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.
From auction-housenpx claudepluginhub marketcheckhub/marketcheck-cowork-plugin --plugin auction-houseThis skill uses the workspace's default tool permissions.
Provides UI/UX resources: 50+ styles, color palettes, font pairings, guidelines, charts for web/mobile across React, Next.js, Vue, Svelte, Tailwind, React Native, Flutter. Aids planning, building, reviewing interfaces.
Fetches up-to-date documentation from Context7 for libraries and frameworks like React, Next.js, Prisma. Use for setup questions, API references, and code examples.
Calculates TAM/SAM/SOM using top-down, bottom-up, and value theory methodologies for market sizing, revenue estimation, and startup validation.
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: 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]".
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.
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."ranking_dimensions=make,model,trim to isolate trim-level trends. Flag any model where trim composition changed significantly between periods.sold_count > 50 for both periods. Below this threshold, report "INSUFFICIENT VOLUME — trend unreliable" rather than computing a rate.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 |
Use this when the user asks "depreciation curve for [make/model]" or "how fast is [model] losing value."
Get current period pricing — Call mcp__marketcheck__get_sold_summary with make=[make], model=[model], state=[XX], inventory_type=Used, 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.
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.
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.
Calculate depreciation metrics:
Auction timing recommendation:
Use this when the user asks "which cars are losing value fastest" or "depreciation rankings."
Current period — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, 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.
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.
Calculate and rank — For models present in BOTH periods with 50+ sold in EACH period:
Segment-level view — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, 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.
Current period by brand — Call mcp__marketcheck__get_sold_summary with state=[XX], inventory_type=Used, 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.
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.
Calculate 6-month retention % per brand = (current_avg / 6mo_ago_avg) x 100. Only include brands with 100+ sold in both periods.
Tier assignment: Tier 1 (> 98% retention), Tier 2 (95-98%), Tier 3 (90-95%), Tier 4 (< 90%).
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.
-- 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."
-- 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]