month queries
  • Use separate calls for totals vs breakdowns — don't combine in one call

Depreciation Tracker — Value Erosion Intelligence for Auction Timing

Profile

Load the marketcheck-profile.md project memory file if exists. Extract: state/region, target_dmas, vehicle_segments, country. If missing, ask for state. US: get_sold_summary. UK: Not available (no sold data). Confirm: "Using profile: [company], [state]".

User Context

Auction house professional tracking depreciation to optimize consignment timing and set realistic reserve expectations. Fast-depreciating vehicles need faster consignment-to-sale cycles. Slow depreciators can afford more time in the pipeline.

Gotchas

  1. US-only skill — Depreciation tracking requires get_sold_summary with date-ranged pricing. UK has no sold data. If a UK profile triggers this skill, respond: "Depreciation tracking is available for US markets only."
  2. Mix shift inflates apparent depreciation — If cheaper trims gain market share over time, the average sale price drops even if per-trim values are stable. This is mix shift, not depreciation. For critical models, use ranking_dimensions=make,model,trim to isolate trim-level trends. Flag any model where trim composition changed significantly between periods.
  3. Seasonal patterns masquerade as depreciation — Convertible and sports car prices drop in fall/winter and recover in spring. 4WD truck prices spike in winter. A 3-month comparison that spans a seasonal boundary will show false depreciation or appreciation. Always note the months being compared and flag known seasonal segments.
  4. Volume floor prevents noise — Models with fewer than 50 sold units in a period produce unreliable averages. The workflow enforces sold_count > 50 for both periods. Below this threshold, report "INSUFFICIENT VOLUME — trend unreliable" rather than computing a rate.
  5. Annualized rate assumes linear depreciation — The formula monthly_rate x 12 assumes constant monthly depreciation, which is rarely true (depreciation accelerates in the first year, then slows). Present the annualized rate as "at current pace" and caution that it is a projection, not a guarantee.
Field Source Default
State Profile or user input
Vehicle segments Profile all

Workflow: Make/Model Depreciation Curve

Use this when the user asks "depreciation curve for [make/model]" or "how fast is [model] losing value."

  1. Get current period pricing — Call mcp__marketcheck__get_sold_summary with make=[make], model=[model], state=[XX], inventory_type=Used, limit=5000, ranking_dimensions=make,model, ranking_measure=average_sale_price, date_from=[YYYY-MM-01] (first of prior complete month), date_to=[YYYY-MM-DD] (last of prior complete month). Never use the current incomplete month. → Extract only: average_sale_price, sold_count. If sold_count < 50, flag "LOW VOLUME — trend may be unreliable" (see Gotcha #4). Discard full response.

  2. Get 3-month-ago pricing — Same call with date_from and date_to shifted back exactly 3 months. Example: if current period = Feb 2026, then 3-month-ago = Nov 2025. → Extract only: average_sale_price, sold_count. Discard full response.

  3. Get 6-month-ago pricing — Same call with date_from and date_to shifted back exactly 6 months. Example: if current period = Feb 2026, then 6-month-ago = Aug 2025. → Extract only: average_sale_price, sold_count. Discard full response.

  4. Calculate depreciation metrics:

    • 3-month change % = (current - 3mo_ago) / 3mo_ago × 100
    • Monthly rate = 3-month change / 3
    • Annualized rate = monthly rate × 12
    • Classification:
      • Monthly rate > 2%: FAST DEPRECIATION — consign immediately, lower reserves
      • Monthly rate 1-2%: MODERATE — standard 2-week pipeline acceptable
      • Monthly rate < 1%: SLOW — can hold in pipeline, strong residuals
  5. Auction timing recommendation:

    • FAST: "Every week this vehicle sits costs ~$[X] in value loss. Prioritize for next available sale."
    • MODERATE: "Standard 2-week consignment pipeline is acceptable. Expected value loss: ~$[X]."
    • SLOW: "This vehicle holds value well. No urgency on timing."

Workflow: Fastest/Slowest Depreciators in Market

Use this when the user asks "which cars are losing value fastest" or "depreciation rankings."

  1. Current period — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, limit=5000, ranking_dimensions=make,model, ranking_measure=average_sale_price, ranking_order=desc, top_n=30, date_from=[first of prior complete month], date_to=[last of prior complete month]. → Extract only: per model — make, model, average_sale_price, sold_count. Discard full response.

  2. 3-month-ago period — Same call with date_from and date_to shifted back 3 months. → Extract only: per model — make, model, average_sale_price, sold_count. Discard full response.

  3. Calculate and rank — For models present in BOTH periods with 50+ sold in EACH period:

    • Monthly depreciation rate = (current_avg - 3mo_avg) / 3mo_avg / 3 x 100
    • Sort by rate: fastest depreciators first (most negative monthly rate at top)
    • Models below the 50-sold threshold in either period: exclude and note "[N] models excluded — insufficient volume"
  4. Segment-level view — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, limit=5000, ranking_dimensions=body_type, ranking_measure=average_sale_price, date_from=[current period], date_to=[current period end]. Then same call with 3-month-ago dates.

    • Calculate per segment depreciation rate. Note seasonal segments (see Gotcha #3).

Workflow: Brand Residual Ranking

  1. Current period by brand — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, limit=5000, ranking_dimensions=make, ranking_measure=average_sale_price, ranking_order=desc, top_n=25, date_from=[first of prior complete month], date_to=[last of prior complete month]. → Extract only: per make — average_sale_price, sold_count. Discard full response.

  2. 6-month-ago period by brand — Same call with dates shifted back 6 months. → Extract only: per make — average_sale_price, sold_count. Discard full response.

  3. Calculate 6-month retention % per brand = (current_avg / 6mo_ago_avg) x 100. Only include brands with 100+ sold in both periods.

  4. Tier assignment: Tier 1 (> 98% retention), Tier 2 (95-98%), Tier 3 (90-95%), Tier 4 (< 90%).

Output

Depreciation curve table: Period, Avg Sale Price, Change %, Monthly Rate. Classification: FAST/MODERATE/SLOW with auction timing recommendation. For rankings: sorted table of models with depreciation rate, volume, and consignment urgency signal. Segment summary. Brand residual tiers.

Output Template — Single Model Curve

-- Depreciation Curve: [Year] [Make] [Model] — [State] ----------------------------

| Period          | Avg Sale Price | vs Current | Monthly Rate | Volume |
|-----------------|--------------- |------------|------------- |--------|
| [Current month] |        $28,400 |        --  |          --  |    320 |
| [3 months ago]  |        $29,800 |      -4.7% |      -1.57%  |    295 |
| [6 months ago]  |        $31,200 |      -9.0% |      -1.50%  |    310 |

Classification:    MODERATE DEPRECIATION
Monthly Rate:      -1.5% (at current pace)
Annualized Rate:   -18.0% (projection — assumes linear, see caveats)
Weekly Value Loss:  ~$107

-- Auction Timing Recommendation ---------------------------------------------------
"Standard 2-week consignment pipeline is acceptable. Expected value loss during
pipeline: ~$214. No urgency premium needed on reserves."

Output Template — Market Rankings

-- Fastest/Slowest Depreciators: [State] — [Month Year] ---------------------------

FASTEST DEPRECIATORS (consign immediately):
| Rank | Make/Model          | Monthly Rate | 3mo Change | Volume | Urgency          |
|------|---------------------|------------- |------------|--------|------------------|
|    1 | [Make] [Model]      |      -2.8%   |      -8.4% |    180 | CONSIGN NOW      |
|    2 | [Make] [Model]      |      -2.3%   |      -6.9% |    220 | CONSIGN NOW      |
| ...  | ...                 |          ... |        ... |    ... | ...              |

SLOWEST DEPRECIATORS (strong residuals, can hold):
| Rank | Make/Model          | Monthly Rate | 3mo Change | Volume | Urgency          |
|------|---------------------|------------- |------------|--------|------------------|
|    1 | [Make] [Model]      |      -0.3%   |      -0.9% |    410 | NO RUSH          |
| ...  | ...                 |          ... |        ... |    ... | ...              |

-- Segment Summary -----------------------------------------------------------------
| Segment  | Monthly Rate | 3mo Change | Seasonal Flag |
|----------|------------- |------------|---------------|
| SUV      |      -1.2%   |      -3.6% |               |
| Pickup   |      -0.8%   |      -2.4% | Winter demand |
| ...      |          ... |        ... | ...           |

-- Brand Residual Tiers -----------------------------------------------------------
Tier 1 (> 98%): [brands]
Tier 2 (95-98%): [brands]
Tier 3 (90-95%): [brands]
Tier 4 (< 90%): [brands]

Self-Check (before presenting to user)

  1. Date periods are complete calendar months — No partial months, no future months. The "current period" is the last fully complete month, not the current calendar month.
  2. Volume thresholds enforced — Single-model curves require 50+ sold per period. Market rankings require 50+ sold in BOTH periods. Brand tiers require 100+ sold in both periods. Models below thresholds are excluded, not shown with asterisks.
  3. Monthly rate sign is correct — Depreciation should produce a NEGATIVE monthly rate. A positive rate means appreciation (prices going up). If most models show appreciation, note this is unusual and may indicate a supply shortage or seasonal effect.
  4. Annualized rate caveat is present — Every annualized rate must include the disclaimer "at current pace" or "assumes linear progression." Never present annualized rates as guaranteed outcomes.
  5. Seasonal flags are applied — If the analysis spans Oct-Mar, flag 4WD/AWD and truck segments. If Apr-Sep, flag convertibles and sports cars. The Seasonal Flag column should never be entirely empty.
  6. US-only confirmation — If the profile country is UK, the skill should have exited with "Depreciation tracking is available for US markets only." Verify no UK data was accidentally processed.
Install via CLI
npx skills add https://github.com/MarketcheckHub/marketcheck-cowork-plugin --skill depreciation-tracker
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