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Check whether a small check-in plan can handle a rush

Model a small queue minute by minute under explicit simplifying assumptions.

Illustrative resourceNot tool-testedOrganizers exploring a small synthetic check-in queue
What you’re working towards

A deterministic tabletop queue simulation from supplied arrivals and service times, with waiting/backlog shown and assumptions explicit. This is a written practice result, not a recorded AI run.

Download playbook .md

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Make a start

One step at a time.

3 steps

Start with the synthetic worked example or other non-sensitive inputs. Run one prompt at a time in your chosen AI tool. Replace any bracketed placeholders with the requested material, check each reply, and supply the source or earlier outputs that step needs. Paste them again if the tool lacks that context.

Start with the synthetic example, then adapt each prompt to your task.

01

Try the complete example

Open a text AI chat you already have permission to use. Paste the whole prompt below, from TASK through END INPUT, and send it. The input is source material; do not paste the illustrative Output as an answer to imitate. Expect A deterministic tabletop queue simulation from supplied arrivals and service times, with waiting/backlog shown and assumptions explicit. If you receive advice instead of the result, ask for the complete requested result from the supplied input.

Your starting prompt
TASK
Run the complete deterministic tabletop calculation in text for the baseline and separate slower-service case. Show token-level assignment, start/finish/wait, minute snapshots, maxima and totals. Preserve queue order and same-timestamp event rules. Explain the limits without turning the model into a staffing or safety recommendation.

INPUT
Complete fictional administrative tabletop model for eight adults. Two identical desks D1/D2 open at 09:00. Each serves one person at a time for exactly 1 minute, no interruptions. A1–A6 arrive together at 09:00, in that tie-break order; A7–A8 arrive at 09:02, in that order. One first-come-first-served queue. Finish events free desks before assigning the next waiting arrivals at the same timestamp; D1 receives the earlier queued token when both desks are free. Service intervals include start and exclude finish. No more arrivals.
Also calculate a separate sensitivity case where service takes 2 minutes per person, everything else unchanged. Show each person’s arrival/start/finish and start-wait, minute snapshots with in-service and waiting counts, final completion and maximum wait. This is not measured service data, a forecast, crowd-safety analysis or a staffing recommendation.
END INPUT
02

Check and correct

Use eight counters: never assign more than two simultaneously and never start a token before arrival or before its desk is free. Baseline completes 09:04 with waits 0,0,1,1,2,2,1,1; max 2 and sum 8. Slower case completes 09:08 with waits 0,0,2,2,4,4,4,4; max 4 and sum 20. Each snapshot’s serving + waiting + completed equals arrived so far. Compare with the unchanged source yourself. If anything differs, use the correction prompt, then recheck the complete replacement before saving.

Your starting prompt
Check the answer in this sample chat against the complete INPUT above. Use eight counters: never assign more than two simultaneously and never start a token before arrival or before its desk is free. Baseline completes 09:04 with waits 0,0,1,1,2,2,1,1; max 2 and sum 8. Slower case completes 09:08 with waits 0,0,2,2,4,4,4,4; max 4 and sum 20. Each snapshot’s serving + waiting + completed equals arrived so far. Quote each mismatch and its source, then return a complete corrected replacement. If source or answer is missing, ask for it. Do not describe a suggested human trial as completed.
03

Use your own source instead

Open a new chat and copy the prompt below. Replace every bracketed field with your own permitted non-sensitive material, or write unknown. Change the source names, counts, dates and rules together wherever they occur. Expect a complete result using those new values. Compare each source link and calculation with your new input, using the review instructions in this prompt. If a fact or rule is wrong, quote the mismatch and source and ask for a complete corrected replacement; keep essential unknowns held rather than borrowing the practice values.

Your starting prompt
Calculate a small deterministic check-in queue from my synthetic arrivals, desk count, opening/closing rules, service-time assumptions and queue/tie-break discipline. Ask for missing same-timestamp rules rather than choosing secretly. Return each token’s arrival, desk, service start/end and start-wait; provide time snapshots that conserve arrived = waiting + in service + completed. Derive totals, maximum wait and final completion from MY INPUT. Keep any sensitivity case separate and state exactly which assumption changes. Independently simulate with one counter per token and no more simultaneous services than desks. Hold infeasible closing constraints and avoid forecasts, staffing adequacy or safety claims.

MY INPUT
Small synthetic arrival batches: [replace with your source or rule]
Number of check-in desks: [replace with your source or rule]
Fixed service-time assumption: [replace with your source or rule]
Queue discipline: [replace with your source or rule]
Open/close times: [replace with your source or rule]
Allowed changes: [replace with your source or rule]

Use only MY INPUT for facts, quantities, names, dates and permissions. Ask for missing essential facts or conflicting rules instead of guessing. Creative invention is allowed only where this task and my boundaries permit it. Return the actual complete requested result, a separate unknown/hold list and the source-specific review described above. Do not reuse practice-example facts. Keep this a draft; do not publish, contact people, book, buy or change another service.
Optional: improve the result

Add a desk interruption

Optional, sample-only extension. Return to the practice chat, or paste this guide’s complete practice input and your checked answer into a new chat. Model a new explicit constraint rather than assuming staff are always free. This does not apply unchanged to your own source.

Advanced prompt
In a separate one-minute-service sample variant, D2 is unavailable from 09:01 inclusive to 09:03 exclusive. Its 09:00–09:01 service finishes normally. Keep all arrivals and queue rules. Recalculate the full token ledger and minute snapshots; show how the outage changes the maximum wait and final completion. If the complete sample input or answer is missing, ask me to paste it. Keep new variants separate from the original result.
Show, then try

See the shape of the result.

This input is synthetic. The output is a written illustration of the intended result, not a verified AI-tool run.

The starting point

Synthetic input
COMPLETE SYNTHETIC PRACTICE INPUT
Complete fictional administrative tabletop model for eight adults. Two identical desks D1/D2 open at 09:00. Each serves one person at a time for exactly 1 minute, no interruptions. A1–A6 arrive together at 09:00, in that tie-break order; A7–A8 arrive at 09:02, in that order. One first-come-first-served queue. Finish events free desks before assigning the next waiting arrivals at the same timestamp; D1 receives the earlier queued token when both desks are free. Service intervals include start and exclude finish. No more arrivals.
Also calculate a separate sensitivity case where service takes 2 minutes per person, everything else unchanged. Show each person’s arrival/start/finish and start-wait, minute snapshots with in-service and waiting counts, final completion and maximum wait. This is not measured service data, a forecast, crowd-safety analysis or a staffing recommendation.

Copies text only. For image or file tasks, use the source files named in the steps too.

Download source .txt

The intended result

Illustrative output
ILLUSTRATIVE AUTHORED OUTPUT
Written for this guide; no consumer AI execution or real-world trial is claimed.

BASELINE: ONE MINUTE PER PERSON
Token | Arrival | Desk | Start | Finish | Start-wait, minutes
A1 | 09:00 | D1 | 09:00 | 09:01 | 0
A2 | 09:00 | D2 | 09:00 | 09:01 | 0
A3 | 09:00 | D1 | 09:01 | 09:02 | 1
A4 | 09:00 | D2 | 09:01 | 09:02 | 1
A5 | 09:00 | D1 | 09:02 | 09:03 | 2
A6 | 09:00 | D2 | 09:02 | 09:03 | 2
A7 | 09:02 | D1 | 09:03 | 09:04 | 1
A8 | 09:02 | D2 | 09:03 | 09:04 | 1
Snapshots just after finishes, new arrivals and assignments at each minute:
09:00: serving A1/A2; waiting A3–A6 (4); completed 0.
09:01: serving A3/A4; waiting A5/A6 (2); completed 2.
09:02: serving A5/A6; waiting A7/A8 (2); completed 4.
09:03: serving A7/A8; waiting none (0); completed 6.
09:04: serving none; waiting none (0); completed 8.
Final completion 09:04; maximum start-wait 2 minutes. Total start-wait 8 minutes across eight people; mean 1 minute in this deterministic fixture. A5/A6 precede the later arrivals even though both are waiting at 09:02.

SEPARATE SENSITIVITY: TWO MINUTES PER PERSON
Token | Arrival | Desk | Start | Finish | Start-wait, minutes
A1 | 09:00 | D1 | 09:00 | 09:02 | 0
A2 | 09:00 | D2 | 09:00 | 09:02 | 0
A3 | 09:00 | D1 | 09:02 | 09:04 | 2
A4 | 09:00 | D2 | 09:02 | 09:04 | 2
A5 | 09:00 | D1 | 09:04 | 09:06 | 4
A6 | 09:00 | D2 | 09:04 | 09:06 | 4
A7 | 09:02 | D1 | 09:06 | 09:08 | 4
A8 | 09:02 | D2 | 09:06 | 09:08 | 4
Minute snapshots, serving count/waiting count/completed count:
09:00: 2/4/0; 09:01: 2/4/0; 09:02: 2/4/2; 09:03: 2/4/2;
09:04: 2/2/4; 09:05: 2/2/4; 09:06: 2/0/6; 09:07: 2/0/6; 09:08: 0/0/8.
Final completion 09:08; maximum start-wait 4 minutes. Total start-wait 20 minutes; mean 2.5 minutes. The final completion and waiting change because the assumed service duration changes, not because real performance was observed.

MODEL LIMIT
No early arrivals, variable service, interruptions, access needs, separate queues or later batches are modeled. Those need new supplied assumptions. Use eight paper counters for an independent tabletop check before relying even on the arithmetic; make no safety or staffing-adequacy conclusion from this example.
Download result .txt
You’re the final check

Check the worked example.

These checks use the worked example and its particular facts. With your own material, check your actual names, numbers, sources and rules; do not reuse the sample’s values as the answer.

Unsaved checks stay in this tab and reset when you reload. If you choose Save guide, its current example checkmarks are kept in this browser when storage is available.

A few things to watch for.

  • A minute’s arrivals must not jump ahead of people already waiting. Keep the tie-break and event order explicit.
  • Fixed service times are a simplifying assumption, not a measured guarantee. A queue arithmetic result cannot establish crowd safety or staffing adequacy.

What has been checked?

Documentation
No dated source review recorded.
Included files
No scoped artifact-check record.
AI workflow
Not run in a recorded consumer-AI workflow.
Time savings
Time savings not measured

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