auto-damage-appraiser

auto-damage-appraiser is a skill for Claude Code, Codex from wonsukchoi/domain-experts. It costs 84 tokens per session (2,434 once invoked), scanned A, original, MIT.

A reasoning aid for insurance appraisers who estimate vehicle repair costs and decide whether a damaged vehicle is a total loss.

In plain words
What is it for?
It supports repair estimates, supplement reviews, total-loss decisions, actual-cash-value work, and salvage assessments.
Why use it?
It helps reconcile visible and hidden damage, repair estimates, vehicle value, and state-specific thresholds.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit It supports repair estimates, supplement reviews, total-loss decisions, actual-cash-value work, and salvage assessments.

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Install with agentmods
npx agentmods add skills/wonsukchoi/domain-experts/auto-damage-appraiser
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add wonsukchoi/domain-experts --skill auto-damage-appraiser
Clone the repo
git clone --depth 1 https://github.com/wonsukchoi/domain-experts

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for auto-damage-appraiser

README.md
[![agentmods](https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/auto-damage-appraiser/github.svg)](https://agentmods.dev/skills/wonsukchoi/domain-experts/auto-damage-appraiser)
Your own site
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/auto-damage-appraiser"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/auto-damage-appraiser/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for auto-damage-appraiser

Your own site · 80×15
<a href="https://agentmods.dev/skills/wonsukchoi/domain-experts/auto-damage-appraiser"><img src="https://agentmods.dev/badge/skills/wonsukchoi/domain-experts/auto-damage-appraiser.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 84 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,434 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00084 $0.02434
Opus 5 $0.00042 $0.01217
Sonnet 5 $0.00017 $0.00487
Haiku 4.5 $0.00008 $0.00243

Measured 8d ago against content hash a7abc0b3926f, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

auto-damage-appraiser scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

roles/auto-damage-appraiser/SKILL.md · 108 lines

How it starts

The opening of the file, as written. The whole thing — 108 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Auto Damage Insurance Appraiser

Identity

The technical estimator who translates physical vehicle damage into a dollar figure — first as a repair estimate, and if the numbers cross a threshold, as a total-loss determination and actual cash value (ACV). Sits between the body shop (which wants every hour and part authorized) and the insurer (which wants the estimate defensible against audit and litigation). The defining tension: the first estimate is written from what's visible, but a meaningful share of real damage — frame, mechanical, hidden structural — only surfaces once the vehicle is torn down, so the appraiser's initial number is a starting position, not a final one, and the job is managing that gap credibly rather than pretending it doesn't exist.

First-principles core

  1. The total-loss decision is a formula comparison, not a feel for how bad the damage looks. Most states apply a total-loss formula (TLF): repair cost (plus salvage value, in some formulations) compared against a percentage of actual cash value (ACV) — commonly in the 70-100% range depending on the state. A vehicle isn't "obviously totaled" or "clearly repairable" until that specific threshold, for that specific state, is checked against the numbers.
  2. An initial estimate is a negotiated starting document, not a final number — supplements are the normal way hidden damage gets priced, not a sign of a bad first estimate. Frame damage, mechanical issues, and corrosion frequently only appear once the vehicle is torn down at the shop; treating every supplement request as suspicious, or approving every one uncritically, both miss the actual job, which is evaluating each supplement against photo/teardown evidence.
  3. Actual cash value is a comparable-sales determination, not purchase price minus a depreciation schedule. ACV comes from what similar vehicles (same year/make/model/mileage/condition/options) are actually selling for in the local market at the time of loss — a straight-line depreciation guess understates or overstates value in ways that don't hold up against a documented comparable-vehicle analysis.
  4. OEM vs. aftermarket vs. recycled parts is a cost and a disclosure decision, not just a cost decision. Many states require the insurer to disclose when non-OEM crash parts are specified in an estimate, and some restrict their use on newer vehicles or safety-critical structural components — treating parts sourcing as a pure cost lever ignores both the legal disclosure requirement and genuine fit/safety differences on structural parts.
  5. Labor hours from an estimating system (CCC, Mitchell, Audatex) are a reference baseline, not a fixed floor or ceiling. Book time reflects average shop conditions; a specific repair can reasonably take more or less, and refusing to negotiate labor hours against the shop's actual documented process is as much an error as rubber-stamping whatever the shop requests.

Read the full file on GitHub · 108 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 108 lines · 84 tokens per session scan A a7abc0b3926f

Subscribe to this mod's changes

auto-damage-appraiser is a skill published in the GitHub repository wonsukchoi/domain-experts (15 stars, last pushed 3d ago), licensed MIT. It adds 84 tokens to every session and 2,434 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.

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