Claims Valuation — Insurance Total-Loss & Settlement Pricing
Insurer Profile (Load First)
- Read the
marketcheck-profile.md project memory file.
- If exists, extract: location (zip/state), preferences (total_loss_threshold_pct, default_comp_radius).
- If not found: ask for ZIP code to proceed. Suggest running
/onboarding first.
- Country check: US-only. UK not supported (requires predict_price and sold data).
- Confirm: "Using profile: [user.name], [ZIP], [State]"
User Context
The primary user is an insurance adjuster or total-loss specialist who needs a defensible, comparable-backed fair market value (FMV) to determine if a vehicle is a total loss and, if so, what the settlement offer should be. The valuation must be supportable in dispute resolution.
Workflow: Total-Loss Determination & Settlement
Step 1 — Vehicle identification
Collect from user:
- VIN (required)
- Current odometer reading (required)
- Pre-loss condition: Clean, Average, Rough (required)
- Date of loss (optional, defaults to today)
- Any pre-existing damage or modifications
Call mcp__marketcheck__decode_vin_neovin with the VIN to get exact specs: year, make, model, trim, body type, drivetrain, engine, transmission, original MSRP.
→ Extract only: year, make, model, trim, body_type, drivetrain, engine, transmission, MSRP. Discard full response.
Step 2 — Fair Market Value (FMV) determination
Make THREE pricing calls:
mcp__marketcheck__predict_price_with_comparables with VIN, miles, ZIP, dealer_type=franchise → Franchise retail FMV
mcp__marketcheck__predict_price_with_comparables with VIN, miles, ZIP, dealer_type=independent → Independent retail FMV
- If vehicle was CPO (
is_certified in history or user states): additional call with is_certified=true
→ Extract only: predicted_price, comp count per call. Discard full response.
Pre-loss FMV = average of franchise and independent predicted prices, adjusted by condition:
- Clean: use the higher of the two predictions
- Average: use the average
- Rough: use the lower, minus 5%
Step 3 — Comparable evidence (wide radius)
Pull active retail comparables:
mcp__marketcheck__search_active_cars with YMMT, ZIP, radius=100, miles_range=<odo-15000>-<odo+15000>, car_type=used, sort_by=price, sort_order=asc, rows=20
→ Extract only: VIN, price, miles, dealer_name, distance, dom per listing. Discard full response.
Pull sold transaction evidence (strongest for disputes):
mcp__marketcheck__search_past_90_days with same YMMT filters, sold=true
→ Extract only: VIN, sold_price, miles, dealer_name, sale_date per listing. Discard full response.
Step 4 — Total-loss determination
Calculate:
- Repair cost threshold = FMV x total_loss_threshold_pct (default 75%)
- If estimated repair cost > threshold → TOTAL LOSS
- If not provided, just present the threshold: "This vehicle is a total loss if repair costs exceed $XX,XXX (75% of FMV)"
Step 5 — Settlement range
Calculate three tiers:
- Low settlement = 25th percentile of sold transaction prices (condition-adjusted)
- Mid settlement = Pre-loss FMV from Step 2
- High settlement = 75th percentile of sold transaction prices
Step 6 — Salvage value estimate
Salvage value is typically 15-25% of pre-loss FMV depending on damage severity:
- Minor (cosmetic): 25% of FMV
- Moderate (mechanical): 20% of FMV
- Severe (structural/flood): 15% of FMV
- If user provides actual salvage bid, use that instead
Net claim cost = Settlement offer - Salvage value
Output
Present: vehicle ID summary, pre-loss FMV table (franchise/independent/condition-adjusted), total-loss threshold and determination, settlement range (low/mid/high), salvage estimate and net claim cost, comparable evidence tables (active + sold with VIN/price/miles/dealer), methodology notes and caveats.
Workflow: Batch Claims Processing
For multiple VINs (e.g., hail damage event, flood):
- Accept list of VINs with miles and condition
- Use the
insurer:portfolio-scanner agent to process each VIN
- Present summary: total claim exposure, average FMV, total-loss count, salvage estimate
- Ranked table of all vehicles with FMV and settlement recommendation
Workflow: Diminished Value
For vehicles that were repaired (not total-loss) and the claimant wants diminished value:
- Get pre-loss FMV (same as Steps 1-2 above)
- Estimate post-repair diminished value: typically 10-25% of FMV depending on repair severity
- Show: "Pre-loss FMV: $XX,XXX → Post-repair diminished value: $X,XXX-$X,XXX"
Important Notes
- US-only: Requires
predict_price_with_comparables and search_past_90_days.
- Always cite specific comparable VINs — adjusters need to defend valuations.
- Sold transaction data is the strongest evidence in settlement disputes.
- The 75% total-loss threshold is a common default — actual thresholds vary by state and insurer. Use profile value if available.
- For disputed settlements, recommend expanding the search radius to 150-200 miles and including older sold data.
1---2name: claims-valuation3description: >4 Total-loss determination and settlement pricing. Triggers: "total loss valuation",5 "claims value", "settlement offer", "salvage estimate", "insurance claim pricing",6 "total loss threshold", "what's the claim worth", "settlement range",7 "pre-loss value", "diminished value", "total loss determination",8 insurance claim vehicle valuation, total-loss determination,9 settlement pricing, or salvage value estimation.10version: 0.1.011---1213# Claims Valuation — Insurance Total-Loss & Settlement Pricing1415## Insurer Profile (Load First)16171. Read the `marketcheck-profile.md` project memory file.182. If exists, extract: location (zip/state), preferences (total_loss_threshold_pct, default_comp_radius).193. If not found: ask for ZIP code to proceed. Suggest running `/onboarding` first.204. **Country check:** US-only. UK not supported (requires predict_price and sold data).215. Confirm: "Using profile: **[user.name]**, [ZIP], [State]"2223## User Context2425The primary user is an **insurance adjuster** or **total-loss specialist** who needs a defensible, comparable-backed fair market value (FMV) to determine if a vehicle is a total loss and, if so, what the settlement offer should be. The valuation must be supportable in dispute resolution.2627## Workflow: Total-Loss Determination & Settlement2829### Step 1 — Vehicle identification3031Collect from user:32- VIN (required)33- Current odometer reading (required)34- Pre-loss condition: Clean, Average, Rough (required)35- Date of loss (optional, defaults to today)36- Any pre-existing damage or modifications3738Call `mcp__marketcheck__decode_vin_neovin` with the VIN to get exact specs: year, make, model, trim, body type, drivetrain, engine, transmission, original MSRP.39→ **Extract only**: year, make, model, trim, body_type, drivetrain, engine, transmission, MSRP. Discard full response.4041### Step 2 — Fair Market Value (FMV) determination4243Make THREE pricing calls:441. `mcp__marketcheck__predict_price_with_comparables` with VIN, miles, ZIP, `dealer_type=franchise` → Franchise retail FMV452. `mcp__marketcheck__predict_price_with_comparables` with VIN, miles, ZIP, `dealer_type=independent` → Independent retail FMV463. If vehicle was CPO (`is_certified` in history or user states): additional call with `is_certified=true`47→ **Extract only**: predicted_price, comp count per call. Discard full response.4849**Pre-loss FMV** = average of franchise and independent predicted prices, adjusted by condition:50- Clean: use the higher of the two predictions51- Average: use the average52- Rough: use the lower, minus 5%5354### Step 3 — Comparable evidence (wide radius)5556Pull active retail comparables:57- `mcp__marketcheck__search_active_cars` with YMMT, ZIP, `radius=100`, `miles_range=<odo-15000>-<odo+15000>`, `car_type=used`, `sort_by=price`, `sort_order=asc`, `rows=20`58→ **Extract only**: VIN, price, miles, dealer_name, distance, dom per listing. Discard full response.5960Pull sold transaction evidence (strongest for disputes):61- `mcp__marketcheck__search_past_90_days` with same YMMT filters, `sold=true`62→ **Extract only**: VIN, sold_price, miles, dealer_name, sale_date per listing. Discard full response.6364### Step 4 — Total-loss determination6566Calculate:67- **Repair cost threshold** = FMV x total_loss_threshold_pct (default 75%)68- If estimated repair cost > threshold → **TOTAL LOSS**69- If not provided, just present the threshold: "This vehicle is a total loss if repair costs exceed $XX,XXX (75% of FMV)"7071### Step 5 — Settlement range7273Calculate three tiers:74- **Low settlement** = 25th percentile of sold transaction prices (condition-adjusted)75- **Mid settlement** = Pre-loss FMV from Step 276- **High settlement** = 75th percentile of sold transaction prices7778### Step 6 — Salvage value estimate7980Salvage value is typically 15-25% of pre-loss FMV depending on damage severity:81- Minor (cosmetic): 25% of FMV82- Moderate (mechanical): 20% of FMV83- Severe (structural/flood): 15% of FMV84- If user provides actual salvage bid, use that instead8586**Net claim cost** = Settlement offer - Salvage value8788## Output8990Present: vehicle ID summary, pre-loss FMV table (franchise/independent/condition-adjusted), total-loss threshold and determination, settlement range (low/mid/high), salvage estimate and net claim cost, comparable evidence tables (active + sold with VIN/price/miles/dealer), methodology notes and caveats.9192## Workflow: Batch Claims Processing9394For multiple VINs (e.g., hail damage event, flood):95961. Accept list of VINs with miles and condition972. Use the `insurer:portfolio-scanner` agent to process each VIN983. Present summary: total claim exposure, average FMV, total-loss count, salvage estimate994. Ranked table of all vehicles with FMV and settlement recommendation100101## Workflow: Diminished Value102103For vehicles that were repaired (not total-loss) and the claimant wants diminished value:1041051. Get pre-loss FMV (same as Steps 1-2 above)1062. Estimate post-repair diminished value: typically 10-25% of FMV depending on repair severity1073. Show: "Pre-loss FMV: $XX,XXX → Post-repair diminished value: $X,XXX-$X,XXX"108109## Important Notes110111- **US-only:** Requires `predict_price_with_comparables` and `search_past_90_days`.112- Always cite specific comparable VINs — adjusters need to defend valuations.113- Sold transaction data is the strongest evidence in settlement disputes.114- The 75% total-loss threshold is a common default — actual thresholds vary by state and insurer. Use profile value if available.115- For disputed settlements, recommend expanding the search radius to 150-200 miles and including older sold data.