Put a short digital form in front of the customer: vehicle details, the problem in their own words, then follow-up questions that change with the symptom. Have AI turn the answers into a technician note that reports symptoms, never causes, and send the customer a read-back to confirm before any work starts.
The summary is only as good as the questions behind it. "Weird noise, started last week" gives a model nothing to summarise and a technician nothing to test, and an AI will happily fill the gap with a guess. The form's job is to collect the facts. The model's job is to tidy them and say what is still missing.
What a complaint line needs before AI touches it
A common repair-order layout is the three Cs: concern (some shops write complaint), cause and correction. The intake form feeds only the first. Wrench's technician-written guide to the three Cs describes a concern as a symptom, not the customer's guess at the cause or a repair they have already decided on, and says a useful one gives context: what kind of symptom it is (something seen, heard, smelt or felt), where it seems to come from, when it happens, how often, and whether the engine is cold or warm.
Here is the gap in practice. A customer writes "Car feels funny, sometimes". Nothing in that line can be tested. The same customer, asked six short questions, can produce: "Steering wheel shakes at about 100 km/h (60 mph), every time, only once the engine is warm, started two weeks ago, no warning lights." The second line lets a technician plan the road test before the car reaches a bay. Getting from the first to the second is a form-design job. The AI's part comes afterwards, and it cannot invent what nobody asked.
One rule keeps the later steps traceable: one concern per line. A customer who reports a squeal, a warm A/C and a dim headlight has three concerns, and each deserves its own cause and correction later. The summary prompt below numbers them for that reason.
Fourteen fields for the form, and what each one saves
Aim for a form a customer can finish on a phone in three or four minutes. Fourteen fields sounds like a lot, but six are required, most of the rest are single taps, and the follow-up questions in the next section appear only for the symptom the customer picked.
| # | Field | Answer type | What the technician gets from it |
|---|---|---|---|
| 1 | Vehicle: year, make, model | Three short fields or a dropdown | The right manuals, parts and known issues for this car |
| 2 | Mileage | Number | Context for wear, and whether a service is due anyway |
| 3 | Registration plate | Short text | Matches the form to the car on the lot |
| 4 | Is it safe to drive? | One choice: yes / yes but I am worried / no | Triggers the "please do not drive it, call us" message and the towing conversation |
| 5 | The problem in your own words | Long text, 600 characters, required | The customer's own wording, which the summary quotes |
| 6 | What matters most? | One choice, so it can branch: noise, vibration, warning light, smell or smoke, leak, starting or power, brakes or steering, heating, cooling or electrics, something else | Sends the customer to the right follow-up questions |
| 7 | When did it start? | Today / this week / this month / longer / always | Separates a sudden change from slow wear |
| 8 | How often? | Every time / most times / sometimes / once | An intermittent fault needs a different test plan |
| 9 | Is it getting worse? | Yes / no / comes and goes | Helps the writer set the queue order |
| 10 | Engine cold, warm or both? | One choice | Cold-only and warm-only symptoms are tested differently |
| 11 | Warning lights on now? | One choice plus an optional photo | A record of what the dash showed at drop-off |
| 12 | Recent events | Short text: work done, fuel stop, accident, kerb or pothole hit, jump start | The "it started after..." detail customers forget at the counter |
| 13 | Photo or short video | Optional upload | Evidence of a leak, a light or an intermittent noise |
| 14 | Best way and time to reach you | One choice plus a time | Fewer rounds of phone tag before approval |
Make fields 1, 3, 4, 5, 6 and 14 required and leave the rest optional, because every extra required field loses a few customers halfway through. Put field 4 early. If the customer answers "no", show a message in your shop's own words, such as "Please do not drive the car. Call us on [number] and we will arrange it", before they carry on.
Symptom branches: the follow-up questions for each type of complaint
Field 6 is a single-choice question because a form tool can use it to send each customer to the right section. Google's help page puts the same sentence under multiple-choice, checkbox and dropdown questions: "based on a responder's answers, you can send them to a certain section of the form." A single choice still keeps the route simple, because the customer answers one set of follow-ups instead of several stacked together, so ask for the most important symptom in field 6 and use a final "anything else?" text box for the rest. The follow-ups below are questions only. None of them names a cause.
| Symptom chosen | Follow-up questions |
|---|---|
| Noise | Which word fits best: squeal, grind, click or tick, knock or clunk, rattle, hum or whine, roar? Where does it seem to come from: front left, front right, rear, under the car, engine bay, dash? When: braking, accelerating, turning left, turning right, over bumps, at certain speeds, on a cold start, all the time? Does it stop when you release the brake or lift off the throttle? |
| Vibration | Where do you feel it: steering wheel, seat, brake pedal, floor, whole car? At what speed does it start and stop? Does it happen only when braking? Does it change when accelerating or coasting? |
| Warning light | Which light: pick from the pictures or give its colour and shape. Steady or flashing? Did anything happen just before it came on: a fuel stop, a wash, a jump start, a hit on the kerb? Does the car drive any differently? |
| Smell, smoke or leak | What does it smell like: burning, hot oil, sweet, fuel, burnt rubber, musty? Inside, outside or from the engine bay? Is there smoke, and what colour? Any fluid under the car: what colour and where? How often do you top up oil or coolant? |
| Starting or power | What happens when you turn the key or press start: nothing, clicks, cranks slowly, cranks but will not start? Does it matter whether the engine is cold or warm? When does it stall: idling, driving, stopping? Does power drop uphill, when accelerating or when towing? Did it start after refuelling? |
| Brakes or steering | Is the pedal soft, hard, sinking or long? Does the car pull to one side, and when? Is the steering heavy, loose or noisy at full turn? Any problem with the handbrake? |
| Heating, cooling or electrics | What is not working? All the time or sometimes? Is the temperature gauge moving? Any battery or charging light? Which windows, lights or locks are affected? |
Each branch adds three to five questions, so a customer who picks "noise" never sees the electrical questions. Ask your lead technician to rewrite these in the words your customers actually use. Where your form tool lets you attach pictures to answer options, a dashboard-light chart helps people who only know the colour of the symbol.
The summary prompt, with one complaint worked through
Store the instructions in a ChatGPT Project (or a Claude Project, where custom project instructions need a paid plan), so each car only needs the form answers pasted underneath. The prompt asks for a fixed layout, bans causes, and makes the model say "not stated" instead of guessing. The safety triggers in line 7 are an example list; your lead technician should write the real one.
You turn a customer's intake form into a note for the technician. You summarise what the customer reported. You do not diagnose.
INPUT: form answers, including the customer's own words and ticked options.
OUTPUT in this order, plain text, under 130 words:
1. CONCERNS: one numbered line per separate concern, in the customer's terms (symptom, not cause).
2. WHEN: conditions that bring it on (cold or warm engine, speed, braking, turning, load, A/C, weather).
3. WHERE: where the customer says it comes from.
4. SINCE AND HOW OFTEN: when it started and how often it happens.
5. WARNING LIGHTS: which, steady or flashing, or none reported.
6. RECENT EVENTS: work, accident, fuel stop, kerb hit, jump start, new parts.
7. SAFETY FLAG: YES or NO. YES if the customer mentions any of: grinding or scraping when braking; brake pedal soft, sinking or long; steering loose, heavy or pulling hard; smoke; fuel smell; flashing warning light; overheating; loss of power while driving; a leak that is getting bigger. Give the words that triggered it.
8. UNKNOWNS: up to four short questions the service writer should ask at the counter.
RULES
- Use only what the form says. Write 'not stated' for anything missing. Never guess.
- Never name a cause, a part or a repair. If the customer suggests one, write 'Customer suspects: ...'.
- Quote the customer's words for sounds and feelings.
- No prices, no time estimates, no advice to the customer.
- If answers contradict each other, list the conflict under UNKNOWNS.
- Replace any phone number, email address or name with [removed].A customer's answers, as they might arrive (illustrative):
Vehicle: mid-size SUV, 82,400 on the clock
Safe to drive: Yes, but I am worried
Problem: makes a weird noise when i brake and kinda shaky at speed, started after i hit a pothole last week. brakes were done like a year ago??
Main symptom: Noise
Noise type: grinding
Seems to come from: front left
When: only when braking, stops when I let go of the pedal
Since: this week
Warning lights: none
Cold or warm: both
Recent events: pothole last week
Contact: text, after 5 pmThe summary the prompt produces from those answers:
CONCERNS:
1. "Weird noise" when braking, described as grinding, front left.
2. "Kinda shaky at speed", not stated where it is felt or at what speed.
WHEN: Noise only while braking, stops when the pedal is released. Shake at speed, not stated whether during braking.
WHERE: Noise front left. Shake location not stated.
SINCE AND HOW OFTEN: About a week, after hitting a pothole. Frequency not stated.
WARNING LIGHTS: None reported.
RECENT EVENTS: Pothole impact last week. Brake work about a year ago (customer unsure).
SAFETY FLAG: YES. "Grinding" when braking; customer says drivable but worried.
UNKNOWNS: Where is the shake felt, and at what speed? Does it also shake while braking? Does the car pull to one side? Which shop did the brake work?A thinner first version of the prompt, one that asked only for a short summary, tends to produce a note like this one (illustrative). It opens with "Likely worn brake pads and a wheel balance issue after pothole impact", which is a diagnosis nobody asked for and which a rushed technician might believe. It writes the shake as "constant", which the customer never said. And it drops the pothole, the one detail that points a technician at suspension. Each of those became a rule above: no causes, "not stated" for gaps, and RECENT EVENTS as its own line. That is the pattern to expect. Every fix goes into the prompt, not into hand-editing each note.
Three more complaints, and what the summary does with them
| What the customer wrote | What the summary says | What I would fix |
|---|---|---|
| "Check engine light is on and it runs rough since I filled up at a different station" | Concerns: 1. Check engine light on. 2. "Runs rough". Customer suspects: fuel from the last fill-up. Light steady or flashing: not stated | Nothing in the note. Keeping the customer's theory labelled as theirs is the point, because the technician still diagnoses. If the answers do not say steady or flashing, the form needs that as a required choice |
| "A/C blows warm sometimes" | Concern: A/C air warm intermittently. Unknowns: how long it stays warm, whether it happens in traffic or at speed, whether the temperature gauge moves, whether the engine is cold or warm when it starts | A good note, but the questions should have been on the form. Add them to the heating, cooling and electrics branch so the writer is not asking them at the counter |
| "Car feels funny" | Concern: customer says the car "feels funny". No further detail given. Unknowns: what feels funny, when, where, since when | The form failed, not the model. Make the follow-up branch required, so this answer cannot be submitted alone |
A fourth case catches shops with a mixed customer base. A customer writes the problem in another language. Add one line to the prompt: "If the customer writes in another language, give the summary in English and put the original wording in brackets." Machine translation can mangle sounds and feelings, so the bracketed original lets a colleague who speaks the language check it. Keep the raw answers attached to the repair order in every case.
Customer sign-off: read it back before any work starts
The read-back gives you a dated record of what the customer said, and it lets them correct "front left" to "front right" before anyone starts a road test. It also catches the case where the form and the customer's real worry differ. Run a second, shorter prompt on the same answers:
Rewrite the CONCERNS, WHEN and WHERE lines as a short message to the customer, under 70 words. Start: 'Here is what we have noted about your [vehicle]:'. Use their own words for sounds and feelings. Do not add a cause, a price or advice. End: 'Reply YES if that is right, or tell us what to change before we start.'Here is what we have noted about your SUV: a grinding noise from the front left, only when braking, which stops when you let go of the pedal. A shake at speed, which you have not placed yet. It started about a week ago, after a pothole. Reply YES if that is right, or tell us what to change before we start. [your name]
Check the message against the raw answers before it goes out, and have the writer send it, not an automation, until the summaries have run clean for a few weeks. At the counter, show the same text on a tablet with a tick box labelled "This matches what I told you". Then add a second block of fixed wording that the AI never touches, because it is an authorisation. Here is a draft for your adviser to check against the rules that apply to your shop:
I confirm the description above matches what I told you. I authorise [shop name] to inspect and diagnose the concerns listed, up to [number] hours of diagnostic time ($[amount]). No repair work will start until I have approved a written estimate. You may contact me by [method] at [time].
If you charge for diagnosis, show the amount on the form before the customer submits it. A fee they first meet at the counter turns into an argument. The estimate approval is a separate step, covered in the tutorial on building an auto repair price estimate template with ChatGPT, and the sign-off here should never be read as approval to repair. Decide in advance what happens when a customer does not reply to the read-back: the usual choice is that the writer phones before the car goes into the queue.
Where to build the form, and what each choice costs
| Option | What it gives you | The catch |
|---|---|---|
| Google Forms | Sections, with branching to a section based on an answer; responses can feed a Google Sheet; works well if your team is already on Google accounts | Google's help page says responders must sign in to a Google Account to answer a file-upload question, uploads land in a Drive folder owned by the form owner, and file upload is unavailable if the form is in a shared drive. For photos and video, ask customers to text them instead |
| Jotform | A form builder with a library of auto repair templates, among them an Auto Repair Job Form and a Vehicle Repair Form; its free Starter plan allows 5 forms, 100 submissions a month and 100 MB of storage | At 12 intakes a day over 22 working days you need about 264 submissions a month, so the free plan runs out in the second week. Paid plans were $39 a month, or $34 a month billed yearly, for Bronze on its pricing page in October 2026. The comparison of Tally Forms and Jotform covers the alternatives |
| Your shop-management system's online form | No new tool, and the answers can land straight on the repair order | Check it has a free-text concern field, questions that change with the answer, and a way to export or notify. If not, use one of the tools above and paste the summary in |
| Paper plus a tablet | The fallback for walk-ins | Someone must retype it; use the same fields so the summary step still works |
Three small things raise completion. Print a QR code that opens the form on the key-drop envelope and on a card at the counter, so a customer leaving keys after hours answers in the car park. Text the link when the appointment is booked. And for customers who ring instead, let the writer read the same questions aloud and type the answers. For calls nobody can answer, see what an AI receptionist for a mechanic costs against missed calls.
Paste it or wire it: getting answers to the AI
Start by pasting. Open the linked response sheet, copy the complaint columns without the name or phone number, paste them under the prompt in the Project, check the note and drop it into the repair order. That takes about 40 seconds a car, or eight minutes a day at 12 cars, and you will learn which prompt rules matter before you automate anything.
To automate, a typical chain is: a new row in the response sheet triggers a Zap, an AI step writes the summary, and an email or message posts it to the service writer. Zapier's Free plan allows two-step Zaps only, so a three-step chain like this needs a paid plan, and its AI step is available from Professional upwards. Triggers do not count as tasks, but each action does, and an AI step uses 1, 3 or 5 tasks depending on the model tier (1 with your own API key). At 264 intakes a month, the AI step plus an email is 528 tasks at the low end, 1,056 at the middle tier and 1,584 at the top, against 750 tasks on Professional, which lists at $29.99 a month billed monthly or $19.99 billed yearly. So use your own API key or the smallest model tier, or keep pasting.
With an API key, the model itself is cheap. API use is billed per token on the developer platform, separate from any ChatGPT or Claude subscription. A summary run is roughly 600 words in and 200 words out, and at a mid-priced model's list price of $2 per million input tokens and $10 per million output tokens (Claude Sonnet 5, checked September 2026) that is under half a cent a car, about a dollar for 264 cars. Model names and prices change, so check the current price page before you budget.
Keep names and numbers out of the prompt
An intake form collects personal details, and the summary step only needs the complaint. Send the model the complaint columns, keyed by repair-order number, and leave the name, phone number and plate behind. Customers still type phone numbers into the free-text box ("call my husband on..."), which is why the prompt replaces any number, email address or name with [removed].
Use a plan where business content is not used for training by default, such as ChatGPT Business, Claude Team or Gemini in Google Workspace. Both ChatGPT Business and Claude Team need at least two seats, so a one-person front desk either pays for two or uses an individual plan with the model-training switch turned off in privacy settings. Then add a line under the form: "We tidy your answers into a note with an AI tool, and our staff read every note." If you serve customers in the EU, or you store photos and plates for longer than a repair takes, ask a data-protection adviser what else applies.
Ten old complaints as a test, and what failing looks like
Before the first live customer, pull ten real complaints from old repair orders, remove the names, and run them through the prompt. Choose them to break it.
| Test complaint | It passes if |
|---|---|
| Two vague ones ("feels funny", "not right") | The note says so plainly and lists questions, with no invented detail |
| Two where the customer names a part ("I think it's the alternator") | The theory appears only as "Customer suspects: ..." |
| Two with several concerns in one paragraph | Each concern gets its own numbered line |
| One intermittent fault | "How often" and "when" are marked not stated if the customer did not say |
| One that mentions brakes going soft | SAFETY FLAG is YES with the customer's words quoted |
| One written in another language | An English summary with the original in brackets |
| One that contradicts itself ("only cold", then "only after a long drive") | The conflict appears under UNKNOWNS, not smoothed over |
Count nine clean out of ten as the bar for going live, and fix every failure in the prompt, not by editing the note. Re-run all ten after any change, because a stricter rule in one place can loosen another. Repeat the test whenever you change the model or the form's wording.
What it saves in a three-bay shop: a quick sum
These numbers are made up, so replace them with a fortnight of your own timing. Take a shop writing 12 repair orders a day over 22 working days. Today the writer spends six minutes per car taking the complaint at the counter, and technicians have to go back to the customer on three cars in ten, about eight minutes each. With the form, the writer spends two minutes reviewing the summary and the read-back, and technician re-asks fall to one car in ten.
- Writer: 12 cars × 4 minutes saved = 48 minutes a day.
- Technician re-asks: 3.6 a day falls to 1.2, saving 2.4 × 8 minutes = 19.2 minutes a day.
- Minus the pasting: 12 × 40 seconds = 8 minutes a day.
- Net: about 59 minutes a day, or around 22 hours over the 22-day month.
The bigger number is harder to measure: the repeat visit. Suppose, again as an assumption, that one car in 60 comes back because the first diagnosis chased the wrong symptom, and each return costs 1.5 hours of technician time at a $135 labour rate that you never bill. That is 4.4 cars a month, about $890 of unbilled time. If clearer complaints halve it, the form is worth about $445 a month before counting the customer who does not return a third time. Put your own comeback count from the last three months into that sum before you believe it.
Order of work: write the fourteen fields (one hour), add the branches (one hour), save the two prompts and run the ten-complaint test (one hour), then use it for a fortnight by hand. When the summaries need no edits, think about automating. For the shop-wide procedures that sit around the form, such as vehicle handover, the tutorial on AI-drafted intake, handover and quality steps picks up where this ends, and ChatGPT for car mechanics explains why the diagnosis itself stays with your technicians. Once the car is in, repair updates that customers appreciate keep the conversation going.
Questions shops ask about intake forms and AI summaries
What if a customer will not fill in a form?
Use the same questions at the counter or on the phone and let the service writer type the answers into the same form. The summary step works identically, because it only sees the answers. For a voicemail, paste the transcript under the prompt and add a line saying the source was a voicemail, so the summary does not claim detail the caller never gave.
Should the customer see the AI summary?
Only the read-back version, in plain sentences with no field labels, and only after a staff member has checked it against the original answers. The technician note, with its safety flag and list of unknowns, is an internal document. Keep the customer's raw answers on the repair order beside whichever version you send.
Do I have to tell customers an AI tool is involved?
A one-line note under the form is easy and costs nothing: answers are tidied into a note by an AI tool and checked by staff. Whether your data-protection rules require more depends on where your customers are and what you store, so ask a qualified adviser, especially if the form collects photos, plates or contact details.
Further reads
- Best AI for Mechanic Diagnosis: Fault Codes, Manuals and Limits — Where AI helps with fault codes and manuals, and where it stops
- Following Up Unapproved Repair Estimates With AI — Chasing estimates the customer has not yet approved
- Phone Repair Intake Form: Turn Customer Messages Into Tickets With AI — The same idea for a phone repair counter
- Should a Small Auto Repair Shop Use AI? A Decision Checklist — Whether a small shop should use AI at all, and for what
- AI Service Reminders That Bring Garage Customers Back — Bring customers back after the repair is done
- Turning On-Site Voice Notes Into Job Sheets and Quotes With AI — Turn a technician's spoken notes into a clean job sheet
- Best AI for Auto Mechanics: Estimates, Parts Research and Messages — ChatGPT, Claude or Gemini for a garage: which one for estimate wording, parts research and customer texts, and the supplier-catalogue checks that stay manual.
- Body Shop Quality Control Checklist: Post-Repair Checks With AI — Filled-in post-repair checks for panels, paint, electrics and photos, with sign-off rules and prompts that turn your own comebacks into a checklist.
- Repair Shop Software for Bike Shops: Service Bookings and Quotes With AI — Service tiers, intake questions, a spring-rush booking cap worked out in bench hours, and a quote prompt that only uses your own price list.
- AI for Body Shops: Insurer Paperwork, Supplements and Job Notes — Where AI helps a collision repair shop with paperwork: photo captions, supplement requests, daily job notes and repair summaries, and what a person must sign.
- AI for Automotive Repair: What Phone Answering Costs a Small Shop — Smith.ai, Dialzara, Goodcall, Rosie and AutoLeap priced at 100 and 300 calls a month for a small repair shop, with a booking and quote script.
- Mobile Mechanic Software for One Van: Jobber vs ServiceM8 With AI — One van, about 60 jobs a month: what Jobber and ServiceM8 charge, how each handles vehicles and parts, and what their AI does for a mechanic.
- AI Tools and AI Development: The Complete 2026 Guide — the AI hub, including every tutorial in the AI-for-business series.
Sources: Google Docs Editors Help, 'Choose a type of question for your form'; Jotform pricing page (Starter plan limits and USD prices) and template library; Wrench's technician-written guide to the three Cs; Zapier plan and task-counting pages (September 2026); Anthropic API list prices (September 2026).