Claims Valuation — Insurance Total-Loss & Settlement Pricing

SkillDev tools

Total-loss determination and settlement pricing. Triggers: "total loss valuation", "claims value", "settlement offer", "salvage estimate", "insurance claim pricing", "total loss threshold", "what's the claim worth", "settlement range", "pre-loss value", "diminished value", "total loss determination", insurance claim vehicle valuation, total-loss determination, settlement pricing, or salvage value estimation.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Claims Valuation — Insurance Total-Loss & Settlement Pricing skill

What this skill tells your AI

The instructions your AI receives, as published by fdu-ins/insurance-skills in Skills/claims-valuation/SKILL.md and read by ahel’s review.

Insurer Profile (Load First)

  1. Read the marketcheck-profile.md project memory file.
  2. If exists, extract: location (zip/state), preferences (total_loss_threshold_pct, default_comp_radius).
  3. If not found: ask for ZIP code to proceed. Suggest running /onboarding first.
  4. Country check: US-only. UK not supported (requires predict_price and sold data).
  5. 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:

  1. mcp__marketcheck__predict_price_with_comparables with VIN, miles, ZIP, dealer_type=franchise → Franchise retail FMV
  2. mcp__marketcheck__predict_price_with_comparables with VIN, miles, ZIP, dealer_type=independent → Independent retail FMV
  3. If vehicle was CPO (is_certified in history or user states): additional call with is_certified=trueExtract 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=20Extract 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=trueExtract 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):

  1. Accept list of VINs with miles and condition
  2. Use the insurer:portfolio-scanner agent to process each VIN
  3. Present summary: total claim exposure, average FMV, total-loss count, salvage estimate
  4. 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:

  1. Get pre-loss FMV (same as Steps 1-2 above)
  2. Estimate post-repair diminished value: typically 10-25% of FMV depending on repair severity
  3. 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.

Signals

GitHub stars
73
Forks
19
Last commit
Jul 2026
Advanced
Catalog kind
skill
Gateway key
claims-valuation
Source
github.com/fdu-ins/insurance-skills