Replace-vs-Repair Cost Advisor

The problem this kills

You already know the truck that keeps going back to the same machine. The compressor that's been "repaired" five times this year. The chiller that's older than the technician who services it. But when the customer asks "should I just replace it?", the honest answer is usually a shrug and a gut feeling - because nobody has ever added up what that asset has actually cost you to keep alive.

So the easy repair wins again. You quote the small fix, the customer says yes, and three weeks later you're back. The lifetime spend quietly sails past the price of a brand-new unit, and nobody notices until it's embarrassing.

This tool kills the shrug. It totals every dollar of labor and parts you've ever sunk into an asset, counts the visits, factors in age and downtime, and puts that next to what a replacement actually costs. Now when you say "replace it," you have a number - and the customer can see it too.

What you'll build

A private web app your team logs into. You import your repair history, asset ages, and replacement-cost estimates (from a CSV or Google Sheet - no integration required). The tool rolls everything up per asset, calculates a repair-to-replacement ratio, and scores each one repair-again or replace-now against a threshold you set (for example, "flag it when lifetime repairs pass 50% of a new unit").

Every replace-now advisory lands in a review queue. A manager reads the reasoning, adjusts if needed, and approves - and only approved advisories can be sent. Approved items go out as a clean, customer-ready summary email through Resend, and the whole list exports to CSV in the exact columns your system expects.

What's inside the Implementation Plan

The plan is a complete, paste-and-go runbook. You drop the whole thing into Claude Code and it builds the tool with you, step by step.

It opens by interviewing you about your business - how you track repairs today, what your asset IDs and SKUs look like, how you price labor and parts, what counts as "downtime cost," and where your replace threshold should sit. It reflects a short tailored spec back to you and waits for your thumbs-up before it builds anything. The result fits your shop, not a generic template.

From there it walks through the data model, the import, the scoring engine, the manager approval gate, the customer email, and the CSV export - each step ending with a ready-to-copy prompt.

The governance it includes (this is the point)

This isn't a spreadsheet macro - it's built like a real internal system:

• Login so only your team can open it.
• Row-level security so each organization only ever sees its own assets and customers.
• A full audit trail - who scored, who edited, who approved, and exactly when.
• A human-in-the-loop approval gate - the tool drafts the recommendation, a manager reviews and approves, and only then can it go to a customer. The AI never sends advice on its own.
• Duplicate guards so importing the same repair history twice can't double-count costs or process an asset twice.

Who it's for

Service managers who need to make the replace call and defend it. Account managers who have to deliver that call to a customer without sounding like they're upselling. Facilities teams sitting on aging equipment who want a straight, numbers-backed answer instead of a sales pitch.

You've got this - paste the first prompt and let the interview tailor the rest to your shop.